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\n \n \n

\n \n 2026\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n \n One‑carbon pathway gene expression analyses in blood samples of subjects with trisomy 21.\n \n \n \n \n\n\n \n Vione, B.; Gaudesi, A. M.; Antonaros, F.; Cicilloni, M.; Vitale, L.; Piovesan, A.; Pelleri, M. C.; Strippoli, P.; Sperti, G.; Ramacieri, G.; Catapano, F.; Paradisi, P.; Pirazzoli, G. L.; Corvaglia, L. T.; Locatelli, C.; and Caracausi, M.\n\n\n \n\n\n\n Clinica Chimica Acta, 581: 120747. February 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"One‑carbon$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{vione_onecarbon_2026,\n\ttitle = {One‑carbon pathway gene expression analyses in blood samples of subjects with trisomy 21},\n\tvolume = {581},\n\tissn = {00098981},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0009898125006266},\n\tdoi = {10.1016/j.cca.2025.120747},\n\tlanguage = {en},\n\turldate = {2026-02-17},\n\tjournal = {Clinica Chimica Acta},\n\tauthor = {Vione, Beatrice and Gaudesi, Alessandro Maria and Antonaros, Francesca and Cicilloni, Michela and Vitale, Lorenza and Piovesan, Allison and Pelleri, Maria Chiara and Strippoli, Pierluigi and Sperti, Giacomo and Ramacieri, Giuseppe and Catapano, Francesca and Paradisi, Pietro and Pirazzoli, Gian Luca and Corvaglia, Luigi Tommaso and Locatelli, Chiara and Caracausi, Maria},\n\tmonth = feb,\n\tyear = {2026},\n\tkeywords = {SP3},\n\tpages = {120747},\n}\n\n\n\n

\n\n\n\n

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\n \n\n \n \n \n \n \n \n Performance Assessment of DL for Network Intrusion Detection on a Constrained IoT Device.\n \n \n \n \n\n\n \n Mazinani, A.; Antonucci, D.; Davoli, L.; and Ferrari, G.\n\n\n \n\n\n\n Future Internet, 18(1): 34. January 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"Performance$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{mazinani_performance_2026,\n\ttitle = {Performance {Assessment} of {DL} for {Network} {Intrusion} {Detection} on a {Constrained} {IoT} {Device}},\n\tvolume = {18},\n\tissn = {1999-5903},\n\turl = {https://www.mdpi.com/1999-5903/18/1/34},\n\tdoi = {10.3390/fi18010034},\n\tabstract = {This work investigates the deployment of Deep Learning (DL) models for network intrusion detection on resource-constrained IoT devices, using the public CICIoT2023 dataset. In particular, we consider the following DL models: Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), Temporal Convolutional Network (TCN), Multi-Layer Perceptron (MLP). Bayesian optimization is employed to fine-tune the models’ hyperparameters and ensure reliable performance evaluation across both binary (2-class) and multi-class (8-class, 34-class) intrusion detection. Then, the computational complexity of each DL model is analyzed—in terms of the number of Multiply–ACCumulate operations (MACCs), RAM usage, and inference time—through the STMicroelectronics Cube.AI Analyzer tool, with models being deployed on an STM32H7S78-DK board. To assess the practical deployability of the considered DL models, a trade-off score (balancing classification accuracy and computational efficiency) is introduced: according to this score, our experimental results indicate that MLP and TCN outperform the other models. Furthermore, Post-Training Quantization (PTQ) to 8-bit integer precision is applied, allowing the model size to be reduced by more than 90\\% with negligible performance degradation. This demonstrates the effectiveness of quantization in optimizing DL models for real-world deployment on resource-constrained IoT devices.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2026-02-10},\n\tjournal = {Future Internet},\n\tauthor = {Mazinani, Armin and Antonucci, Daniele and Davoli, Luca and Ferrari, Gianluigi},\n\tmonth = jan,\n\tyear = {2026},\n\tkeywords = {SP1, WP4},\n\tpages = {34},\n}\n\n\n\n

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\n\n\n

\n \n\n \n \n \n \n \n \n MLOps in the Healthcare Domain: a Systematic Literature Review.\n \n \n \n \n\n\n \n Mallardi, G.; Quaranta, L.; Calefato, F.; and Lanubile, F.\n\n\n \n\n\n\n In Taibi, D.; and Smite, D., editor(s), Software Engineering and Advanced Applications, volume 16082, pages 334–349, Cham, 2026. Springer Nature Switzerland\n Series Title: Lecture Notes in Computer Science\n\n\n\n
\n\n\n\n \n \n $\"MLOps$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{taibi_mlops_2026,\n\taddress = {Cham},\n\ttitle = {{MLOps} in the {Healthcare} {Domain}: a {Systematic} {Literature} {Review}},\n\tvolume = {16082},\n\tisbn = {978-3-032-04199-9 978-3-032-04200-2},\n\tshorttitle = {{MLOps} in the {Healthcare} {Domain}},\n\turl = {https://link.springer.com/10.1007/978-3-032-04200-2_23},\n\tdoi = {10.1007/978-3-032-04200-2_23},\n\tlanguage = {en},\n\turldate = {2025-10-28},\n\tbooktitle = {Software {Engineering} and {Advanced} {Applications}},\n\tpublisher = {Springer Nature Switzerland},\n\tauthor = {Mallardi, Giulio and Quaranta, Luigi and Calefato, Fabio and Lanubile, Filippo},\n\teditor = {Taibi, Davide and Smite, Darja},\n\tyear = {2026},\n\tnote = {Series Title: Lecture Notes in Computer Science},\n\tkeywords = {SP1, WP4},\n\tpages = {334--349},\n}\n\n\n\n

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\n \n 2025\n \n \n (80)\n \n \n

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\n \n\n \n \n \n \n \n \n Abstracts for the International Patellofemoral Pain Research Retreat. 1–4 October, 2025 Massachusetts General Hospital Sports Medicine Boston, USA.\n \n \n \n \n\n\n \n \n\n\n \n\n\n\n In JOSPT Open, volume 3, pages 501–529, October 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Abstracts$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{noauthor_abstracts_2025,\n\ttitle = {Abstracts for the {International} {Patellofemoral} {Pain} {Research} {Retreat}. 1–4 {October}, 2025 {Massachusetts} {General} {Hospital} {Sports} {Medicine} {Boston}, {USA}},\n\tvolume = {3},\n\tissn = {2832-8280},\n\turl = {https://www.jospt.org/doi/10.2519/josptopen.2025.0187},\n\tdoi = {10.2519/josptopen.2025.0187},\n\tabstract = {Abstracts presented at the 8th International Patellofemoral Research Retreat, 1st-4th October, 2025, in Boston, Massachusetts.\n            JOSPT Open 2025;3(4):501-529. Epub 19 September 2025. doi:10.2519/josptopen.2025.0187},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2026-02-17},\n\tbooktitle = {{JOSPT} {Open}},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {501--529},\n}\n\n\n\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Sensing regimes in potentiometric immunoassays.\n \n \n \n \n\n\n \n Macchia, E.; and Torsi, L.\n\n\n \n\n\n\n Nature Reviews Materials. December 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Sensing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{macchia_sensing_2025,\n\ttitle = {Sensing regimes in potentiometric immunoassays},\n\tissn = {2058-8437},\n\turl = {https://www.nature.com/articles/s41578-025-00863-6},\n\tdoi = {10.1038/s41578-025-00863-6},\n\tlanguage = {en},\n\turldate = {2026-02-17},\n\tjournal = {Nature Reviews Materials},\n\tauthor = {Macchia, Eleonora and Torsi, Luisa},\n\tmonth = dec,\n\tyear = {2025},\n\tkeywords = {SP3},\n}\n\n\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Association between triglyceride glucose-body mass index and diabetic nephropathy and renal function decline in type 2 diabetes: evidence of stronger links in men and older adults.\n \n \n \n \n\n\n \n Longo, S.; Zupo, F.; Menghini, R.; Fernández-Real, J. M.; and Federici, M.\n\n\n \n\n\n\n Acta Diabetologica, 63(1): 175–178. November 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Association$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{longo_association_2025,\n\ttitle = {Association between triglyceride glucose-body mass index and diabetic nephropathy and renal function decline in type 2 diabetes: evidence of stronger links in men and older adults},\n\tvolume = {63},\n\tissn = {1432-5233},\n\tshorttitle = {Association between triglyceride glucose-body mass index and diabetic nephropathy and renal function decline in type 2 diabetes},\n\turl = {https://link.springer.com/10.1007/s00592-025-02605-0},\n\tdoi = {10.1007/s00592-025-02605-0},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2026-02-17},\n\tjournal = {Acta Diabetologica},\n\tauthor = {Longo, Susanna and Zupo, Francesco and Menghini, Rossella and Fernández-Real, Jose Manuel and Federici, Massimo},\n\tmonth = nov,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {175--178},\n}\n\n\n\n

\n\n\n\n

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\n \n\n \n \n \n \n \n \n Glycometabolic cardiac dysfunction in HFpEF: Lessons from multi-omics studies.\n \n \n \n \n\n\n \n Longo, S.; Mollace, R.; Casagrande, V.; Bucciarelli, L.; Martelli, E.; Menghini, R.; Fernández-Real, J. M.; and Federici, M.\n\n\n \n\n\n\n Pharmacological Research, 222: 108032. December 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Glycometabolic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{longo_glycometabolic_2025,\n\ttitle = {Glycometabolic cardiac dysfunction in {HFpEF}: {Lessons} from multi-omics studies},\n\tvolume = {222},\n\tissn = {10436618},\n\tshorttitle = {Glycometabolic cardiac dysfunction in {HFpEF}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1043661825004578},\n\tdoi = {10.1016/j.phrs.2025.108032},\n\tlanguage = {en},\n\turldate = {2026-02-17},\n\tjournal = {Pharmacological Research},\n\tauthor = {Longo, Susanna and Mollace, Rocco and Casagrande, Viviana and Bucciarelli, Loredana and Martelli, Eugenio and Menghini, Rossella and Fernández-Real, Jose Manuel and Federici, Massimo},\n\tmonth = dec,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {108032},\n}\n\n\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Psychological flexibility mediates the long-term impact of adverse interpersonal experiences in childhood and adolescence.\n \n \n \n \n\n\n \n Fazio, L.; Semeraro, C.; Pennacchio, T. C.; Asselti, M. G.; Russo, M.; Cassibba, R.; Bertolino, A.; Rampino, A.; Grattagliano, I.; Pergola, G.; and Antonucci, L. A.\n\n\n \n\n\n\n BMC Psychology, 13(1): 927. August 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Psychological$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{fazio_psychological_2025,\n\ttitle = {Psychological flexibility mediates the long-term impact of adverse interpersonal experiences in childhood and adolescence},\n\tvolume = {13},\n\tissn = {2050-7283},\n\turl = {https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-025-03297-5},\n\tdoi = {10.1186/s40359-025-03297-5},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2026-02-17},\n\tjournal = {BMC Psychology},\n\tauthor = {Fazio, Leonardo and Semeraro, Cristina and Pennacchio, Teresa Claudia and Asselti, Martina Grazia and Russo, Marianna and Cassibba, Rosalinda and Bertolino, Alessandro and Rampino, Antonio and Grattagliano, Ignazio and Pergola, Giulio and Antonucci, Linda Antonella},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {927},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Pre-vaccination immune markers predict response to BNT162b2 mRNA vaccine in vulnerable groups – The CONVERS project, report from a pediatric tertiary hospital.\n \n \n \n \n\n\n \n Cotugno, N.; Sanna, M.; Amodio, D.; Morrocchi, E.; Pighi, C.; Medri, C.; Pascucci, G. R.; Santilli, V.; Manno, E. C.; Zangari, P.; Rossetti, C.; Colantoni, N.; Olivieri, G.; Emili, E.; Neri, A.; Rotili, A.; Rossi, P.; Levy, O.; Putignani, L.; Palma, P.; Romani, L.; Finocchi, A.; Cancrini, C.; Moschese, V.; Sgrulletti, M.; Lancella, L.; Bernardi, S.; De Luca, M.; Giancotta, C.; Colagrossi, L.; Bonfante, F.; Profeti, E.; Franzese, E.; Amodeo, A.; Perno, C. F.; Atti, M. C. D.; Plebani, C.; Giaquinto, C.; Valentini, D.; Villani, A.; De Angelis, P.; Rea, F.; Tambucci, R.; Rivalta, B.; Pacillo, L.; and Rotulo, G. A.\n\n\n \n\n\n\n Vaccine, 49: 126778. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Pre-vaccination$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{cotugno_pre-vaccination_2025,\n\ttitle = {Pre-vaccination immune markers predict response to {BNT162b2} {mRNA} vaccine in vulnerable groups – {The} {CONVERS} project, report from a pediatric tertiary hospital},\n\tvolume = {49},\n\tissn = {0264410X},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0264410X25000751},\n\tdoi = {10.1016/j.vaccine.2025.126778},\n\tlanguage = {en},\n\turldate = {2026-02-17},\n\tjournal = {Vaccine},\n\tauthor = {Cotugno, Nicola and Sanna, Marco and Amodio, Donato and Morrocchi, Elena and Pighi, Chiara and Medri, Chiara and Pascucci, Giuseppe Rubens and Santilli, Veronica and Manno, Emma Concetta and Zangari, Paola and Rossetti, Chiara and Colantoni, Nicole and Olivieri, Giulio and Emili, Elena and Neri, Alessia and Rotili, Arianna and Rossi, Paolo and Levy, Ofer and Putignani, Lorenza and Palma, Paolo and Romani, Lorenza and Finocchi, Andrea and Cancrini, Caterina and Moschese, Viviana and Sgrulletti, Mayla and Lancella, Laura and Bernardi, Stefania and De Luca, Maia and Giancotta, Carmela and Colagrossi, Luna and Bonfante, Francesco and Profeti, Elisa and Franzese, Enrica and Amodeo, Antonino and Perno, Carlo Federico and Atti, Marta Ciofi Degli and Plebani, Carlo and Giaquinto, Carlo and Valentini, Diletta and Villani, Alberto and De Angelis, Paola and Rea, Francesca and Tambucci, Renato and Rivalta, Beatrice and Pacillo, Lucia and Rotulo, Gioacchino Andrea},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {126778},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A LLMOps-Driven Framework for Clinical Data Harmonization.\n \n \n \n \n\n\n \n Marfoglia, A.; Robustelli, A.; D'Errico, C.; Mellone, S.; and Carbonaro, A.\n\n\n \n\n\n\n In Proceedings of the 1st ECAI Workshop on Machine Learning Operations, Bologna, Italy, October 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{marfoglia_llmops-driven_2025,\n\taddress = {Bologna, Italy},\n\ttitle = {A {LLMOps}-{Driven} {Framework} for {Clinical} {Data} {Harmonization}},\n\turl = {https://ceur-ws.org/Vol-4109/paper3.pdf},\n\tbooktitle = {Proceedings of the 1st {ECAI} {Workshop} on {Machine} {Learning} {Operations}},\n\tauthor = {Marfoglia, Alberto and Robustelli, Antonio and D'Errico, Christian and Mellone, Sabato and Carbonaro, Antonella},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Feasibility of MLOps-based healthcare pipelines in ensuring the Cybersecurity Framework.\n \n \n \n \n\n\n \n Robustelli, A.; Marfoglia, A.; D'Errico, C.; Mellone, S.; and Carbonaro, A.\n\n\n \n\n\n\n In Proceedings of the 1st ECAI Workshop on Machine Learning Operations, Bologna, Italy, October 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Feasibility$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{robustelli_feasibility_2025,\n\taddress = {Bologna, Italy},\n\ttitle = {Feasibility of {MLOps}-based healthcare pipelines in ensuring the {Cybersecurity} {Framework}},\n\turl = {https://ceur-ws.org/Vol-4109/paper1.pdf},\n\tbooktitle = {Proceedings of the 1st {ECAI} {Workshop} on {Machine} {Learning} {Operations}},\n\tauthor = {Robustelli, Antonio and Marfoglia, Alberto and D'Errico, Christian and Mellone, Sabato and Carbonaro, Antonella},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

\n\n\n\n

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\n \n\n \n \n \n \n \n \n Trolox, r-irisin and resveratrol cocktail to counteract osteoblast metabolism alterations in osteoarthritis and osteoporosis.\n \n \n \n \n\n\n \n Bonanni, R.; Falvino, A.; Smakaj, A.; Tranquillo, L.; Rinaldi, A. M.; D’Arcangelo, G.; Cifelli, P.; Tancredi, V.; Cariati, I.; and Tarantino, U.\n\n\n \n\n\n\n Journal of Bone and Mineral Metabolism, 43(6): 672–684. November 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Trolox,$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bonanni_trolox_2025,\n\ttitle = {Trolox, r-irisin and resveratrol cocktail to counteract osteoblast metabolism alterations in osteoarthritis and osteoporosis},\n\tvolume = {43},\n\tissn = {0914-8779, 1435-5604},\n\turl = {https://link.springer.com/10.1007/s00774-025-01642-7},\n\tdoi = {10.1007/s00774-025-01642-7},\n\tabstract = {Abstract\n            \n              Introduction\n              Osteoarthritis and osteoporosis are age-related musculoskeletal disorders characterized by increased oxidative stress and cellular senescence, which contribute to altered metabolism and disease progression. Although research in this field is constantly evolving, the discovery of new molecular targets and drug combinations to counteract musculoskeletal disorders remains a goal of great interest. This study aimed to evaluate the efficacy of a cocktail of trolox, recombinant irisin (r-irisin) and resveratrol in modulation of osteoblastic metabolism by investigating the expression of NADPH oxidase 4 (NOX4), sirtuin 1 (SIRT1) and pentraxin 3 (PTX3).\n            \n            \n              Materials and methods\n              20 male patients undergoing hip arthroplasty were enrolled, including ten patients with coxarthrosis and ten patients with osteoporosis. Femoral head biopsies were taken from each patient to isolate primary osteoblast cultures, which were treated with the cocktail for 6 days.\n            \n            \n              Results\n              The cocktail of trolox, r-irisin and resveratrol increased cell viability, and reduced ROS and senescence β-galactosidase activity (SA-β-Gal) levels. In addition, western blotting analysis showed reduced expression of NOX4 and increased expression of SIRT1 and PTX3 in both experimental groups, although with more pronounced effects in osteoarthritic patients, highlighting lower treatment efficacy in the presence of osteoporosis.\n            \n            \n              Conclusions\n              The improvement in cell viability and reduction in oxidative stress and cellular senescence observed through treatment-induced modulation of the NOX4–SIRT1 axis and PTX3 suggests a protective role for these biomarkers in bone metabolism. These findings could offer new perspectives in counteracting the effects of aging on the skeletal system by improving bone health and mitigating metabolic alterations.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2026-02-17},\n\tjournal = {Journal of Bone and Mineral Metabolism},\n\tauthor = {Bonanni, Roberto and Falvino, Angela and Smakaj, Amarildo and Tranquillo, Lucia and Rinaldi, Anna Maria and D’Arcangelo, Giovanna and Cifelli, Pierangelo and Tancredi, Virginia and Cariati, Ida and Tarantino, Umberto},\n\tmonth = nov,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {672--684},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Pyrolyzed Walnut Shell‐Based Flexible Electrodes for Magnetically Triggered ON/OFF DNA Release.\n \n \n \n \n\n\n \n Bollella, P.; Cassano, B.; Marchianò, V.; Tricase, A.; Macchia, E.; and Torsi, L.\n\n\n \n\n\n\n Advanced NanoBiomed Research, 5(10): 2500131. October 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Pyrolyzed$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bollella_pyrolyzed_2025,\n\ttitle = {Pyrolyzed {Walnut} {Shell}‐{Based} {Flexible} {Electrodes} for {Magnetically} {Triggered} {ON}/{OFF} {DNA} {Release}},\n\tvolume = {5},\n\tcopyright = {http://creativecommons.org/licenses/by/4.0/},\n\tissn = {2699-9307, 2699-9307},\n\turl = {https://advanced.onlinelibrary.wiley.com/doi/10.1002/anbr.202500131},\n\tdoi = {10.1002/anbr.202500131},\n\tabstract = {A magnetically gated, enzymatically driven DNA release platform based on sustainable pyrolyzed walnut shell‐derived carbon electrodes is reported. Upon glucose addition under aerobic conditions, biocatalytic oxygen reduction at the cathode induces a local pH increase, resulting in electrostatic repulsion of negatively charged 5(6)‐carboxyfluorescein‐labeled DNA (FAM‐labeled DNA). Electrochemical analysis reveals an oxygen reduction reaction (ORR) onset potential of +0.576 ± 0.003 V vs. Ag/AgCl and a maximum current of −8.2 ± 0.4 μA. Electrochemical impedance spectroscopy (EIS) confirms a post‐ORR increase in interfacial resistance from 6.2 ± 0.5 to 11.1 ± 0.9 kΩ. DNA release reaches 97\\% after 400 min, corresponding to a surface density of 22 ± 4 nmol cm\n              −2\n              . A competing enzymatic gate, composed of co‐immobilized glucose oxidase and catalase (GOx–CAT) on magnetic nanoparticles (MNPs), enables remote suppression of electron flow and DNA release upon application of a 0.3 T magnetic field. Under “OFF” conditions, DNA release is reduced to 1\\%, and anodic current decreases by 60\\%. The system exhibits excellent reversibility over four ON–OFF cycles with minimal performance degradation. This bioelectronic platform represents a self‐powered, reversible strategy for stimuli‐responsive drug release.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2026-02-17},\n\tjournal = {Advanced NanoBiomed Research},\n\tauthor = {Bollella, Paolo and Cassano, Blanca and Marchianò, Verdiana and Tricase, Angelo and Macchia, Eleonora and Torsi, Luisa},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2500131},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MLOps-Driven Automation of Regulatory Documentation for AI-Based Medical Software.\n \n \n \n \n\n\n \n Rosmarino, F.; Mallardi, G.; Quaranta, L.; and Lanubile, F.\n\n\n \n\n\n\n In Proceedings of the 1st ECAI Workshop on Machine Learning Operations, Bologna, Italy, October 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"MLOps-Driven$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{rosmarino_mlops-driven_2025,\n\taddress = {Bologna, Italy},\n\ttitle = {{MLOps}-{Driven} {Automation} of {Regulatory} {Documentation} for {AI}-{Based} {Medical} {Software}},\n\turl = {https://ceur-ws.org/Vol-4109/paper8.pdf},\n\tbooktitle = {Proceedings of the 1st {ECAI} {Workshop} on {Machine} {Learning} {Operations}},\n\tauthor = {Rosmarino, Fabrizio and Mallardi, Giulio and Quaranta, Luigi and Lanubile, Filippo},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Experimental Performance Assessment and Comparison of IMU-Equipped Wearable Devices for Gait Analysis.\n \n \n \n \n\n\n \n Mattioli, V.; Sanfelici, M.; Bettini, M.; Davoli, L.; Belli, L.; Raheli, R.; and Ferrari, G.\n\n\n \n\n\n\n In 2025 International Workshop on Biomedical Applications, Technologies and Sensors (BATS), pages 139–144, Rome, Italy, October 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Experimental$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{mattioli_experimental_2025,\n\taddress = {Rome, Italy},\n\ttitle = {Experimental {Performance} {Assessment} and {Comparison} of {IMU}-{Equipped} {Wearable} {Devices} for {Gait} {Analysis}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3315-7510-6},\n\turl = {https://ieeexplore.ieee.org/document/11336176/},\n\tdoi = {10.1109/BATS67559.2025.11336176},\n\turldate = {2026-01-22},\n\tbooktitle = {2025 {International} {Workshop} on {Biomedical} {Applications}, {Technologies} and {Sensors} ({BATS})},\n\tpublisher = {IEEE},\n\tauthor = {Mattioli, Veronica and Sanfelici, Marco and Bettini, Marta and Davoli, Luca and Belli, Laura and Raheli, Riccardo and Ferrari, Gianluigi},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {139--144},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Signal Normalization Approach for Robust Driving Stress Assessment Using Multi-Domain Physiological Data.\n \n \n \n \n\n\n \n Fruet, D.; Barà, C.; Pernice, R.; Iovino, M.; Faes, L.; and Nollo, G.\n\n\n \n\n\n\n Eng, 6(11): 288. October 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{fruet_signal_2025,\n\ttitle = {A {Signal} {Normalization} {Approach} for {Robust} {Driving} {Stress} {Assessment} {Using} {Multi}-{Domain} {Physiological} {Data}},\n\tvolume = {6},\n\tissn = {2673-4117},\n\turl = {https://www.mdpi.com/2673-4117/6/11/288},\n\tdoi = {10.3390/eng6110288},\n\tabstract = {Objective: Stress recognition is a widely investigated and debated area in biomedical research. Physiological monitoring has gained increasing attention as one of the methodologies used to assess an individual’s stress level. In this study, we investigated the effectiveness of a novel normalization technique applied to multi-domain physiological data for the objective classification of stress levels using a feature extraction approach. Methods: Electrocardiographic (ECG) and respiratory data from a publicly available database, collected from drivers experiencing various stress levels, underwent a novel inter-subject normalization procedure. This method involved adjusting the time scale of the original data to a common scale across subjects according to fixed resting heart and respiratory rates. Subsequently, a feature-based stress state classification procedure was conducted using the Support Vector Machine (SVM) algorithm. The efficacy of this inter-subject normalization procedure was assessed by comparing the classification results obtained using features from the original signals with those obtained from the inter-subject-normalized signals. Additionally, the inter-subject normalization procedure was compared with two common feature normalization approaches: standardization and scaling. Results: Features derived from the subject-normalized signals yielded improved performance, significantly enhancing accuracy from 68\\% to 73\\%, as well as precision and sensitivity. Conclusions: The novel inter-subject normalization procedure proves to be an effective technique for highlighting differences in features among various stress states and for mitigating basal physiological variability across subjects. Significance: Using inter-subject normalization on multi-domain physiological signals holds promise as a method to improve multilevel stress classification through feature extraction, ensuring that the features maintain their correspondence even after the normalization process.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2025-12-11},\n\tjournal = {Eng},\n\tauthor = {Fruet, Damiano and Barà, Chiara and Pernice, Riccardo and Iovino, Marta and Faes, Luca and Nollo, Giandomenico},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {288},\n}\n\n\n\n

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\n Objective: Stress recognition is a widely investigated and debated area in biomedical research. Physiological monitoring has gained increasing attention as one of the methodologies used to assess an individual’s stress level. In this study, we investigated the effectiveness of a novel normalization technique applied to multi-domain physiological data for the objective classification of stress levels using a feature extraction approach. Methods: Electrocardiographic (ECG) and respiratory data from a publicly available database, collected from drivers experiencing various stress levels, underwent a novel inter-subject normalization procedure. This method involved adjusting the time scale of the original data to a common scale across subjects according to fixed resting heart and respiratory rates. Subsequently, a feature-based stress state classification procedure was conducted using the Support Vector Machine (SVM) algorithm. The efficacy of this inter-subject normalization procedure was assessed by comparing the classification results obtained using features from the original signals with those obtained from the inter-subject-normalized signals. Additionally, the inter-subject normalization procedure was compared with two common feature normalization approaches: standardization and scaling. Results: Features derived from the subject-normalized signals yielded improved performance, significantly enhancing accuracy from 68% to 73%, as well as precision and sensitivity. Conclusions: The novel inter-subject normalization procedure proves to be an effective technique for highlighting differences in features among various stress states and for mitigating basal physiological variability across subjects. Significance: Using inter-subject normalization on multi-domain physiological signals holds promise as a method to improve multilevel stress classification through feature extraction, ensuring that the features maintain their correspondence even after the normalization process.\n

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\n \n\n \n \n \n \n \n \n From raw data to research-ready: A FHIR-based transformation pipeline in a real-world oncology setting.\n \n \n \n \n\n\n \n Carbonaro, A.; Giorgetti, L.; Ridolfi, L.; Pasolini, R.; Pagliarani, A.; Cavallucci, M.; Andalò, A.; Gaudio, L. D.; De Angelis, P.; Vespignani, R.; and Gentili, N.\n\n\n \n\n\n\n Computers in Biology and Medicine, 197: 111051. October 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"From$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{carbonaro_raw_2025,\n\ttitle = {From raw data to research-ready: {A} {FHIR}-based transformation pipeline in a real-world oncology setting},\n\tvolume = {197},\n\tissn = {00104825},\n\tshorttitle = {From raw data to research-ready},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0010482525014039},\n\tdoi = {10.1016/j.compbiomed.2025.111051},\n\tlanguage = {en},\n\turldate = {2025-12-11},\n\tjournal = {Computers in Biology and Medicine},\n\tauthor = {Carbonaro, Antonella and Giorgetti, Luca and Ridolfi, Lorenzo and Pasolini, Roberto and Pagliarani, Andrea and Cavallucci, Martina and Andalò, Alice and Gaudio, Livia Del and De Angelis, Paolo and Vespignani, Roberto and Gentili, Nicola},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {111051},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Editorial: Implementing digital twins in healthcare: pathways to person-centric solutions.\n \n \n \n \n\n\n \n Carbonaro, A.; Marfoglia, A.; Quaranta, L.; Mellone, S.; and Lanubile, F.\n\n\n \n\n\n\n Frontiers in Digital Health, 7: 1741466. December 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Editorial:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{carbonaro_editorial_2025,\n\ttitle = {Editorial: {Implementing} digital twins in healthcare: pathways to person-centric solutions},\n\tvolume = {7},\n\tissn = {2673-253X},\n\tshorttitle = {Editorial},\n\turl = {https://www.frontiersin.org/articles/10.3389/fdgth.2025.1741466/full},\n\tdoi = {10.3389/fdgth.2025.1741466},\n\tabstract = {Over the past decade, digital twins (DTs) have evolved from an engineering metaphor into a powerful paradigm for healthcare innovation. By dynamically linking physical and digital representations of patients, devices, and clinical processes, DTs enable continuous learning systems where data, knowledge, and decision-making converge. This transformation goes far beyond simulation: it redefines how we understand, monitor, and personalize health, moving toward predictive, preventive, personalized, and participatory (4P) medicine. The Research Topic “\n              Implementing Digital Twins in Healthcare: Pathways to Person-Centric Solutions\n              ” brings together 8 multidisciplinary contributions that explore the translation of digital twin concepts into practical, ethical, and sustainable healthcare applications. Collectively, the works emphasize that DT implementation is not a purely technological endeavor, but rather a systemic, epistemological, and human-centered transformation of care.},\n\turldate = {2025-12-11},\n\tjournal = {Frontiers in Digital Health},\n\tauthor = {Carbonaro, Antonella and Marfoglia, Alberto and Quaranta, Luigi and Mellone, Sabato and Lanubile, Filippo},\n\tmonth = dec,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {1741466},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Hybrid Approach Integrating Clinical Data and Tomography to Improve Diagnosis of Parkinson’s Disease.\n \n \n \n \n\n\n \n Aversano, L.; Iammarino, M.; Madau, A.; Montano, D.; and Verdone, C.\n\n\n \n\n\n\n ACM Transactions on Computing for Healthcare, 6(4): 1–22. October 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{aversano_hybrid_2025,\n\ttitle = {A {Hybrid} {Approach} {Integrating} {Clinical} {Data} and {Tomography} to {Improve} {Diagnosis} of {Parkinson}’s {Disease}},\n\tvolume = {6},\n\tissn = {2691-1957, 2637-8051},\n\turl = {https://dl.acm.org/doi/10.1145/3735660},\n\tdoi = {10.1145/3735660},\n\tabstract = {Parkinson’s Disease (PD) is a neurodegenerative condition primarily affecting the elderly but also occurring in younger individuals. It is caused by a progressive loss of nerve cells in the brain’s substantia nigra that release dopamine, essential for controlling movements. Dopamine deficiency results in symptoms affecting both motor and non-motor functions, which vary among individuals. Diagnosis relies on clinical symptoms and medical history, often supported by brain scans, as there is no specific diagnostic test available. Diagnosis is challenging due to vague initial symptoms resembling other conditions. Current research indicates that AI can significantly enhance data and image analysis, aiding in the diagnosis and monitoring of PD progression. To this aim, this study proposes a hybrid model allowing the integrated use of clinical data and single photon emission computed tomography images of a patient to predict the presence of the disease. The approach consists of a combination of two types of neural networks, an LSTM for clinical data and a CNN for images. The validation is performed on a widely validated dataset belonging to the Parkinson’s Progression Markers Initiative, from which the data recording visits of 1,814 patients were extracted. The obtained results are interesting and useful to address further investigations.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-11-24},\n\tjournal = {ACM Transactions on Computing for Healthcare},\n\tauthor = {Aversano, Lerina and Iammarino, Martina and Madau, Antonella and Montano, Debora and Verdone, Chiara},\n\tmonth = oct,\n\tyear = {2025},\n\tkeywords = {SP1},\n\tpages = {1--22},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n “KAN you hear me?” Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding.\n \n \n \n \n\n\n \n Koudounas, A.; La Quatra, M.; Pastor, E.; Siniscalchi, S. M.; and Baralis, E.\n\n\n \n\n\n\n In Interspeech 2025, pages 4123–4127, August 2025. ISCA\n \n\n\n\n
\n\n\n\n \n \n $\"“KAN$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{koudounas_kan_2025,\n\ttitle = {“{KAN} you hear me?” {Exploring} {Kolmogorov}-{Arnold} {Networks} for {Spoken} {Language} {Understanding}},\n\tshorttitle = {“{KAN} you hear me?},\n\turl = {https://www.isca-archive.org/interspeech_2025/koudounas25_interspeech.html},\n\tdoi = {10.21437/Interspeech.2025-1612},\n\tlanguage = {en},\n\turldate = {2025-11-19},\n\tbooktitle = {Interspeech 2025},\n\tpublisher = {ISCA},\n\tauthor = {Koudounas, Alkis and La Quatra, Moreno and Pastor, Eliana and Siniscalchi, Sabato Marco and Baralis, Elena},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {4123--4127},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MVP: Multi-source Voice Pathology detection.\n \n \n \n \n\n\n \n Koudounas, A.; La Quatra, M.; Ciravegna, G.; Fantini, M.; Crosetti, E.; Succo, G.; Cerquitelli, T.; Siniscalchi, S. M.; and Baralis, E.\n\n\n \n\n\n\n In Interspeech 2025, pages 3548–3552, August 2025. ISCA\n \n\n\n\n
\n\n\n\n \n \n $\"MVP:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{koudounas_mvp_2025,\n\ttitle = {{MVP}: {Multi}-source {Voice} {Pathology} detection},\n\tshorttitle = {{MVP}},\n\turl = {https://www.isca-archive.org/interspeech_2025/koudounas25b_interspeech.html},\n\tdoi = {10.21437/Interspeech.2025-1868},\n\tlanguage = {en},\n\turldate = {2025-11-19},\n\tbooktitle = {Interspeech 2025},\n\tpublisher = {ISCA},\n\tauthor = {Koudounas, Alkis and La Quatra, Moreno and Ciravegna, Gabriele and Fantini, Marco and Crosetti, Erika and Succo, Giovanni and Cerquitelli, Tania and Siniscalchi, Sabato Marco and Baralis, Elena},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {3548--3552},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Exploring Generative Error Correction for Dysarthric Speech Recognition.\n \n \n \n \n\n\n \n La Quatra, M.; Koudounas, A.; Salerno, V. M.; and Siniscalchi, S. M.\n\n\n \n\n\n\n In Interspeech 2025, pages 3284–3288, August 2025. ISCA\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{la_quatra_exploring_2025,\n\ttitle = {Exploring {Generative} {Error} {Correction} for {Dysarthric} {Speech} {Recognition}},\n\turl = {https://www.isca-archive.org/interspeech_2025/laquatra25_interspeech.html},\n\tdoi = {10.21437/Interspeech.2025-1553},\n\tlanguage = {en},\n\turldate = {2025-11-19},\n\tbooktitle = {Interspeech 2025},\n\tpublisher = {ISCA},\n\tauthor = {La Quatra, Moreno and Koudounas, Alkis and Salerno, Valerio Mario and Siniscalchi, Sabato Marco},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {3284--3288},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Self-monitoring of Developers’ Emotions: the Case of Agile Retrospective Meetings.\n \n \n \n \n\n\n \n Grassi, D.; Lanubile, F.; Novielli, N.; Quaranta, L.; and Serebrenik, A.\n\n\n \n\n\n\n ACM Transactions on Software Engineering and Methodology. September 2025.\n Place: New York, NY, USA\n\n\n\n
\n\n\n\n \n \n $\"Self-monitoring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{grassi_self-monitoring_2025,\n\ttitle = {Self-monitoring of {Developers}’ {Emotions}: the {Case} of {Agile} {Retrospective} {Meetings}},\n\tissn = {1049-331X},\n\turl = {https://doi.org/10.1145/3766064},\n\tdoi = {10.1145/3766064},\n\tabstract = {Developers experience a wide range of emotions while creating software. Being able to identify the causes of one’s own and peers’ emotions can equip developers with the ability to regulate their behavior to restore positive moods and productivity. In this paper, we investigate to what extent self-monitoring of emotions can enhance agile retrospective meetings by improving the emotion awareness of participants. To this aim, we conducted a controlled experiment involving three software development teams involving two student teams and one professional developers team. The experiment design involves the collection of biometrics and self-reported information about emotions, which are then visualized before the retrospective meetings to inform discussion using EmoVizPhy, a tool that we designed and implemented for this aim. While students found that self-monitoring helped them recall significant emotional episodes, leading to more meaningful contributions during retrospectives, professional developers perceived limited benefits from this practice. Furthermore, based on the analysis of corrective actions identified by the participants during the study, we hypothesize that self-monitoring of emotions through EmoVizPhy may play a valuable role in facilitating the consolidation of new agile teams for which roles and collaboration dynamics are still being defined.},\n\tjournal = {ACM Transactions on Software Engineering and Methodology},\n\tpublisher = {Association for Computing Machinery},\n\tauthor = {Grassi, Daniela and Lanubile, Filippo and Novielli, Nicole and Quaranta, Luigi and Serebrenik, Alexander},\n\tmonth = sep,\n\tyear = {2025},\n\tnote = {Place: New York, NY, USA},\n\tkeywords = {SP1, WP4, agile teams, biometric sensors, emotion awareness, retrospective meetings, visualization},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Markov model for estimating the cost-effectiveness of immunotherapy for newly diagnosed multiple myeloma patients.\n \n \n \n \n\n\n \n Bilancia, M.; Solimando, A. G.; Manca, F.; Vacca, A.; and Ria, R.\n\n\n \n\n\n\n Computational Statistics and Data Analysis, 206: 108130. June 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bilancia_markov_2025,\n\ttitle = {A {Markov} model for estimating the cost-effectiveness of immunotherapy for newly diagnosed multiple myeloma patients},\n\tvolume = {206},\n\tissn = {01679473},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0167947325000064},\n\tdoi = {10.1016/j.csda.2025.108130},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Computational Statistics and Data Analysis},\n\tauthor = {Bilancia, Massimo and Solimando, Antonio Giovanni and Manca, Fabio and Vacca, Angelo and Ria, Roberto},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {108130},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Exploring brain age prediction through MRI molecular-enriched functional connectivity.\n \n \n \n \n\n\n \n Pinnamonti, M; Moretto, M; Sammassimo, V; and Veronese, M\n\n\n \n\n\n\n In OHBM 2025 Annual Meeting Abstract Book, June 2025. Zenodo\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{pinnamonti_exploring_2025,\n\ttitle = {Exploring brain age prediction through {MRI} molecular-enriched functional connectivity},\n\tcopyright = {Creative Commons Attribution 4.0 International},\n\turl = {https://zenodo.org/doi/10.5281/zenodo.15641971},\n\tdoi = {10.5281/ZENODO.15641971},\n\tabstract = {The Abstract Book of OHBM's 31st Annual Meeting in Brisbane, Australia, is provided by Aperture Neuro, OHBM's official journal.},\n\turldate = {2025-10-15},\n\tbooktitle = {{OHBM} 2025 {Annual} {Meeting} {Abstract} {Book}},\n\tpublisher = {Zenodo},\n\tauthor = {Pinnamonti, M and Moretto, M and Sammassimo, V and Veronese, M},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Addressing Current Unmet Clinical Needs by Co-Designing a Novel Web Interface for Decision Support in Pediatric Type 1 Diabetes.\n \n \n \n \n\n\n \n Cossu, L.; Cappon, G.; Pellizzari, E.; Deodati, A.; Schiaffini, R.; Cianfarani, S.; Sparacino, G.; and Facchinetti, A.\n\n\n \n\n\n\n In 2025 IEEE 13th International Conference on Healthcare Informatics (ICHI), pages 689–690, Rende, Italy, June 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Addressing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{cossu_addressing_2025,\n\taddress = {Rende, Italy},\n\ttitle = {Addressing {Current} {Unmet} {Clinical} {Needs} by {Co}-{Designing} a {Novel} {Web} {Interface} for {Decision} {Support} in {Pediatric} {Type} 1 {Diabetes}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3315-2094-6},\n\turl = {https://ieeexplore.ieee.org/document/11081626/},\n\tdoi = {10.1109/ICHI64645.2025.00101},\n\turldate = {2025-10-15},\n\tbooktitle = {2025 {IEEE} 13th {International} {Conference} on {Healthcare} {Informatics} ({ICHI})},\n\tpublisher = {IEEE},\n\tauthor = {Cossu, Luca and Cappon, Giacomo and Pellizzari, Elisa and Deodati, Annalisa and Schiaffini, Riccardo and Cianfarani, Stefano and Sparacino, Giovanni and Facchinetti, Andrea},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {689--690},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Progressive NK Cell Dysfunction and ILC Imbalance Favor Immune Evasion in Multiple Myeloma.\n \n \n \n \n\n\n \n Bilotta, M. T.; Solimando, A. G.; Desantis, V.; Di Marzo, L.; Sabatini, A.; Forcelloni, S.; Andriano, A.; Morizio, A.; Argentiero, A.; Ria, R.; Quatrini, L.; Moretta, L.; Vacca, P.; and Tumino, N.\n\n\n \n\n\n\n Blood Advances,bloodadvances.2025016659. September 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Progressive$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bilotta_progressive_2025,\n\ttitle = {Progressive {NK} {Cell} {Dysfunction} and {ILC} {Imbalance} {Favor} {Immune} {Evasion} in {Multiple} {Myeloma}},\n\tissn = {2473-9529, 2473-9537},\n\turl = {https://ashpublications.org/bloodadvances/article/doi/10.1182/bloodadvances.2025016659/547195/Progressive-NK-Cell-Dysfunction-and-ILC-Imbalance},\n\tdoi = {10.1182/bloodadvances.2025016659},\n\tlanguage = {en},\n\turldate = {2025-10-15},\n\tjournal = {Blood Advances},\n\tauthor = {Bilotta, Maria Teresa and Solimando, Antonio Giovanni and Desantis, Vanessa and Di Marzo, Lucia and Sabatini, Andrea and Forcelloni, Sergio and Andriano, Alessandro and Morizio, Arcangelo and Argentiero, Antonella and Ria, Roberto and Quatrini, Linda and Moretta, Lorenzo and Vacca, Paola and Tumino, Nicola},\n\tmonth = sep,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {bloodadvances.2025016659},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Graphene‐Based Opto‐Electronic Platform for Ultra‐Sensitive Biomarker Detection at Zeptomolar Concentrations.\n \n \n \n \n\n\n \n Piscitelli, M.; Franco, C. D.; Bianco, G. V.; Bruno, G.; Macchia, E.; Torsi, L.; and Scamarcio, G.\n\n\n \n\n\n\n Small Methods, 9(8): 2402026. August 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Graphene‐Based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{piscitelli_graphenebased_2025,\n\ttitle = {Graphene‐{Based} {Opto}‐{Electronic} {Platform} for {Ultra}‐{Sensitive} {Biomarker} {Detection} at {Zeptomolar} {Concentrations}},\n\tvolume = {9},\n\tissn = {2366-9608, 2366-9608},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/smtd.202402026},\n\tdoi = {10.1002/smtd.202402026},\n\tabstract = {Abstract\n            \n              A ground‐breaking graphene‐based biosensor designed for label‐free detection of immunoglobulin M (IgM) achieving a remarkable concentration of 100 zeptomolar (10\n              −19\n              m\n              ), is reported. The sensor is a two‐terminal device and incorporates a millimeter‐wide gold interface, bio‐functionalized with ≈10\n              12\n              anti‐IgM antibodies and capacitively coupled to a bare graphene electrode through a water‐soaked paper strip. In this configuration, few affinity binding events trigger a collective electrostatic reorganization of the protein layer, leading to an extended surface potential (SP) shift of the biofunctionalized Au surface. The SP shift, mediated by electrolyte capacitive coupling, induces a corresponding shift in the Fermi level of graphene. This shifts the graphene phonon frequencies, which are measured by Raman spectroscopy. Decoupling the sensing interface from the transducing graphene layer provides flexibility in surface chemistry modifications, while preserving the graphene integrity. A key aspect of this biosensor is its ability to precisely determine the graphene charge neutrality point from the voltage dependence of phonon frequency shifts, enabling detections of biomarker at unprecedented low concentrations. The integration of graphene with optical probing demonstrates a proof‐of‐concept and establishes a ground‐breaking approach to in situ biomarker detection, setting the stage for a future generation of portable opto‐electronic high‐performance diagnostic tools for single‐marker detection.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2025-10-15},\n\tjournal = {Small Methods},\n\tauthor = {Piscitelli, Matteo and Franco, Cinzia Di and Bianco, Giuseppe Valerio and Bruno, Giovanni and Macchia, Eleonora and Torsi, Luisa and Scamarcio, Gaetano},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2402026},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Plasmonic Single‐Molecule Affinity Detection at 10$^{\\textrm{−20}}$ Molar.\n \n \n \n \n\n\n \n Macchia, E.; Franco, C. D.; Scandurra, C.; Sarcina, L.; Piscitelli, M.; Catacchio, M.; Caputo, M.; Bollella, P.; Scamarcio, G.; and Torsi, L.\n\n\n \n\n\n\n Advanced Materials, 37(9): 2418610. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Plasmonic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{macchia_plasmonic_2025,\n\ttitle = {Plasmonic {Single}‐{Molecule} {Affinity} {Detection} at 10$^{\\textrm{−20}}$ {Molar}},\n\tvolume = {37},\n\tissn = {0935-9648, 1521-4095},\n\turl = {https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202418610},\n\tdoi = {10.1002/adma.202418610},\n\tabstract = {Abstract\n            \n              DNA can be readily amplified through replication, enabling the detection of a single‐target copy. A comparable performance for proteins in immunoassays has yet to be fully assessed. Surface‐plasmon‐resonance (SPR) serves as a probe capable of performing assays at concentrations typically around 10⁻⁹ molar. In this study, plasmonic single‐molecule assays for both proteins and DNA are demonstrated, achieving limits‐of‐detections (LODs) as low as 10⁻\n              2\n              ⁰ molar (1 ± 1 molecule in 0.1 mL), even in human serum, in 1 h. This represents an improvement in typical SPR LODs by eleven orders‐of‐magnitude. The single‐molecule SPR assay is achieved with a millimeter‐wide surface functionalized with a physisorbed biolayer comprising trillions of recognition‐elements (antibodies or protein–probe complexes) which undergo an acidic or alkaline pH‐conditioning. Potentiometric and surface‐probing imaging experiments reveal the phenomenon underlying this extraordinary performance enhancement. The data suggest an unexplored amplification process within the biomaterial, where pH‐conditioning, driving the biolayer in a metastable state, induces a self‐propagating aggregation of partially misfolded proteins, following single‐affinity binding. This process triggers an electrostatic rearrangement, resulting in the displacement of a charge equivalent to 1.5e per 10\n              2\n              recognition elements. Such findings open new opportunities for reliable SPR‐based biosensing at the physical detection limits, with promising applications in point‐of‐care plasmonic systems.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2025-10-15},\n\tjournal = {Advanced Materials},\n\tauthor = {Macchia, Eleonora and Franco, Cinzia Di and Scandurra, Cecilia and Sarcina, Lucia and Piscitelli, Matteo and Catacchio, Michele and Caputo, Mariapia and Bollella, Paolo and Scamarcio, Gaetano and Torsi, Luisa},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2418610},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Metabolic and genetic imbalance of the homocysteine-methionine cycle in trisomy 21.\n \n \n \n \n\n\n \n Vione, B.; Lajin, B.; Antonaros, F.; Cicilloni, M.; Catapano, F.; Locatelli, C.; Pelleri, M. C.; Piovesan, A.; Vitale, L.; Pirazzoli, G. L.; Strippoli, P.; Corvaglia, L. T.; Ramacieri, G.; and Caracausi, M.\n\n\n \n\n\n\n Physiological Genomics, 57(9): 566–574. September 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Metabolic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{vione_metabolic_2025,\n\ttitle = {Metabolic and genetic imbalance of the homocysteine-methionine cycle in trisomy 21},\n\tvolume = {57},\n\tissn = {1094-8341, 1531-2267},\n\turl = {https://journals.physiology.org/doi/10.1152/physiolgenomics.00168.2024},\n\tdoi = {10.1152/physiolgenomics.00168.2024},\n\tabstract = {S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are critical metabolites for the fundamental cellular functions, such as proliferation and epigenetic regulation. For the first time, their levels were quantified in the urine of subjects with trisomy 21 (T21) and compared with euploid controls (N). These dosages were compared with their plasma levels, and the expression of genes involved in SAM and SAH production/utilization was further investigated in the differential blood transcriptome map of T21 versus N samples.\n          , \n            The homocysteine-methionine cycle is involved in the critical human cellular functions, such as proliferation and epigenetic regulation. S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) metabolites are synthesized in this metabolic cycle, and their levels are finely regulated to ensure proper functioning of key enzymes controlling the cellular growth and differentiation. SAM and SAH levels were found altered in the plasma of subjects with trisomy 21 (T21), but how this metabolic dysregulation influences the clinical manifestation of T21 phenotype has not been previously described. SAM and SAH quantifications were performed in urine samples of 58 subjects with T21 and 48 controls (N) through liquid chromatography with tandem mass spectrometry. SAH resulted slightly more excreted in urine of subjects with T21 (T21/N mean ratio = 1.16, P value = 0.021), although no difference was found in SAM levels. Metabolite urine levels were compared with those previously observed in plasma, in which higher amounts of SAM and SAH were found. In addition, we examined if an association between the levels of SAM and SAH in T21 and the expression levels of genes involved in their production/utilization exists using the transcriptome map of blood samples of T21 and N subjects. The analysis showed overexpression of 44 methyltransferase genes responsible for the conversion of SAM to SAH, of two genes involved in SAH utilization, adenosylhomocysteinase-like 1, adenosylhomocysteinase-like 2, and of one gene involved in SAM utilization, adenosylmethionine decarboxylase 1. These data support the hypothesis that T21 genetic imbalance is responsible for SAM and SAH excess, which may be involved in the T21 phenotypic features.\n            NEW \\& NOTEWORTHY S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are critical metabolites for the fundamental cellular functions, such as proliferation and epigenetic regulation. For the first time, their levels were quantified in the urine of subjects with trisomy 21 (T21) and compared with euploid controls (N). These dosages were compared with their plasma levels, and the expression of genes involved in SAM and SAH production/utilization was further investigated in the differential blood transcriptome map of T21 versus N samples.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2025-10-15},\n\tjournal = {Physiological Genomics},\n\tauthor = {Vione, Beatrice and Lajin, Bassam and Antonaros, Francesca and Cicilloni, Michela and Catapano, Francesca and Locatelli, Chiara and Pelleri, Maria Chiara and Piovesan, Allison and Vitale, Lorenza and Pirazzoli, Gian Luca and Strippoli, Pierluigi and Corvaglia, Luigi Tommaso and Ramacieri, Giuseppe and Caracausi, Maria},\n\tmonth = sep,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {566--574},\n}\n\n\n\n

\n\n\n

\n S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are critical metabolites for the fundamental cellular functions, such as proliferation and epigenetic regulation. For the first time, their levels were quantified in the urine of subjects with trisomy 21 (T21) and compared with euploid controls (N). These dosages were compared with their plasma levels, and the expression of genes involved in SAM and SAH production/utilization was further investigated in the differential blood transcriptome map of T21 versus N samples. , The homocysteine-methionine cycle is involved in the critical human cellular functions, such as proliferation and epigenetic regulation. S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) metabolites are synthesized in this metabolic cycle, and their levels are finely regulated to ensure proper functioning of key enzymes controlling the cellular growth and differentiation. SAM and SAH levels were found altered in the plasma of subjects with trisomy 21 (T21), but how this metabolic dysregulation influences the clinical manifestation of T21 phenotype has not been previously described. SAM and SAH quantifications were performed in urine samples of 58 subjects with T21 and 48 controls (N) through liquid chromatography with tandem mass spectrometry. SAH resulted slightly more excreted in urine of subjects with T21 (T21/N mean ratio = 1.16, P value = 0.021), although no difference was found in SAM levels. Metabolite urine levels were compared with those previously observed in plasma, in which higher amounts of SAM and SAH were found. In addition, we examined if an association between the levels of SAM and SAH in T21 and the expression levels of genes involved in their production/utilization exists using the transcriptome map of blood samples of T21 and N subjects. The analysis showed overexpression of 44 methyltransferase genes responsible for the conversion of SAM to SAH, of two genes involved in SAH utilization, adenosylhomocysteinase-like 1, adenosylhomocysteinase-like 2, and of one gene involved in SAM utilization, adenosylmethionine decarboxylase 1. These data support the hypothesis that T21 genetic imbalance is responsible for SAM and SAH excess, which may be involved in the T21 phenotypic features. NEW & NOTEWORTHY S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are critical metabolites for the fundamental cellular functions, such as proliferation and epigenetic regulation. For the first time, their levels were quantified in the urine of subjects with trisomy 21 (T21) and compared with euploid controls (N). These dosages were compared with their plasma levels, and the expression of genes involved in SAM and SAH production/utilization was further investigated in the differential blood transcriptome map of T21 versus N samples.\n

\n\n\n

@article{fazio_psychological_2025,\n\ttitle = {Psychological flexibility mediates the long-term impact of adverse interpersonal experiences in childhood and adolescence},\n\tvolume = {13},\n\tissn = {2050-7283},\n\turl = {https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-025-03297-5},\n\tdoi = {10.1186/s40359-025-03297-5},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-10-15},\n\tjournal = {BMC Psychology},\n\tauthor = {Fazio, Leonardo and Semeraro, Cristina and Pennacchio, Teresa Claudia and Asselti, Martina Grazia and Russo, Marianna and Cassibba, Rosalinda and Bertolino, Alessandro and Rampino, Antonio and Grattagliano, Ignazio and Pergola, Giulio and Antonucci, Linda Antonella},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {927},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Leveraging Design of Experiments to Unravel the Amplification Mechanism of Single‐Molecule Wide‐Field Biosensors.\n \n \n \n \n\n\n \n Catacchio, M.; Caputo, M.; Sarcina, L.; Di Franco, C.; Piscitelli, M.; Castrignanò, E.; Bollella, P.; Scamarcio, G.; Macchia, E.; and Torsi, L.\n\n\n \n\n\n\n Advanced Materials Interfaces, 12(14): 2500090. July 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Leveraging$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{catacchio_leveraging_2025,\n\ttitle = {Leveraging {Design} of {Experiments} to {Unravel} the {Amplification} {Mechanism} of {Single}‐{Molecule} {Wide}‐{Field} {Biosensors}},\n\tvolume = {12},\n\tissn = {2196-7350, 2196-7350},\n\turl = {https://advanced.onlinelibrary.wiley.com/doi/10.1002/admi.202500090},\n\tdoi = {10.1002/admi.202500090},\n\tabstract = {Abstract\n            \n              Detecting single molecules on large interfaces, spanning several square micrometers, is often considered unfeasible due to the minimal perturbation individual molecules exert on the sensing surface. However, biological systems, such as cellular membranes, demonstrate remarkable sensitivity, achieving single‐molecule detection on interfaces as large as 10\n              3\n              µm\n              2\n              , despite the stark mismatch between molecular footprints and surface areas. While these amplification mechanisms are well‐documented, their molecular and biophysical foundations remain poorly understood. To contribute to probing these phenomena, a Design of Experiments (DoE) approach explores how pH and ionic strength in conditioning solutions influence Surface Plasmon Resonance (SPR) detection in the single‐molecule regime. Conditioning a physisorbed layer of capturing antibodies at low pH emerges as the key strategy, enabling the reliable detection of only 6 ± 2 IgG molecules with a significant SPR signal. The analysis further reveals that pH conditioning induces a refractive index shift within the antibody layer, which is quantitatively correlated with changes in zeta potential (ζ‐potential). These findings provide critical insights into the mechanisms driving ultrasensitive SPR detection and establish a data‐driven framework for advancing biosensing technologies.},\n\tlanguage = {en},\n\tnumber = {14},\n\turldate = {2025-10-15},\n\tjournal = {Advanced Materials Interfaces},\n\tauthor = {Catacchio, Michele and Caputo, Mariapia and Sarcina, Lucia and Di Franco, Cinzia and Piscitelli, Matteo and Castrignanò, Erika and Bollella, Paolo and Scamarcio, Gaetano and Macchia, Eleonora and Torsi, Luisa},\n\tmonth = jul,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2500090},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Targeting ERRs to counteract age-related muscle atrophy associated with physical inactivity: a pilot study.\n \n \n \n \n\n\n \n Bonanni, R.; Falvino, A.; Matticari, A.; Rinaldi, A. M.; D’Arcangelo, G.; Cifelli, P.; Iundusi, R.; Gasbarra, E.; Tancredi, V.; Cariati, I.; and Tarantino, U.\n\n\n \n\n\n\n Frontiers in Physiology, 16: 1616693. July 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Targeting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bonanni_targeting_2025,\n\ttitle = {Targeting {ERRs} to counteract age-related muscle atrophy associated with physical inactivity: a pilot study},\n\tvolume = {16},\n\tissn = {1664-042X},\n\tshorttitle = {Targeting {ERRs} to counteract age-related muscle atrophy associated with physical inactivity},\n\turl = {https://www.frontiersin.org/articles/10.3389/fphys.2025.1616693/full},\n\tdoi = {10.3389/fphys.2025.1616693},\n\tabstract = {Introduction\n              Estrogen-related receptors has been suggested as a potential therapeutic target to counteract muscle decline associated with aging or inactivity, being known to regulate mitochondrial function and cellular respiration by up-regulating key factors in muscle responses to exercise. This study aimed to evaluate the targeting of ERRs in myoblasts isolated from the skeletal muscle of inactive women by assessing the metabolic and expression changes associated with its activation.\n            \n            \n              Methods\n              Twenty women undergoing hip arthroplasty for coxarthrosis were enrolled and divided into an active group (n = 10) and an inactive group (n = 10) based on self-reported physical activity. During surgery, muscle biopsies were taken for histological and western blotting analysis, measuring the expression levels of NADPH oxidase 4 (NOX4), sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), estrogen related receptor alpha (ERRα), and fibronectin type III domain-containing protein 5 (FNDC5). Primary cultures of myoblasts were set up from the muscle tissue of inactive women and treated with the ERRs agonist, SLU-PP-332, for subsequent qualitative and quantitative investigations. In addition, myoblasts were differentiated into myotubes for 15 days, and the success of differentiation was evaluated by immunofluorescence analysis.\n            \n            \n              Results\n              Clinical and instrumental evaluation showed less functional limitation, higher handgrip strength values, and significantly reduced visual analogue scale scores in active subjects, in association with a significant increase in muscle fiber diameter. In addition, significantly higher expression of NOX4, concomitant with reduced levels of SIRT1, PGC-1α, ERRα, and FNDC5, was detected in the muscle tissue of inactive women. Interestingly, SLU-PP-332 treatment promoted down-regulation of NOX4 and upregulation of SIRT1, PGC-1α, ERRα, FNDC5, Akt, and B-cell lymphoma 2 (Bcl-2) in myoblasts, reducing cytotoxicity, oxidative stress, and senescence, as well as increasing levels of reduced glutathione. Furthermore, SLU-PP-332 treatment promoted abundant myotube formation, positively influencing cell differentiation.\n            \n            \n              Discussion\n              Targeting ERRs could represent a promising therapeutic strategy to counteract muscle atrophy in elderly and sedentary subjects. However, further studies are needed to clarify the molecular mechanisms involved and explore the impact of ERRs activation on muscle metabolism.},\n\turldate = {2025-10-15},\n\tjournal = {Frontiers in Physiology},\n\tauthor = {Bonanni, Roberto and Falvino, Angela and Matticari, Antonio and Rinaldi, Anna Maria and D’Arcangelo, Giovanna and Cifelli, Pierangelo and Iundusi, Riccardo and Gasbarra, Elena and Tancredi, Virginia and Cariati, Ida and Tarantino, Umberto},\n\tmonth = jul,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {1616693},\n}\n\n\n\n

\n\n\n

\n Introduction Estrogen-related receptors has been suggested as a potential therapeutic target to counteract muscle decline associated with aging or inactivity, being known to regulate mitochondrial function and cellular respiration by up-regulating key factors in muscle responses to exercise. This study aimed to evaluate the targeting of ERRs in myoblasts isolated from the skeletal muscle of inactive women by assessing the metabolic and expression changes associated with its activation. Methods Twenty women undergoing hip arthroplasty for coxarthrosis were enrolled and divided into an active group (n = 10) and an inactive group (n = 10) based on self-reported physical activity. During surgery, muscle biopsies were taken for histological and western blotting analysis, measuring the expression levels of NADPH oxidase 4 (NOX4), sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), estrogen related receptor alpha (ERRα), and fibronectin type III domain-containing protein 5 (FNDC5). Primary cultures of myoblasts were set up from the muscle tissue of inactive women and treated with the ERRs agonist, SLU-PP-332, for subsequent qualitative and quantitative investigations. In addition, myoblasts were differentiated into myotubes for 15 days, and the success of differentiation was evaluated by immunofluorescence analysis. Results Clinical and instrumental evaluation showed less functional limitation, higher handgrip strength values, and significantly reduced visual analogue scale scores in active subjects, in association with a significant increase in muscle fiber diameter. In addition, significantly higher expression of NOX4, concomitant with reduced levels of SIRT1, PGC-1α, ERRα, and FNDC5, was detected in the muscle tissue of inactive women. Interestingly, SLU-PP-332 treatment promoted down-regulation of NOX4 and upregulation of SIRT1, PGC-1α, ERRα, FNDC5, Akt, and B-cell lymphoma 2 (Bcl-2) in myoblasts, reducing cytotoxicity, oxidative stress, and senescence, as well as increasing levels of reduced glutathione. Furthermore, SLU-PP-332 treatment promoted abundant myotube formation, positively influencing cell differentiation. Discussion Targeting ERRs could represent a promising therapeutic strategy to counteract muscle atrophy in elderly and sedentary subjects. However, further studies are needed to clarify the molecular mechanisms involved and explore the impact of ERRs activation on muscle metabolism.\n

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\n \n\n \n \n \n \n \n \n Analyzing the Caloric Variability of Bites in a Semi-Naturalistic Dietary Setting.\n \n \n \n \n\n\n \n Bhuyan, M. J.; Vedovelli, L.; Lanera, C.; Gasparini, D.; Berchialla, P.; Baldi, I.; and Gregori, D.\n\n\n \n\n\n\n Nutrients, 17(13): 2192. June 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Analyzing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{bhuyan_analyzing_2025,\n\ttitle = {Analyzing the {Caloric} {Variability} of {Bites} in a {Semi}-{Naturalistic} {Dietary} {Setting}},\n\tvolume = {17},\n\tissn = {2072-6643},\n\turl = {https://www.mdpi.com/2072-6643/17/13/2192},\n\tdoi = {10.3390/nu17132192},\n\tabstract = {Background: Obesity is a major public health issue in developed countries, primarily managed through dietary interventions and physical activity. Food portion sizes influence the estimation of energy intake, particularly through bites, of which characteristics remain insufficiently defined. This study investigates the variability in bite energy content. Methods: This observational study was conducted over 14 months. Thirteen types of packaged food were provided to 30 Italian healthy volunteers (mean age 26.8 ± 8.5 years) in a semi-naturalistic dietary feeding setting. Participants’ anthropometric measurements were recorded. A total of 1850 bites were weighed and 420 bites were assessed for volume and energy content. Results: Bite volume and mass explained bite energy content at different rates. The most influential anthropometric feature was waist circumference. Gender modified the association between waist circumference and bite characteristics; males showed increased bite volume, mass, and energy content as waist circumference increased, whereas females showed little or no association. Age was inversely associated with bite volume and mass, with younger participants having larger bites. Gender significantly influenced average bite size, with females showing lower values than males. The use of a fork was associated with higher bite volume, mass, and energy compared to a spoon. Food eaten with bare hands had lower mass but higher energy content compared to food eaten with a spoon. The variability in bite energy was considerably greater per bite than per gram, reflecting the combined influence of food texture, bite size, and cutlery used. Conclusions: Bite energy variability, influenced by intrinsic factors (gender, age, waist circumference) and extrinsic factors (cutlery, food texture), significantly impacts portion size effect. Future bite counters should consider these elements for accurate dietary assessment.},\n\tlanguage = {en},\n\tnumber = {13},\n\turldate = {2025-10-15},\n\tjournal = {Nutrients},\n\tauthor = {Bhuyan, Mohammad Junayed and Vedovelli, Luca and Lanera, Corrado and Gasparini, Daniele and Berchialla, Paola and Baldi, Ileana and Gregori, Dario},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2192},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Enhancing legal question answering with data generation and knowledge distillation from large language models.\n \n \n \n \n\n\n \n Italiani, P.; Moro, G.; and Ragazzi, L.\n\n\n \n\n\n\n Artificial Intelligence and Law. July 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Enhancing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{italiani_enhancing_2025,\n\ttitle = {Enhancing legal question answering with data generation and knowledge distillation from large language models},\n\tissn = {0924-8463, 1572-8382},\n\turl = {https://link.springer.com/10.1007/s10506-025-09463-9},\n\tdoi = {10.1007/s10506-025-09463-9},\n\tabstract = {Abstract\n            \n              Legal question answering (LQA) relies on supervised methods to automatically handle law-related queries. These solutions require a substantial amount of carefully annotated data for training, which makes the process very costly. Although large language models (LLMs) show promise in zero-shot QA, their computational demands limit their practical use, making specialized small language models (SLMs) more favorable. Furthermore, the growing interest in synthetic data generation has recently surged, spurred by the impressive generation capabilities of LLMs. This paper presents\n              Ace-Attorney\n              , an LLM distillation approach devised to develop LQA data and supervised models without human annotation. Given a textual prompt, a frozen LLM generates artificial examples that are used as knowledge to train a student SLM with an order of magnitude fewer parameters. Taking into account a realistic retrieval-based scenario to fetch the correct document for answer generation, we propose Selective Generative Paradigm, a novel approach designed to improve retrieval efficacy. Extensive experiments demonstrate the effectiveness and efficiency of distilled models on\n              Syn-LeQA\n              , our human-free synthetic dataset, and a public expert-annotated corpus. Notably, by using only a few dozen training samples, our best SLM achieves LLM-comparable performance with\n              \n                \n                  \\$\\${\\textbackslash}approx \\$\\$\n                  \n                    ≈\n                  \n                \n              \n              1200\\% less CO\n              \n                \n                  \\$\\$\\_2\\$\\$\n                  \n                    \n                      \n                      2\n                      \n                    \n                  \n                \n              \n              emissions. The data and the code to fully reproduce our results are available at\n              https://github.com/disi-unibo-nlp/ace-attorney\n              .},\n\tlanguage = {en},\n\turldate = {2025-10-03},\n\tjournal = {Artificial Intelligence and Law},\n\tauthor = {Italiani, Paolo and Moro, Gianluca and Ragazzi, Luca},\n\tmonth = jul,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Digital Disruption in Healthcare: What It Means for the NHS.\n \n \n \n \n\n\n \n Atella, V.; and Chiari, L.\n\n\n \n\n\n\n Economia Italiana, 47(2): 63–135. September 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Digital$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{atella_digital_2025,\n\ttitle = {Digital {Disruption} in {Healthcare}: {What} {It} {Means} for the {NHS}},\n\tvolume = {47},\n\tissn = {0392-775X},\n\tshorttitle = {Digital {Disruption} in {Healthcare}},\n\turl = {https://doi.org/10.57621/EI2025-02-S-03},\n\tdoi = {10.57621/EI2025-02-S-03},\n\tabstract = {This paper examines the transformative impact of digital technologies on healthcare systems, with a specific focus on the NHS. While earlier waves of medical innovation developed gradually over decades, the current digital disruption—driven by artificial intelligence, big data, genomics, and connected health devices—is unfolding at a much faster pace, reshaping how care is delivered, accessed, and organized. The paper traces the historical trajectory of health technologies, identifies key enabling innovations, and analyzes their maturity and readiness for adoption. It explores how digital tools are improving clinical outcomes, altering workforce structures, and influencing health expenditures. At the same time, the paper highlights the regulatory, ethical, and governance challenges posed by these technologies, including concerns around data use, algorithmic transparency, and equity. It argues for the urgent need to modernize regulatory frameworks and health technology assessment methods to keep pace with innovation. In doing so, it calls for anticipatory, adaptive, and inclusive approaches that support responsible innovation while safeguarding public trust and sustainability in the NHS and beyond.},\n\tlanguage = {eng},\n\tnumber = {2},\n\turldate = {2025-09-24},\n\tjournal = {Economia Italiana},\n\tauthor = {Atella, Vincenzo and Chiari, Lorenzo},\n\tmonth = sep,\n\tyear = {2025},\n\tkeywords = {SP1, WP5},\n\tpages = {63--135},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n In silico prediction of hip fractures: improved fall modeling and expanded validation across cohorts with diverse risk profiles.\n \n \n \n \n\n\n \n Savelli, G.; Oliviero, S.; Viceconti, M.; and La Mattina, A. A.\n\n\n \n\n\n\n Journal of the Mechanical Behavior of Biomedical Materials, 172: 107182. December 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"In$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{savelli_silico_2025,\n\ttitle = {In silico prediction of hip fractures: improved fall modeling and expanded validation across cohorts with diverse risk profiles},\n\tvolume = {172},\n\tissn = {17516161},\n\tshorttitle = {In silico prediction of hip fractures},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S175161612500298X},\n\tdoi = {10.1016/j.jmbbm.2025.107182},\n\tlanguage = {en},\n\turldate = {2025-09-11},\n\tjournal = {Journal of the Mechanical Behavior of Biomedical Materials},\n\tauthor = {Savelli, Giacomo and Oliviero, Sara and Viceconti, Marco and La Mattina, Antonino Amedeo},\n\tmonth = dec,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {107182},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Benchmarking of open-source algorithms for heart rate estimation from motion-corrupted photoplethysmography.\n \n \n \n \n\n\n \n Sicbaldi, M.; Palmerini, L.; Moscato, S.; Di Florio, P.; Silvani, A.; and Chiari, L.\n\n\n \n\n\n\n Computers in Biology and Medicine, 196: 110808. September 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Benchmarking$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{sicbaldi_benchmarking_2025,\n\ttitle = {Benchmarking of open-source algorithms for heart rate estimation from motion-corrupted photoplethysmography},\n\tvolume = {196},\n\tissn = {00104825},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S001048252501159X},\n\tdoi = {10.1016/j.compbiomed.2025.110808},\n\tlanguage = {en},\n\turldate = {2025-09-05},\n\tjournal = {Computers in Biology and Medicine},\n\tauthor = {Sicbaldi, Marcello and Palmerini, Luca and Moscato, Serena and Di Florio, Paola and Silvani, Alessandro and Chiari, Lorenzo},\n\tmonth = sep,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {110808},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Digital twin-based adaptive optimization of basal insulin in pediatric patients: a feasibility study.\n \n \n \n \n\n\n \n Pellizzari, E.; Cappon, G.; Sparacino, G.; and Facchinetti, A.\n\n\n \n\n\n\n In Diabetes Technology & Therapeutics, volume 27, pages e135–e203, March 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Digital$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{pellizzari_digital_2025,\n\ttitle = {Digital twin-based adaptive optimization of basal insulin in pediatric patients: a feasibility study},\n\tvolume = {27},\n\tcopyright = {https://www.liebertpub.com/nv/resources-tools/text-and-data-mining-policy/121/},\n\turl = {https://www.liebertpub.com/doi/10.1089/dia.2024.78502.abstracts.part4a},\n\tdoi = {10.1089/dia.2024.78502.abstracts.part4a},\n\tlanguage = {en},\n\turldate = {2025-08-06},\n\tbooktitle = {Diabetes {Technology} \\& {Therapeutics}},\n\tauthor = {Pellizzari, Elisa and Cappon, Giacomo and Sparacino, Giovanni and Facchinetti, Andrea},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {e135--e203},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Leveraging LLM to Improve Efficacy of AGP Reports: A Feasibility Study.\n \n \n \n \n\n\n \n Cossu, L.; Cappon, G.; Deodati, A.; Schiaffini, R.; Cianfarani, S.; and Facchinetti, A.\n\n\n \n\n\n\n In 2024 Diabetes Technology Meeting Abstracts, volume 19, pages 497–575, March 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Leveraging$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{cossu_leveraging_2025,\n\ttitle = {Leveraging {LLM} to {Improve} {Efficacy} of {AGP} {Reports}: {A} {Feasibility} {Study}},\n\tvolume = {19},\n\turl = {https://journals.sagepub.com/doi/10.1177/19322968251314275},\n\tdoi = {10.1177/19322968251314275},\n\tlanguage = {en},\n\turldate = {2025-05-27},\n\tbooktitle = {2024 {Diabetes} {Technology} {Meeting} {Abstracts}},\n\tauthor = {Cossu, Luca and Cappon, Giacomo and Deodati, Annalisa and Schiaffini, Riccardo and Cianfarani, Stefano and Facchinetti, Andrea},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {497--575},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Efficacy and Safety of Mepolizumab 300 mg in Eosinophilic Granulomatosis With Polyangiitis: A Meta‐Analysis of Eight Retrospective Studies.\n \n \n \n \n\n\n \n Spataro, F.; Cacciapaglia, F.; Carlucci, P.; Solimando, A. G.; Desantis, V.; Di Girolamo, A.; Montagnani, M.; Di Bona, D.; Vacca, A.; and Ria, R.\n\n\n \n\n\n\n Allergy: European Journal of Allergy and Clinical Immunology,all.16625. June 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficacy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{spataro_efficacy_2025,\n\ttitle = {Efficacy and {Safety} of {Mepolizumab} 300 mg in {Eosinophilic} {Granulomatosis} {With} {Polyangiitis}: {A} {Meta}‐{Analysis} of {Eight} {Retrospective} {Studies}},\n\tissn = {0105-4538, 1398-9995},\n\tshorttitle = {Efficacy and {Safety} of {Mepolizumab} 300 mg in {Eosinophilic} {Granulomatosis} {With} {Polyangiitis}},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/all.16625},\n\tdoi = {10.1111/all.16625},\n\tlanguage = {en},\n\turldate = {2025-07-30},\n\tjournal = {Allergy: European Journal of Allergy and Clinical Immunology},\n\tauthor = {Spataro, Federico and Cacciapaglia, Fabio and Carlucci, Palma and Solimando, Antonio Giovanni and Desantis, Vanessa and Di Girolamo, Attilio and Montagnani, Monica and Di Bona, Danilo and Vacca, Angelo and Ria, Roberto},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {all.16625},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n An interoperable web-based platform to support health surveillance against latent tuberculosis infection in health care workers and students: The evolution of CROSSWORD study protocol.\n \n \n \n \n\n\n \n Rizzi, A.; Nucera, E.; Mazzucco, W.; Palumbo, P.; Staiti, D.; Moscato, U.; De Simone, F. M.; Sali, M.; Boldrini, L.; Capocchiano, N. D.; Patarnello, S.; Rumi, G.; Chini, R.; Carusi, V.; Centrone, M.; Di Rienzo, A.; Longhino, D.; Laface, C.; Mellone, S.; Maida, C. M.; Cannizzaro, E.; Cirrincione, L.; Verso, M. G.; Saracino, A.; Di Gennaro, F.; Vimercati, L.; De Maria, L.; Sponselli, S.; Scoppettuolo, G.; Pastorino, R.; Gasbarrini, A.; and Inchingolo, R.\n\n\n \n\n\n\n PLOS ONE, 20(3): e0319568. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{rizzi_interoperable_2025,\n\ttitle = {An interoperable web-based platform to support health surveillance against latent tuberculosis infection in health care workers and students: {The} evolution of {CROSSWORD} study protocol},\n\tvolume = {20},\n\tissn = {1932-6203},\n\tshorttitle = {An interoperable web-based platform to support health surveillance against latent tuberculosis infection in health care workers and students},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0319568},\n\tdoi = {10.1371/journal.pone.0319568},\n\tabstract = {Background\n              Tuberculosis (TB) prevention is a major goal in teaching hospital setting. Because of the possible progression or reactivation of latent disease, the screening of both health-care workers (HCWs) and students is an important issue in the TB control program.\n            \n            \n              Objective\n              to deploy a web-based platform interoperating health surveillance systems from different hospitals to define models based on the highlighted risk factors to predict the occurrence of Latent Tuberculosis Infection (LTBI) and to define prevention strategies and interventions.\n            \n            \n              Methods\n              This is a cross-sectional ambispective observational study without drug and device. The primary endpoint is the prevalence of LTBI. The secondary endpoint is the identification of possible risk factors of LTBI in a large cohort of HCWs and students.\n            \n            \n              Conclusions\n              This study aims to enrich the primary prevention measures against TB, having a high socio-economic-health impact in high-risk populations (HCWs and students) through an interoperable digital approach based on data obtained in three large Italian teaching hospitals.\n              \n                ClinicalTrials.gov:\n                NCT05756582},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2025-07-30},\n\tjournal = {PLOS ONE},\n\tauthor = {Rizzi, Angela and Nucera, Eleonora and Mazzucco, Walter and Palumbo, Pierpaolo and Staiti, Domenico and Moscato, Umberto and De Simone, Francesco Maria and Sali, Michela and Boldrini, Luca and Capocchiano, Nikola Dino and Patarnello, Stefano and Rumi, Gabriele and Chini, Raffaella and Carusi, Valentina and Centrone, Michele and Di Rienzo, Alessia and Longhino, David and Laface, Chiara and Mellone, Sabato and Maida, Carmelo Massimo and Cannizzaro, Emanuele and Cirrincione, Luigi and Verso, Maria Gabriella and Saracino, Annalisa and Di Gennaro, Francesco and Vimercati, Luigi and De Maria, Luigi and Sponselli, Stefania and Scoppettuolo, Giancarlo and Pastorino, Roberta and Gasbarrini, Antonio and Inchingolo, Riccardo},\n\teditor = {Serra, Nicola},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {e0319568},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n CONNECTED: A Knowledge Graph-Driven Platform for Clinical Data Harmonization and Personalized Digital Twin-Based Healthcare.\n \n \n \n \n\n\n \n Marfoglia, A.; D’Errico, C.; Nardini, F.; Mellone, S.; and Carbonaro, A.\n\n\n \n\n\n\n In 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), pages 116–121, Washington DC, DC, USA, March 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"CONNECTED:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{marfoglia_connected_2025,\n\taddress = {Washington DC, DC, USA},\n\ttitle = {{CONNECTED}: {A} {Knowledge} {Graph}-{Driven} {Platform} for {Clinical} {Data} {Harmonization} and {Personalized} {Digital} {Twin}-{Based} {Healthcare}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3315-3553-7},\n\tshorttitle = {{CONNECTED}},\n\turl = {https://ieeexplore.ieee.org/document/11038700/},\n\tdoi = {10.1109/PerComWorkshops65533.2025.00051},\n\turldate = {2025-07-30},\n\tbooktitle = {2025 {IEEE} {International} {Conference} on {Pervasive} {Computing} and {Communications} {Workshops} and other {Affiliated} {Events} ({PerCom} {Workshops})},\n\tpublisher = {IEEE},\n\tauthor = {Marfoglia, Alberto and D’Errico, Christian and Nardini, Filippo and Mellone, Sabato and Carbonaro, Antonella},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP1},\n\tpages = {116--121},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Cluster-Based Approach for Emotion Recognition in Software Development.\n \n \n \n \n\n\n \n Grassi, D.; Lanubile, F.; Motca-Schnabel, A.; and Novielli, N.\n\n\n \n\n\n\n In 2025 IEEE/ACM 18th International Conference on Cooperative and Human Aspects of Software Engineering (CHASE), pages 239–247, Ottawa, ON, Canada, April 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{grassi_cluster-based_2025,\n\taddress = {Ottawa, ON, Canada},\n\ttitle = {A {Cluster}-{Based} {Approach} for {Emotion} {Recognition} in {Software} {Development}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3315-3871-2},\n\turl = {https://ieeexplore.ieee.org/document/11024464/},\n\tdoi = {10.1109/CHASE66643.2025.00034},\n\turldate = {2025-07-30},\n\tbooktitle = {2025 {IEEE}/{ACM} 18th {International} {Conference} on {Cooperative} and {Human} {Aspects} of {Software} {Engineering} ({CHASE})},\n\tpublisher = {IEEE},\n\tauthor = {Grassi, Daniela and Lanubile, Filippo and Motca-Schnabel, Alberta and Novielli, Nicole},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP1},\n\tpages = {239--247},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Towards Ensuring Responsible AI for Medical Device Certification.\n \n \n \n \n\n\n \n Mallardi, G.; Quaranta, L.; Calefato, F.; and Lanubile, F.\n\n\n \n\n\n\n In 2025 IEEE/ACM International Workshop on Responsible AI Engineering (RAIE), pages 29–32, Ottawa, ON, Canada, April 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{mallardi_towards_2025,\n\taddress = {Ottawa, ON, Canada},\n\ttitle = {Towards {Ensuring} {Responsible} {AI} for {Medical} {Device} {Certification}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3315-1466-2},\n\turl = {https://ieeexplore.ieee.org/document/11029424/},\n\tdoi = {10.1109/RAIE66699.2025.00009},\n\turldate = {2025-07-30},\n\tbooktitle = {2025 {IEEE}/{ACM} {International} {Workshop} on {Responsible} {AI} {Engineering} ({RAIE})},\n\tpublisher = {IEEE},\n\tauthor = {Mallardi, Giulio and Quaranta, Luigi and Calefato, Fabio and Lanubile, Filippo},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP1},\n\tpages = {29--32},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n How to manage hypersensitivity reactions to enzyme replacement therapy in lysosomal storage diseases?.\n \n \n \n \n\n\n \n Spataro, F.; Solimando, A. G.; Desantis, V.; Vacca, A.; Di Girolamo, A.; and Ria, R.\n\n\n \n\n\n\n Orphanet Journal of Rare Diseases, 20(1): 287. June 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"How$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{spataro_how_2025,\n\ttitle = {How to manage hypersensitivity reactions to enzyme replacement therapy in lysosomal storage diseases?},\n\tvolume = {20},\n\tissn = {1750-1172},\n\turl = {https://ojrd.biomedcentral.com/articles/10.1186/s13023-025-03844-8},\n\tdoi = {10.1186/s13023-025-03844-8},\n\tabstract = {Abstract\n            Lysosomal Storage Diseases (LSDs) encompass a range of genetic disorders characterized by enzyme deficiencies that lead to substrate accumulation and progressive tissue damage. Enzyme Replacement Therapy (ERT) is the primary treatment for LSDs, yet it is often associated with hypersensitivity reactions (HSRs), ranging from mild rashes to severe anaphylaxis. These reactions, frequently driven by anti-drug antibodies, pose significant challenges in treatment adherence and patient outcomes. This paper outlines a stepwise approach to managing HSRs during ERT, focusing on three escalating strategies. The first-line approach involves premedication using antihistamines, corticosteroids, antileukotrienes, and bronchodilators to prevent or reduce the severity of HSRs.\n            For patients who continue to experience HSRs despite premedication, desensitization protocols are recommended, involving the gradual reintroduction of ERT in controlled, increasing doses.\n            In cases of refractory HSRs, omalizumab, a monoclonal antibody targeting IgE, has been successfully used as a third-line intervention.\n            This comprehensive, stepwise strategy aims to provide clinicians a guide to manage these challenges, offering practical steps for optimizing treatment while ensuring patient safety. Future research is needed to further validate these management techniques and explore new therapeutic options for optimizing care in this rare but critical patient population.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-07-30},\n\tjournal = {Orphanet Journal of Rare Diseases},\n\tauthor = {Spataro, Federico and Solimando, Antonio Giovanni and Desantis, Vanessa and Vacca, Angelo and Di Girolamo, Attilio and Ria, Roberto},\n\tmonth = jun,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {287},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Successful rapid desensitization to zoledronic acid in a multiple myeloma patient.\n \n \n \n \n\n\n \n Spataro, F.; Solimando, A. G.; Desantis, V.; Vacca, A.; and Ria, R.\n\n\n \n\n\n\n Discover Oncology, 16(1): 401. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Successful$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{spataro_successful_2025,\n\ttitle = {Successful rapid desensitization to zoledronic acid in a multiple myeloma patient},\n\tvolume = {16},\n\tissn = {2730-6011},\n\turl = {https://link.springer.com/10.1007/s12672-025-02207-w},\n\tdoi = {10.1007/s12672-025-02207-w},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-07-30},\n\tjournal = {Discover Oncology},\n\tauthor = {Spataro, Federico and Solimando, Antonio Giovanni and Desantis, Vanessa and Vacca, Angelo and Ria, Roberto},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {401},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n CT Perfusion Imaging in Patients with Acute Ischemic Stroke: The Role of Premorbid Statin Treatment.\n \n \n \n \n\n\n \n Picchi, E.; Di Giuliano, F.; Pucci, N.; Sallustio, F.; Minosse, S.; Mascolo, A. P.; Marrama, F.; Ferrazzoli, V.; Da Ros, V.; Diomedi, M.; Federici, M.; and Garaci, F.\n\n\n \n\n\n\n Tomography, 11(5): 54. May 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"CT$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{picchi_ct_2025,\n\ttitle = {{CT} {Perfusion} {Imaging} in {Patients} with {Acute} {Ischemic} {Stroke}: {The} {Role} of {Premorbid} {Statin} {Treatment}},\n\tvolume = {11},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2379-139X},\n\tshorttitle = {{CT} {Perfusion} {Imaging} in {Patients} with {Acute} {Ischemic} {Stroke}},\n\turl = {https://www.mdpi.com/2379-139X/11/5/54},\n\tdoi = {10.3390/tomography11050054},\n\tabstract = {Background. Statins appear to be useful in patients with acute ischemic stroke. Our aim was to evaluate the association between premorbid statin treatment and CT perfusion characteristics of acute ischemic stroke. Methods. A retrospective analysis of patients with acute stroke secondary to occlusion of large vessels in the anterior circulation was performed to assess collateral flow, ischemic core volume, and ischemic penumbra using CT angiography and CT perfusion maps. Fisher’s exact test was used to compare baseline characteristics of patients in the two groups. The Wilcoxon rank-sum test for independent groups was used to compare all variables obtained for the two different groups with and without statin use. Results. We identified 61 patients, including 29 treated with statins and 32 not treated with statins before stroke onset matched by age, gender, and vascular risk factors except for hypercholesterolemia. The statin group showed lower National Institutes of health Stroke Scale scores at onset (14 ± 6.1 vs. 16 ± 4.5; p = 0.04) and lower volumes of brain tissue characterized by impaired cerebral blood flow (CBF), cerebral blood volume (CBV), and Tmax9.5−25s; otherwise, no statistically significant difference was found in the volume of the Tmax16−25s between the two groups. Conclusions. Premorbid statin treatment is associated with a favorable imaging condition of acute ischemic stroke in terms of ischemic core and ischemic penumbra volume.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2025-07-30},\n\tjournal = {Tomography},\n\tauthor = {Picchi, Eliseo and Di Giuliano, Francesca and Pucci, Noemi and Sallustio, Fabrizio and Minosse, Silvia and Mascolo, Alfredo Paolo and Marrama, Federico and Ferrazzoli, Valentina and Da Ros, Valerio and Diomedi, Marina and Federici, Massimo and Garaci, Francesco},\n\tmonth = may,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {54},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Neurological findings in a cohort of adults with down syndrome.\n \n \n \n \n\n\n \n Grotteschi, N.; Rochat, M. J.; Pollarini, V.; Ghezzo, A.; Pellegrini, C.; Calandra-Buonaura, G.; Lodi, R.; Tonon, C.; Cortelli, P.; Bacalini, M. G.; Pirazzoli, G. L.; and Sambati, L.\n\n\n \n\n\n\n Neurological Sciences, 46(8): 3639–3649. August 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Neurological$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{grotteschi_neurological_2025,\n\ttitle = {Neurological findings in a cohort of adults with down syndrome},\n\tvolume = {46},\n\tissn = {1590-1874, 1590-3478},\n\turl = {https://link.springer.com/10.1007/s10072-025-08195-7},\n\tdoi = {10.1007/s10072-025-08195-7},\n\tabstract = {Abstract\n            \n              The aim of this study is to describe the results of a comprehensive neurological assessment conducted on a cohort of 70 adults with Down syndrome (DS), aged 21 to 74 years, recruited in Bologna, Italy. Neurocognitive disorder (NcD) was identified in 28.6\\% of participants and showed a significant association with psychiatric disorders (\n              p\n              =0.03). Psychiatric conditions were present in 40\\% of the cohort, while Down Syndrome Regression Disorder (DSRD) was diagnosed in 7.1\\%. Transient loss of consciousness affected 28.6\\% of individuals. Epilepsy, observed in 7.1\\%, was significantly associated with NcD (\n              p\n              =0.02). Neurological examination revealed that stereotypic movements correlated with DSRD (\n              p\n              {\\textless}0.01), tics with obsessive-compulsive disorders (\n              p\n              =0.01), and hypokinetic movement disorders with psychotic conditions (\n              p\n              =0.03). Additionally, nystagmus and cerebellar signs were significantly associated with elevated serum bilirubin levels (\n              p\n              {\\textless}0.01). These findings underscore the high prevalence and complexity of neurological comorbidities in adults with DS, emphasizing the need for specialized, multidisciplinary care.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2025-07-30},\n\tjournal = {Neurological Sciences},\n\tauthor = {Grotteschi, Nicola and Rochat, Magali Jane and Pollarini, Virginia and Ghezzo, Alessandro and Pellegrini, Camilla and Calandra-Buonaura, Giovanna and Lodi, Raffaele and Tonon, Caterina and Cortelli, Pietro and Bacalini, Maria Giulia and Pirazzoli, Gian Luca and Sambati, Luisa},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {3639--3649},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Altered Brain‐Behavior Association During Resting State is a Potential Psychosis Risk Marker.\n \n \n \n \n\n\n \n Fazio, L.; Stolfa, G.; Passiatore, R.; Tavella, A.; Blasi, G.; Buciuman, M. O.; Goldman, A. L.; Haas, S. S.; Kambeitz‐Ilankovic, L.; Koutsouleris, N.; Nicoli, M.; Popolizio, T.; Rampino, A.; Ruef, A.; Sambataro, F.; Selvaggi, P.; Ulrich, W.; Weinberger, D. R.; Apulian Network on Risk for Psychosis, PRONIA Consortium; Bertolino, A.; Antonucci, L. A.; and Pergola, G.\n\n\n \n\n\n\n Advanced Science, 12(26): 2405700. July 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Altered$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{fazio_altered_2025,\n\ttitle = {Altered {Brain}‐{Behavior} {Association} {During} {Resting} {State} is a {Potential} {Psychosis} {Risk} {Marker}},\n\tvolume = {12},\n\tissn = {2198-3844, 2198-3844},\n\turl = {https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.202405700},\n\tdoi = {10.1002/advs.202405700},\n\tabstract = {Abstract\n            Alterations in cognitive and neuroimaging measures in psychosis may reflect altered brain‐behavior interactions patterns accompanying the symptomatic manifestation of the disease. Using graph connectivity‐based approaches, we tested the brain‐behavior association between cognitive functioning and functional connectivity at different stages of psychosis. We collected resting‐state fMRI of 204 neurotypical controls (NC) in two independent cohorts, 43 patients with chronic psychosis (PSY), and 22 subjects with subthreshold psychotic symptoms (STPS). In NC, we calculated graph connectivity metrics and tested their associations with neuropsychological scores. Replicable associations were tested in PSY and STPS and externally validated in three cohorts of 331, 371, and 232 individuals, respectively. NC showed a positive correlation between the degree centrality of a right prefrontal‐cingulum‐striatal circuit and total errors on Wisconsin Card Sorting Test. Conversely, PSY and STPS showed negative correlations. External replications confirmed both associations while highlighting the heterogeneity of STPS. Group differences in either centrality or cognition alone were not equally replicable. In four independent cohorts totaling 1,203 participants, we identified a replicable alteration of the brain‐behavior association in different stages of psychosis. These results highlight the high replicability of multimodal markers and suggest the opportunity for longitudinal investigations that may test this marker for early risk identification.},\n\tlanguage = {en},\n\tnumber = {26},\n\turldate = {2025-07-30},\n\tjournal = {Advanced Science},\n\tauthor = {Fazio, Leonardo and Stolfa, Giuseppe and Passiatore, Roberta and Tavella, Angelantonio and Blasi, Giuseppe and Buciuman, Madalina O. and Goldman, Aaron L. and Haas, Shalaila S. and Kambeitz‐Ilankovic, Lana and Koutsouleris, Nikolaos and Nicoli, Monica and Popolizio, Teresa and Rampino, Antonio and Ruef, Anne and Sambataro, Fabio and Selvaggi, Pierluigi and Ulrich, William and Weinberger, Daniel R. and {Apulian Network on Risk for Psychosis, PRONIA Consortium} and Bertolino, Alessandro and Antonucci, Linda A. and Pergola, Giulio},\n\tmonth = jul,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2405700},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Altered Expression of Cell Cycle Regulators and Factors Released by Aged Cells in Skeletal Muscle of Patients with Bone Fragility: A Pilot Study on the Potential Role of SIRT1 in Muscle Atrophy.\n \n \n \n \n\n\n \n Falvino, A.; Bonanni, R.; Gasperini, B.; Cariati, I.; Chiavoghilefu, A.; Smakaj, A.; Visconti, V. V.; Botta, A.; Iundusi, R.; Gasbarra, E.; Tancredi, V.; and Tarantino, U.\n\n\n \n\n\n\n Biomedicines, 13(6): 1350. May 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Altered$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{falvino_altered_2025,\n\ttitle = {Altered {Expression} of {Cell} {Cycle} {Regulators} and {Factors} {Released} by {Aged} {Cells} in {Skeletal} {Muscle} of {Patients} with {Bone} {Fragility}: {A} {Pilot} {Study} on the {Potential} {Role} of {SIRT1} in {Muscle} {Atrophy}},\n\tvolume = {13},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2227-9059},\n\tshorttitle = {Altered {Expression} of {Cell} {Cycle} {Regulators} and {Factors} {Released} by {Aged} {Cells} in {Skeletal} {Muscle} of {Patients} with {Bone} {Fragility}},\n\turl = {https://www.mdpi.com/2227-9059/13/6/1350},\n\tdoi = {10.3390/biomedicines13061350},\n\tabstract = {Background/Objectives: Cellular aging represents a crucial element in the progression of musculoskeletal diseases, contributing to muscle atrophy, functional decline, and alterations in bone turnover, which promote fragility fractures. However, knowledge about expression patterns of factors potentially involved in aging and senescence at the tissue level remains limited. Our pilot study aimed to characterize the expression profile of cell cycle regulators, factors released by aged cells, and sirtuin 1 (SIRT1) in the muscle tissue of 26 elderly patients undergoing hip arthroplasty, including 13 with low-energy fracture and 13 with osteoarthritis (OA). Methods: The mRNA expression levels of cyclin-dependent kinase inhibitor 1A (CDKN1A), cyclin-dependent kinase inhibitor 1B (CDKN1B), cyclin-dependent kinase inhibitor 2A (CDKN2A), p53, tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-15 (IL-15), chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-C motif) ligand 3 (CCL3), growth differentiation factor 15 (GDF15), and SIRT1 were evaluated in muscle tissue by qRT-PCR. In addition, immunohistochemistry and Western blotting analysis were conducted to measure the protein levels of SIRT1. Results: A marked muscle atrophy was observed in fractured patients compared to the OA group, in association with an up-regulation of cell cycle regulators and factors released by the aged cells. The expression of matrix metallopeptidase 3 (MMP3), plasminogen activator inhibitor 1 (PAI-1), and fas cell surface death receptor (FAS) was also investigated, although no significant differences were observed between the two experimental groups. Notably, SIRT1 expression was significantly higher in OA patients, confirming its role in maintaining muscle health during aging. Conclusions: Further studies will be needed to clarify the role of SIRT1 in the senescence characteristic of age-related musculoskeletal disorders, counteracting the muscle atrophy that predisposes to fragility fractures.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2025-07-30},\n\tjournal = {Biomedicines},\n\tauthor = {Falvino, Angela and Bonanni, Roberto and Gasperini, Beatrice and Cariati, Ida and Chiavoghilefu, Angela and Smakaj, Amarildo and Visconti, Virginia Veronica and Botta, Annalisa and Iundusi, Riccardo and Gasbarra, Elena and Tancredi, Virginia and Tarantino, Umberto},\n\tmonth = may,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {1350},\n}\n\n\n\n

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\n Background/Objectives: Cellular aging represents a crucial element in the progression of musculoskeletal diseases, contributing to muscle atrophy, functional decline, and alterations in bone turnover, which promote fragility fractures. However, knowledge about expression patterns of factors potentially involved in aging and senescence at the tissue level remains limited. Our pilot study aimed to characterize the expression profile of cell cycle regulators, factors released by aged cells, and sirtuin 1 (SIRT1) in the muscle tissue of 26 elderly patients undergoing hip arthroplasty, including 13 with low-energy fracture and 13 with osteoarthritis (OA). Methods: The mRNA expression levels of cyclin-dependent kinase inhibitor 1A (CDKN1A), cyclin-dependent kinase inhibitor 1B (CDKN1B), cyclin-dependent kinase inhibitor 2A (CDKN2A), p53, tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-15 (IL-15), chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-C motif) ligand 3 (CCL3), growth differentiation factor 15 (GDF15), and SIRT1 were evaluated in muscle tissue by qRT-PCR. In addition, immunohistochemistry and Western blotting analysis were conducted to measure the protein levels of SIRT1. Results: A marked muscle atrophy was observed in fractured patients compared to the OA group, in association with an up-regulation of cell cycle regulators and factors released by the aged cells. The expression of matrix metallopeptidase 3 (MMP3), plasminogen activator inhibitor 1 (PAI-1), and fas cell surface death receptor (FAS) was also investigated, although no significant differences were observed between the two experimental groups. Notably, SIRT1 expression was significantly higher in OA patients, confirming its role in maintaining muscle health during aging. Conclusions: Further studies will be needed to clarify the role of SIRT1 in the senescence characteristic of age-related musculoskeletal disorders, counteracting the muscle atrophy that predisposes to fragility fractures.\n

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\n \n\n \n \n \n \n \n \n The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.\n \n \n \n \n\n\n \n Dei Cas, D.; Di Camillo, B.; Fadini, G. P.; Sparacino, G.; and Longato, E.\n\n\n \n\n\n\n Computer Methods and Programs in Biomedicine, 268: 108812. August 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{dei_cas_impact_2025,\n\ttitle = {The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes},\n\tvolume = {268},\n\tissn = {01692607},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0169260725002299},\n\tdoi = {10.1016/j.cmpb.2025.108812},\n\tlanguage = {en},\n\turldate = {2025-07-30},\n\tjournal = {Computer Methods and Programs in Biomedicine},\n\tauthor = {Dei Cas, Davide and Di Camillo, Barbara and Fadini, Gian Paolo and Sparacino, Giovanni and Longato, Enrico},\n\tmonth = aug,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {108812},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Survey of Hand Hygiene, High-Touch Device Use, and Proper Habits of Health Care Workers for Infection Risk Prevention: Protocol for a Cross-Sectional Study.\n \n \n \n \n\n\n \n Aprile, A.; Morlino, G.; Mosconi, C.; Guarente, L.; Messina, A.; Carestia, M.; De Filippis, P.; Pica, F.; Maurici, M.; and Palombi, L.\n\n\n \n\n\n\n JMIR Research Protocols, 14: e60450. April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Survey$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{aprile_survey_2025,\n\ttitle = {Survey of {Hand} {Hygiene}, {High}-{Touch} {Device} {Use}, and {Proper} {Habits} of {Health} {Care} {Workers} for {Infection} {Risk} {Prevention}: {Protocol} for a {Cross}-{Sectional} {Study}},\n\tvolume = {14},\n\tissn = {1929-0748},\n\tshorttitle = {Survey of {Hand} {Hygiene}, {High}-{Touch} {Device} {Use}, and {Proper} {Habits} of {Health} {Care} {Workers} for {Infection} {Risk} {Prevention}},\n\turl = {https://www.researchprotocols.org/2025/1/e60450},\n\tdoi = {10.2196/60450},\n\tabstract = {Background\n              Care-related infections are infectious diseases that occur in a care setting. The most important prevention methods are hand hygiene and the proper use of gloves and gowns. Recent literature points out that hand contact with mobile devices or potentially contaminated environments can promote an increased occurrence of health care–associated infections (HAIs).\n            \n            \n              Objective\n              This study aims to analyze the correlation between the microbial population present on the hands of health care professionals in the wards of the Tor Vergata Hospital in Rome and the microorganisms present on the surfaces of their smartphones and tablets by searching for the main agents responsible for HAIs.\n            \n            \n              Methods\n              Sterile swabs will be used to collect samples from hands and smartphones, which will then be plated on nutrient agar and other selective media for microbial count. Colonies showing growth and morphological characteristics suggestive of potential pathogens will be isolated and subjected to further analysis for identification at the species level and for antimicrobial resistance profiling (using a proprietary automated analytical profile index system). Sampling will be conducted quarterly (first 2 weeks of each quarter) to assess any changes in microbial flora. In parallel, an Italian version of the World Health Organization questionnaire on health care workers’ knowledge of hand hygiene and a questionnaire on the use of high-touch devices will be administered to participants. Each quarter, 30 health workers will be selected, resulting in a total of 120 health workers and 240 samples collected by the end of the study. For each sample, the analysis will focus on quantifying the total bacterial load at 37 °C and 22 °C, along with detecting coliforms or Escherichia coli, Enterococci, Staphylococci, Acinetobacter, Klebsiella, Pseudomonas, and any associated antimicrobial resistance.\n            \n            \n              Results\n              The study aims to begin sample collection by June 2025. The protocol was properly evaluated and approved by the territorial ethics committee “Lazio Area 2” on March 21, 2024, with the code 76.24 CET2 utv\\_ptv.\n            \n            \n              Conclusions\n              The findings of this study will be crucial in highlighting the need for targeted education and training of health care practitioners involved in the study, with a focus on the prevention of HAIs.\n            \n            \n              International Registered Report Identifier (IRRID)\n              PRR1-10.2196/60450},\n\tlanguage = {en},\n\turldate = {2025-07-30},\n\tjournal = {JMIR Research Protocols},\n\tauthor = {Aprile, Antonio and Morlino, Giustino and Mosconi, Claudia and Guarente, Luca and Messina, Alessandra and Carestia, Mariachiara and De Filippis, Patrizia and Pica, Francesca and Maurici, Massimo and Palombi, Leonardo},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {e60450},\n}\n\n\n\n

\n\n\n

\n Background Care-related infections are infectious diseases that occur in a care setting. The most important prevention methods are hand hygiene and the proper use of gloves and gowns. Recent literature points out that hand contact with mobile devices or potentially contaminated environments can promote an increased occurrence of health care–associated infections (HAIs). Objective This study aims to analyze the correlation between the microbial population present on the hands of health care professionals in the wards of the Tor Vergata Hospital in Rome and the microorganisms present on the surfaces of their smartphones and tablets by searching for the main agents responsible for HAIs. Methods Sterile swabs will be used to collect samples from hands and smartphones, which will then be plated on nutrient agar and other selective media for microbial count. Colonies showing growth and morphological characteristics suggestive of potential pathogens will be isolated and subjected to further analysis for identification at the species level and for antimicrobial resistance profiling (using a proprietary automated analytical profile index system). Sampling will be conducted quarterly (first 2 weeks of each quarter) to assess any changes in microbial flora. In parallel, an Italian version of the World Health Organization questionnaire on health care workers’ knowledge of hand hygiene and a questionnaire on the use of high-touch devices will be administered to participants. Each quarter, 30 health workers will be selected, resulting in a total of 120 health workers and 240 samples collected by the end of the study. For each sample, the analysis will focus on quantifying the total bacterial load at 37 °C and 22 °C, along with detecting coliforms or Escherichia coli, Enterococci, Staphylococci, Acinetobacter, Klebsiella, Pseudomonas, and any associated antimicrobial resistance. Results The study aims to begin sample collection by June 2025. The protocol was properly evaluated and approved by the territorial ethics committee “Lazio Area 2” on March 21, 2024, with the code 76.24 CET2 utv_ptv. Conclusions The findings of this study will be crucial in highlighting the need for targeted education and training of health care practitioners involved in the study, with a focus on the prevention of HAIs. International Registered Report Identifier (IRRID) PRR1-10.2196/60450\n

\n\n\n

\n \n\n \n \n \n \n \n \n Umbrella Review of Systematic Reviews and Meta-Analyses on Consumption of Different Food Groups and Risk of Type 2 Diabetes Mellitus and Metabolic Syndrome.\n \n \n \n \n\n\n \n Banjarnahor, R.; Javadi Arjmand, E.; Onni, A.; Thomassen, L.; Perillo, M.; Balakrishna, R.; Sletten, I.; Lorenzini, A.; Plastina, P.; and Fadnes, L.\n\n\n \n\n\n\n Journal of Nutrition, 155(5): 1285–1297. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Umbrella$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{banjarnahor_umbrella_2025,\n\ttitle = {Umbrella {Review} of {Systematic} {Reviews} and {Meta}-{Analyses} on {Consumption} of {Different} {Food} {Groups} and {Risk} of {Type} 2 {Diabetes} {Mellitus} and {Metabolic} {Syndrome}},\n\tvolume = {155},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002294382&doi=10.1016%2fj.tjnut.2025.03.021&partnerID=40&md5=e6683d352a0c3ef63b5da93d861ebd14},\n\tdoi = {10.1016/j.tjnut.2025.03.021},\n\tnumber = {5},\n\tjournal = {Journal of Nutrition},\n\tauthor = {Banjarnahor, R.L. and Javadi Arjmand, E. and Onni, A.T. and Thomassen, L.M. and Perillo, M. and Balakrishna, R. and Sletten, I.S.K. and Lorenzini, A. and Plastina, P. and Fadnes, L.T.},\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {1285--1297},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Population risk stratification tools and interventions for chronic disease management in primary care: a systematic literature review.\n \n \n \n \n\n\n \n Golinelli, D.; Pecoraro, V.; Tedesco, D.; Negro, A.; Berti, E.; Camerlingo, M.; Alberghini, L.; Lippi Bruni, M.; Rolli, M.; and Grilli, R.\n\n\n \n\n\n\n BMC Health Services Research, 25(1). 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Population$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{golinelli_population_2025,\n\ttitle = {Population risk stratification tools and interventions for chronic disease management in primary care: a systematic literature review},\n\tvolume = {25},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003020418&doi=10.1186%2fs12913-025-12690-0&partnerID=40&md5=07974d71a9f9c790cf204fc37f1d83d6},\n\tdoi = {10.1186/s12913-025-12690-0},\n\tnumber = {1},\n\tjournal = {BMC Health Services Research},\n\tauthor = {Golinelli, D. and Pecoraro, V. and Tedesco, D. and Negro, A. and Berti, E. and Camerlingo, M.D. and Alberghini, L. and Lippi Bruni, M. and Rolli, M. and Grilli, R.},\n\tyear = {2025},\n\tkeywords = {SP2},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Bioelectronic Large-Area Transistors for High-Performance Sensing.\n \n \n \n \n\n\n \n Macchia, E.; Bollella, P.; and Torsi, L.\n\n\n \n\n\n\n Annual Review of Analytical Chemistry, 18(1): 407–425. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Bioelectronic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{macchia_bioelectronic_2025,\n\ttitle = {Bioelectronic {Large}-{Area} {Transistors} for {High}-{Performance} {Sensing}},\n\tvolume = {18},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005567203&doi=10.1146%2fannurev-anchem-061522-034729&partnerID=40&md5=ef786a6adcfb9c4ae1b73bccdaff944d},\n\tdoi = {10.1146/annurev-anchem-061522-034729},\n\tnumber = {1},\n\tjournal = {Annual Review of Analytical Chemistry},\n\tauthor = {Macchia, E. and Bollella, P. and Torsi, L.},\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {407--425},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Critical behavior of epidemics depending on the interplay between temporal scales and human behavior.\n \n \n \n \n\n\n \n Maniscalco, D.; Bertola, T.; d'Andrea , V.; and De Domenico, M.\n\n\n \n\n\n\n Chaos, Solitons and Fractals, 198. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Critical$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{maniscalco_critical_2025,\n\ttitle = {Critical behavior of epidemics depending on the interplay between temporal scales and human behavior},\n\tvolume = {198},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004266362&doi=10.1016%2fj.chaos.2025.116501&partnerID=40&md5=f0e869b9f4a6f3ac889331d6142f7670},\n\tdoi = {10.1016/j.chaos.2025.116501},\n\tjournal = {Chaos, Solitons and Fractals},\n\tauthor = {Maniscalco, D. and Bertola, T. and d'Andrea, V. and De Domenico, M.},\n\tyear = {2025},\n\tkeywords = {SP2},\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Methodological and Applied Statistics and Demography III: SIS 2024, Short Papers, Contributed Sessions 1.\n \n \n \n \n\n\n \n Pollice, A.; and Mariani, P.,\n editors.\n \n\n\n \n\n\n\n In Pollice, A.; and Mariani, P., editor(s), of Italian Statistical Society Series on Advances in Statistics, Cham, 2025. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n \n $\"Methodological$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{pollice_methodological_2025,\n\taddress = {Cham},\n\tseries = {Italian {Statistical} {Society} {Series} on {Advances} in {Statistics}},\n\ttitle = {Methodological and {Applied} {Statistics} and {Demography} {III}: {SIS} 2024, {Short} {Papers}, {Contributed} {Sessions} 1},\n\tcopyright = {https://www.springernature.com/gp/researchers/text-and-data-mining},\n\tisbn = {978-3-031-64430-6 978-3-031-64431-3},\n\tshorttitle = {Methodological and {Applied} {Statistics} and {Demography} {III}},\n\turl = {https://link.springer.com/10.1007/978-3-031-64431-3},\n\tdoi = {10.1007/978-3-031-64431-3},\n\tlanguage = {en},\n\turldate = {2025-02-27},\n\tpublisher = {Springer Nature Switzerland},\n\teditor = {Pollice, Alessio and Mariani, Paolo},\n\tyear = {2025},\n\tkeywords = {SP2, WP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Bilingual Dual-Head Deep Model for Parkinson’s Disease Detection from Speech.\n \n \n \n \n\n\n \n La Quatra, M.; Orozco-Arroyave, J. R.; and Siniscalchi, M. S.\n\n\n \n\n\n\n In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1–5, Hyderabad, India, April 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Bilingual$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{la_quatra_bilingual_2025,\n\taddress = {Hyderabad, India},\n\ttitle = {Bilingual {Dual}-{Head} {Deep} {Model} for {Parkinson}’s {Disease} {Detection} from {Speech}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3503-6874-1},\n\turl = {https://ieeexplore.ieee.org/document/10889445/},\n\tdoi = {10.1109/ICASSP49660.2025.10889445},\n\turldate = {2025-06-05},\n\tbooktitle = {{ICASSP} 2025 - 2025 {IEEE} {International} {Conference} on {Acoustics}, {Speech} and {Signal} {Processing} ({ICASSP})},\n\tpublisher = {IEEE},\n\tauthor = {La Quatra, Moreno and Orozco-Arroyave, Juan Rafael and Siniscalchi, Marco Sabato},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {1--5},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Genomic profiling at a single center cracks the code in inborn errors of immunity.\n \n \n \n \n\n\n \n Andriano, A.; Desantis, V.; Marasco, C.; Marzollo, A.; Bresolin, S.; Resta, N.; Di Marzo, L.; Pappagallo, F.; Mascolo, A.; Caradonna, I. C.; D’Amore, S.; Vacca, A.; and Solimando, A. G.\n\n\n \n\n\n\n Internal and Emergency Medicine. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Genomic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{andriano_genomic_2025,\n\ttitle = {Genomic profiling at a single center cracks the code in inborn errors of immunity},\n\tissn = {1828-0447, 1970-9366},\n\turl = {https://link.springer.com/10.1007/s11739-025-03871-0},\n\tdoi = {10.1007/s11739-025-03871-0},\n\tabstract = {Abstract\n            \n              Inborn errors of immunity (IEI) entail a diverse group of disorders resulting from hereditary or de novo mutations in single genes, leading to immune dysregulation. This study explores the clinical utility of next-generation sequencing (NGS) techniques in diagnosing monogenic immune defects. Eight patients attending the immunodeficiency clinic and with unclassified antibody deficiency were included in the analysis. Clinical records, immune characteristics, and family histories were reviewed, and a target gene panel (TGP) sequencing was performed to identify pathogenic variants. TGPs identified seven variants in\n              TNFRSF13B\n              (TACI),\n              CARMIL2\n              ,\n              STAT1\n              ,\n              STAT3\n              , and\n              ORAI1\n              genes. These findings provided definitive diagnoses and proper prognostic assessment. Patients exhibited a wide range of clinical manifestations, including recurrent infections, autoimmune cytopenias, and organ-specific complications. The genetic diversity observed highlights the importance of genetic testing in diagnosing IEIs and tailoring treatments. This study underscores the role of TGPs in diagnosing IEIs, revealing significant genetic heterogeneity and phenotypic variability. They offer a precise tool for identifying underlying genetic defects, facilitating personalized medicine approaches, and eventually improving patient outcomes. The findings emphasize the need for comprehensive genetic testing to uncover novel pathogenic variants, enhancing our understanding of immune system dysfunction. NGS is a critical tool for the management of IEI, enabling precise diagnosis and personalized treatment strategies. Despite resource limitations, the progressive affordability is likely to expand its clinical utility, ultimately improving patient care and advancing the field of immunology. In the meantime, accurate phenotypic assessment is essential for resource optimization and case prioritization.},\n\tlanguage = {en},\n\turldate = {2025-04-17},\n\tjournal = {Internal and Emergency Medicine},\n\tauthor = {Andriano, Alessandro and Desantis, Vanessa and Marasco, Carolina and Marzollo, Antonio and Bresolin, Silvia and Resta, Nicoletta and Di Marzo, Lucia and Pappagallo, Fabrizio and Mascolo, Antonella and Caradonna, Ingrid Catalina and D’Amore, Simona and Vacca, Angelo and Solimando, Antonio Giovanni},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP3},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Qini Curves for Potential Impact Assessment of Risk Predictive Models Informing Intervention Policies.\n \n \n \n \n\n\n \n Palumbo, P.\n\n\n \n\n\n\n Value in Health,S109830152500066X. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Qini$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{palumbo_qini_2025,\n\ttitle = {Qini {Curves} for {Potential} {Impact} {Assessment} of {Risk} {Predictive} {Models} {Informing} {Intervention} {Policies}},\n\tissn = {10983015},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S109830152500066X},\n\tdoi = {10.1016/j.jval.2025.01.024},\n\tlanguage = {en},\n\turldate = {2025-04-17},\n\tjournal = {Value in Health},\n\tauthor = {Palumbo, Pierpaolo},\n\tmonth = feb,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {S109830152500066X},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Rad4XCNN: A new agnostic method for post-hoc global explanation of CNN-derived features by means of Radiomics.\n \n \n \n \n\n\n \n Prinzi, F.; Militello, C.; Zarcaro, C.; Bartolotta, T. V.; Gaglio, S.; and Vitabile, S.\n\n\n \n\n\n\n Computer Methods and Programs in Biomedicine, 260: 108576. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Rad4XCNN:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{prinzi_rad4xcnn_2025,\n\ttitle = {{Rad4XCNN}: {A} new agnostic method for post-hoc global explanation of {CNN}-derived features by means of {Radiomics}},\n\tvolume = {260},\n\tissn = {01692607},\n\tshorttitle = {{Rad4XCNN}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0169260724005698},\n\tdoi = {10.1016/j.cmpb.2024.108576},\n\tlanguage = {en},\n\turldate = {2025-04-17},\n\tjournal = {Computer Methods and Programs in Biomedicine},\n\tauthor = {Prinzi, Francesco and Militello, Carmelo and Zarcaro, Calogero and Bartolotta, Tommaso Vincenzo and Gaglio, Salvatore and Vitabile, Salvatore},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {108576},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A light in the darkness: Early phases of development and the emergence of cognition.\n \n \n \n \n\n\n \n Cainelli, E.; Stramucci, G.; and Bisiacchi, P.\n\n\n \n\n\n\n Developmental Cognitive Neuroscience, 72: 101527. April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{cainelli_light_2025,\n\ttitle = {A light in the darkness: {Early} phases of development and the emergence of cognition},\n\tvolume = {72},\n\tissn = {18789293},\n\tshorttitle = {A light in the darkness},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1878929325000222},\n\tdoi = {10.1016/j.dcn.2025.101527},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Developmental Cognitive Neuroscience},\n\tauthor = {Cainelli, Elisa and Stramucci, Giulia and Bisiacchi, Patrizia},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP2, WP5},\n\tpages = {101527},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Classifying Food Items During an Eating Occasion: A Machine Learning Approach with Slope Dynamics for Windowed Kinetic Data.\n \n \n \n \n\n\n \n Baldi, I.; Lanera, C.; Bhuyan, M. J.; Berchialla, P.; Vedovelli, L.; and Gregori, D.\n\n\n \n\n\n\n Foods, 14(2): 276. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Classifying$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{baldi_classifying_2025,\n\ttitle = {Classifying {Food} {Items} {During} an {Eating} {Occasion}: {A} {Machine} {Learning} {Approach} with {Slope} {Dynamics} for {Windowed} {Kinetic} {Data}},\n\tvolume = {14},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2304-8158},\n\tshorttitle = {Classifying {Food} {Items} {During} an {Eating} {Occasion}},\n\turl = {https://www.mdpi.com/2304-8158/14/2/276},\n\tdoi = {10.3390/foods14020276},\n\tabstract = {Background: Wearable devices equipped with a range of sensors have emerged as promising tools for monitoring and improving individuals’ health and lifestyle. Objectives: Contribute to the investigation and development of effective and reliable methods for dietary monitoring based on raw kinetic data generated by wearable devices. Methods: This study uses resources from the NOTION study. A total of 20 healthy subjects (9 women and 11 men, aged 20–31 years) were equipped with two commercial smartwatches during four eating occasions under semi-naturalistic conditions. All meals were video-recorded, and acceleration data were extracted and analyzed. Food recognition on these features was performed using random forest (RF) models with 5-fold cross-validation. The performance of the classifiers was expressed in out-of-bag sensitivity and specificity. Results: Acceleration along the x-axis and power show the highest and lowest rates of median variable importance, respectively. Increasing the window size from 1 to 5 s leads to a gain in performance for almost all food items. The RF classifier reaches the highest performance in identifying meatballs (89.4\\% sensitivity and 81.6\\% specificity) and the lowest in identifying sandwiches (74.6\\% sensitivity and 72.5\\% specificity). Conclusions: Monitoring food items using simple wristband-mounted wearable devices is feasible and accurate for some foods while unsatisfactory for others. Machine learning tools are necessary to deal with the complexity of signals gathered by the devices, and research is ongoing to improve accuracy further and work on large-scale and real-time implementation and testing.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2025-03-20},\n\tjournal = {Foods},\n\tauthor = {Baldi, Ileana and Lanera, Corrado and Bhuyan, Mohammad Junayed and Berchialla, Paola and Vedovelli, Luca and Gregori, Dario},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP3, WP5},\n\tpages = {276},\n}\n\n\n\n

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@article{cotugno_pre-vaccination_2025,\n\ttitle = {Pre-vaccination immune markers predict response to {BNT162b2} {mRNA} vaccine in vulnerable groups – {The} {CONVERS} project, report from a pediatric tertiary hospital},\n\tvolume = {49},\n\tissn = {0264410X},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0264410X25000751},\n\tdoi = {10.1016/j.vaccine.2025.126778},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Vaccine},\n\tauthor = {Cotugno, Nicola and Sanna, Marco and Amodio, Donato and Morrocchi, Elena and Pighi, Chiara and Medri, Chiara and Pascucci, Giuseppe Rubens and Santilli, Veronica and Manno, Emma Concetta and Zangari, Paola and Rossetti, Chiara and Colantoni, Nicole and Olivieri, Giulio and Emili, Elena and Neri, Alessia and Rotili, Arianna and Rossi, Paolo and Levy, Ofer and Putignani, Lorenza and Palma, Paolo and Romani, Lorenza and Finocchi, Andrea and Cancrini, Caterina and Moschese, Viviana and Sgrulletti, Mayla and Lancella, Laura and Bernardi, Stefania and De Luca, Maia and Giancotta, Carmela and Colagrossi, Luna and Bonfante, Francesco and Profeti, Elisa and Franzese, Enrica and Amodeo, Antonino and Perno, Carlo Federico and Atti, Marta Ciofi Degli and Plebani, Carlo and Giaquinto, Carlo and Valentini, Diletta and Villani, Alberto and De Angelis, Paola and Rea, Francesca and Tambucci, Renato and Rivalta, Beatrice and Pacillo, Lucia and Rotulo, Gioacchino Andrea},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP3, WP3},\n\tpages = {126778},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Position paper: Extending Credibility Assessment of In Silico Medicine Predictors to Machine Learning Predictors.\n \n \n \n \n\n\n \n Viceconti, M.; Lanubile, F.; Carbonaro, A.; Mellone, S.; Curreli, C.; Aldieri, A.; Ranciati, S.; and Montanari, A.\n\n\n \n\n\n\n IEEE Journal of Biomedical and Health Informatics,1–9. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Position$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{viceconti_position_2025,\n\ttitle = {Position paper: {Extending} {Credibility} {Assessment} of {In} {Silico} {Medicine} {Predictors} to {Machine} {Learning} {Predictors}},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/legalcode},\n\tissn = {2168-2194, 2168-2208},\n\tshorttitle = {Position paper},\n\turl = {https://ieeexplore.ieee.org/document/10930459/},\n\tdoi = {10.1109/JBHI.2025.3552320},\n\turldate = {2025-03-27},\n\tjournal = {IEEE Journal of Biomedical and Health Informatics},\n\tauthor = {Viceconti, Marco and Lanubile, Filippo and Carbonaro, Antonella and Mellone, Sabato and Curreli, Cristina and Aldieri, Alessandra and Ranciati, Saverio and Montanari, Angela},\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {1--9},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Comparative Evaluation of Commercial, Freely Available, and Open-Source Tools for Single-Cell Analysis Within Freehand-Defined Histological Brightfield Image Regions of Interest.\n \n \n \n \n\n\n \n Piccinini, F.; Tazzari, M.; Tumedei, M. M.; Normanno, N.; Castellani, G.; and Carbonaro, A.\n\n\n \n\n\n\n Technologies, 13(3): 110. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparative$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{piccinini_comparative_2025,\n\ttitle = {Comparative {Evaluation} of {Commercial}, {Freely} {Available}, and {Open}-{Source} {Tools} for {Single}-{Cell} {Analysis} {Within} {Freehand}-{Defined} {Histological} {Brightfield} {Image} {Regions} of {Interest}},\n\tvolume = {13},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2227-7080},\n\turl = {https://www.mdpi.com/2227-7080/13/3/110},\n\tdoi = {10.3390/technologies13030110},\n\tabstract = {In the field of histological analysis, one of the typical issues is the analysis of single cells contained in regions of interest (i.e., ROIs). Today, several commercial, freely available, and open-source software options are accessible for this task. However, the literature lacks recent extensive reviews that summarise the functionalities of the opportunities currently available and provide guidance on selecting the most suitable option for analysing specific cases, for instance, irregular freehand-defined ROIs on brightfield images. In this work, we reviewed and compared 14 software tools tailored for single-cell analysis within a 2D histological freehand-defined image ROI. Precisely, six open-source tools (i.e., CellProfiler, Cytomine, Digital Slide Archive, Icy, ImageJ/Fiji, QuPath), four freely available tools (i.e., Aperio ImageScope, NIS Elements Viewer, Sedeen, SlideViewer), and four commercial tools (i.e., Amira, Arivis, HALO, Imaris) were considered. We focused on three key aspects: (a) the capacity to handle large file formats such as SVS, DICOM, and TIFF, ensuring compatibility with diverse datasets; (b) the flexibility in defining irregular ROIs, whether through automated extraction or manual delineation, encompassing square, circular, polygonal, and freehand shapes to accommodate varied research needs; and (c) the capability to classify single cells within selected ROIs on brightfield images, ranging from fully automated to semi-automated or manual approaches, requiring different levels of user involvement. Thanks to this work, a deeper understanding of the strengths and limitations of different software platforms emerges, facilitating informed decision making for researchers looking for a tool to analyse histological brightfield images.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2025-03-27},\n\tjournal = {Technologies},\n\tauthor = {Piccinini, Filippo and Tazzari, Marcella and Tumedei, Maria Maddalena and Normanno, Nicola and Castellani, Gastone and Carbonaro, Antonella},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {110},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Acyclovir desensitization. A case report and a review of desensitization strategies.\n \n \n \n \n\n\n \n Spataro, F.; Ria, R.; Choul, N.; Vacca, A.; Solimando, A. G; and Di Girolamo, A.\n\n\n \n\n\n\n Journal of Infection in Developing Countries, 19(01): 174–180. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Acyclovir$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{spataro_acyclovir_2025,\n\ttitle = {Acyclovir desensitization. {A} case report and a review of desensitization strategies},\n\tvolume = {19},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0},\n\tissn = {1972-2680},\n\turl = {https://www.jidc.org/index.php/journal/article/view/20300},\n\tdoi = {10.3855/jidc.20300},\n\tabstract = {Introduction: Acyclovir is a synthetic purine nucleoside analog that is used to treat infections caused by herpes simplex virus (HSV) and varicella zoster virus (VZV) by targeting the viral enzyme thymidine kinase. However, its use can lead to hypersensitivity reactions (HR) in rare cases, resulting in treatment discontinuation. Rapid drug desensitization (DD) by intravenous or oral administration protocols are used in these patients in order to avoid treatment discontinuation. This approach has been proven to be effective and safe. Here, we review all the desensitization strategies adopted so far, and also report our experience.\nMethodology: We reviewed all reports related to acyclovir desensitization; focusing on skin test results, protocols and premedication performed, and their effectiveness. We also report on the case of a 74-year-old woman affected by multiple myeloma who developed HR to acyclovir. She underwent skin tests, and lymphocyte proliferation test (LPT) with acyclovir, and was subsequently subjected to oral desensitization.\nResults. Six articles met the inclusion criteria and were analyzed in this review, along with a case report. All DD procedures were well-tolerated, with only mild reactions reported in one patient. Skin tests gave negative results but one result was deemed doubtful response. Moreover, the LPT performed in our case had positive result, indicating a hypersensitive immune response to acyclovir.\nConclusions. Acyclovir desensitization is a safe and effective approach for patients experiencing HR. Standardized in vivo and in vitro testing are required to better estimate the risk of DD and find the safest individualized DD protocol.},\n\tnumber = {01},\n\turldate = {2025-03-20},\n\tjournal = {Journal of Infection in Developing Countries},\n\tauthor = {Spataro, Federico and Ria, Roberto and Choul, Nada and Vacca, Angelo and Solimando, Antonio G and Di Girolamo, Attilio},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {174--180},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Evaluating gait and postural responses to subthalamic stimulation and levodopa: A prospective study using wearable technology.\n \n \n \n \n\n\n \n Cani, I.; D'Ascanio, I.; Baldelli, L.; Lopane, G.; Ranciati, S.; Mantovani, P.; Conti, A.; Cortelli, P.; Calandra‐Buonaura, G.; Chiari, L.; Palmerini, L.; and Giannini, G.\n\n\n \n\n\n\n European Journal of Neurology, 32(1): e16580. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{cani_evaluating_2025,\n\ttitle = {Evaluating gait and postural responses to subthalamic stimulation and levodopa: {A} prospective study using wearable technology},\n\tvolume = {32},\n\tissn = {1351-5101, 1468-1331},\n\tshorttitle = {Evaluating gait and postural responses to subthalamic stimulation and levodopa},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/ene.16580},\n\tdoi = {10.1111/ene.16580},\n\tabstract = {Abstract\n            \n            \n              \n                Background\n              \n              \n                The efficacy of subthalamic stimulation on axial signs of Parkinson's disease (PD) is debated in the literature. This study delves into the dynamic interplay of gait and posture, specifically probing their nuanced response to subthalamic stimulation and levodopa.\n              \n            \n            \n              \n                Methods\n              \n              \n                We used wearable sensor technology to examine alterations in the spatiotemporal parameters of gait and posture in individuals with PD before and 6 months after subthalamic deep brain stimulation (STN‐DBS) surgery. Thirty‐three subjects with PD were evaluated in two pre‐operative and four post‐operative conditions comprising OFF/ON medication and stimulation states. Standardized response mean (SRM) values were calculated to assess treatment responsiveness.\n              \n            \n            \n              \n                Results\n              \n              \n                Significant improvements in spatiotemporal gait parameters, including speed, stride length, cadence, and turning, were observed following STN‐DBS surgery. Quantitatively, stimulation outperformed levodopa in enhancing gait speed, stride length, and turning, as indicated by SRM. Levodopa moderately improved stride time variability and asymmetry, while stimulation alone demonstrated limited efficacy. Postural parameters exhibited minimal change following STN‐DBS, although stimulation showed a slight benefit in certain postural aspects.\n              \n            \n            \n              \n                Conclusion\n              \n              \n                Our findings suggest positive effects of stimulation and levodopa on gait and postural parameters, with STN‐DBS demonstrating superior efficacy in enhancing gait speed, stride length, and turning. However, gait variability remains unaddressed by current therapies, highlighting the need for novel treatments targeting regions beyond the basal ganglia.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-03-20},\n\tjournal = {European Journal of Neurology},\n\tauthor = {Cani, Ilaria and D'Ascanio, Ilaria and Baldelli, Luca and Lopane, Giovanna and Ranciati, Saverio and Mantovani, Paolo and Conti, Alfredo and Cortelli, Pietro and Calandra‐Buonaura, Giovanna and Chiari, Lorenzo and Palmerini, Luca and Giannini, Giulia},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {e16580},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Rapid and Ultra‐Sensitive SARS‐CoV‐2 Subgenomic RNA Detection Using Single‐Molecule With a Large Transistor‐SiMoT Bioelectronic Platform.\n \n \n \n \n\n\n \n Macchia, E.; D'Erchia, A. M.; Caputo, M.; Bianco, A.; Leoni, C.; Intranuovo, F.; Scandurra, C.; Sarcina, L.; Di Franco, C.; Bollella, P.; Scamarcio, G.; Torsi, L.; and Pesole, G.\n\n\n \n\n\n\n Advanced Electronic Materials,2400908. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Rapid$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{macchia_rapid_2025,\n\ttitle = {Rapid and {Ultra}‐{Sensitive} {SARS}‐{CoV}‐2 {Subgenomic} {RNA} {Detection} {Using} {Single}‐{Molecule} {With} a {Large} {Transistor}‐{SiMoT} {Bioelectronic} {Platform}},\n\tissn = {2199-160X, 2199-160X},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/aelm.202400908},\n\tdoi = {10.1002/aelm.202400908},\n\tabstract = {Abstract\n            The replication of Coronaviridae viruses depends on the synthesis of structural proteins expressed through the discontinuous transcription of subgenomic RNAs (sgRNAs). Thus, detecting sgRNAs, which reflect active viral replication, provides valuable insights into infection status. Current diagnostic methods, such as PCR‐based assays, often involve high costs, complex equipment, and reliance on highly trained personnel. Additionally, their specificity can be compromised by technical limitations in kit design. While viral culture remains highly accurate, it is impractical for routine diagnostics. In this study, the single‐molecule‐with‐a‐large‐transistor (SiMoT) technology is presented for detecting sgRNA encoding the nucleocapsid (N) protein in clinical samples. SiMoT incorporates a stable layer of complementary DNA strands on the sensing gate electrode, facilitating rapid, sensitive, and specific sgRNA detection. Among 90 tested samples, SiMoT achieved a diagnostic sensitivity of 98.0\\% and a specificity of 87.8\\%, delivering results within 30 min. This user‐friendly platform requires minimal sample preparation and offers a cost‐effective point‐of‐care (POC) diagnostic solution. With its demonstrated diagnostic accuracy and scalability, SiMoT represents a promising tool for detecting active viral replication in SARS‐CoV‐2 and other coronaviruses. It addresses the limitations of existing molecular and culture‐based methods while enhancing accessibility to reliable diagnostics.},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Advanced Electronic Materials},\n\tauthor = {Macchia, Eleonora and D'Erchia, Anna Maria and Caputo, Mariapia and Bianco, Angelica and Leoni, Claudia and Intranuovo, Francesca and Scandurra, Cecilia and Sarcina, Lucia and Di Franco, Cinzia and Bollella, Paolo and Scamarcio, Gaetano and Torsi, Luisa and Pesole, Graziano},\n\tmonth = feb,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2400908},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Digital integration between hospitals and local health authorities for enhanced vaccination coverage among frail patients: the CareVax study protocol.\n \n \n \n \n\n\n \n Lontano, A.; Regazzi, L.; Tona, D. M.; Di Pumpo, M.; Porcelli, M.; Cacciuttolo, M. G.; Parente, P.; Gasbarrini, A.; Grandaliano, G.; Panocchia, N.; Lopetuso, L.; Pasciuto, T.; Cadeddu, C.; Bruno, S.; Laurenti, P.; Pascucci, D.; and Pastorino, R.\n\n\n \n\n\n\n Frontiers in Public Health, 13: 1490244. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Digital$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{lontano_digital_2025,\n\ttitle = {Digital integration between hospitals and local health authorities for enhanced vaccination coverage among frail patients: the {CareVax} study protocol},\n\tvolume = {13},\n\tissn = {2296-2565},\n\tshorttitle = {Digital integration between hospitals and local health authorities for enhanced vaccination coverage among frail patients},\n\turl = {https://www.frontiersin.org/articles/10.3389/fpubh.2025.1490244/full},\n\tdoi = {10.3389/fpubh.2025.1490244},\n\tabstract = {Background\n              The 2022–2025 Italian Plan for vaccine prevention (PNPV), recognizes vaccine-preventable diseases (VPDs) as significant contributors to mortality, morbidity, and healthcare expenditure. The digitalization of the national vaccine registry is underway. Initiatives aimed at enhancing digital integration between hospitals and territories are limited, and there is still a gap in the development of automated systems for identifying patients who could benefit from vaccinations directly offered from hospitals.\n            \n            \n              Methods\n              \n                Adult frail patients who access the hospital will be recruited over 4 years, following the acquisition of informed consent. With the assistance of a privacy-preserving automated algorithm, electronic hospital and vaccination records will be utilized to assess eligibility for vaccinations against\n                SARS-CoV-2\n                ,\n                Herpes Zoster\n                ,\n                Influenza\n                ,\n                Streptococcus pneumoniae,\n                and\n                Hepatitis B\n                . Eligible patients will be invited to schedule a vaccination appointment and will be asked to fill in a questionnaire evaluating patient-reported experience measures (PREMs). Outcomes of interest are the feasibility of the pathway, patients’ satisfaction and concerns with it, and its impact on vaccination coverage.\n              \n            \n            \n              Ethics and dissemination\n              \n                The study has been approved by the ethics committee of the “Fondazione Policlinico Universitario Agostino Gemelli” -FPG- (\n                comitato.etico@policlinicogemelli.it\n                ), with approval number 5819. Furthermore, it has been published on\n                ClinicalTrial.gov\n                with the approval number NCT06127563. The results of the study will be disseminated via conference presentations and peer-reviewed publications.\n              \n            \n            \n              Clinical trial registration\n              \n                ClinicalTrials.gov\n                , identifier NCT06127563.},\n\turldate = {2025-03-20},\n\tjournal = {Frontiers in Public Health},\n\tauthor = {Lontano, Alberto and Regazzi, Luca and Tona, Diego Maria and Di Pumpo, Matteo and Porcelli, Martina and Cacciuttolo, Maria Gabriella and Parente, Paolo and Gasbarrini, Antonio and Grandaliano, Giuseppe and Panocchia, Nicola and Lopetuso, Loris and Pasciuto, Tina and Cadeddu, Chiara and Bruno, Stefania and Laurenti, Patrizia and Pascucci, Domenico and Pastorino, Roberta},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {1490244},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging.\n \n \n \n \n\n\n \n Giacomel, A.; Martins, D.; Nordio, G.; Easmin, R.; Howes, O.; Selvaggi, P.; Williams, S. C. R.; Turkheimer, F.; De Groot, M.; Dipasquale, O.; Veronese, M.; the FDOPA PET imaging working group; Angelescu, I.; Bloomfield, M.; Bonoldi, I.; Borgan, F.; Dahoun, T.; D’Ambrosio, E.; Demjaha, A.; Donocik, J.; Egerton, A.; Kaar, S.; Kim, E.; Kim, S.; Maccabe, J.; Matthews, J.; McCutcheon, R.; McGuire, P.; Nosarti, C.; Nour, M.; Rogdaki, M.; Rutigliano, G.; Talbot, P. S.; and Vano, L.\n\n\n \n\n\n\n Molecular Psychiatry. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Investigating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{giacomel_investigating_2025,\n\ttitle = {Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging},\n\tissn = {1359-4184, 1476-5578},\n\turl = {https://www.nature.com/articles/s41380-025-02938-w},\n\tdoi = {10.1038/s41380-025-02938-w},\n\tabstract = {Abstract\n            \n              Molecular neuroimaging techniques, like PET and SPECT, offer invaluable insights into the brain’s in-vivo biology and its dysfunction in neuropsychiatric patients. However, the transition of molecular neuroimaging into diagnostics and precision medicine has been limited to a few clinical applications, hindered by issues like practical feasibility, high costs, and high between-subject heterogeneity of neuroimaging measures. In this study, we explore the use of normative modelling (NM) to identify individual patient alterations by describing the physiological variability of molecular functions. NM potentially addresses challenges such as small sample sizes and diverse acquisition protocols typical of molecular neuroimaging studies. We applied NM to two PET radiotracers targeting the dopaminergic system ([\n              11\n              C]-(+)-PHNO and [\n              18\n              F]FDOPA) to create a reference-cohort model of healthy controls. The models were subsequently utilized on different independent cohorts of patients with psychosis in different disease stages and treatment outcomes. Our results showed that patients with psychosis exhibited a higher degree of extreme deviations ({\\textasciitilde}3-fold increase) than controls, although this pattern was heterogeneous, with minimal overlap of extreme deviations topology (max 20\\%). We also confirmed that striatal [\n              18\n              F]FDOPA signal, when referenced to a normative distribution, can predict treatment response (striatal AUC ROC: 0.77–0.83). In conclusion, our results indicate that normative modelling can be effectively applied to molecular neuroimaging after proper harmonization, enabling insights into disease mechanisms and advancing precision medicine. In addition, the method is valuable in understanding the heterogeneity of patient populations and can contribute to maximising cost efficiency in studies aimed at comparing cases and controls.},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Molecular Psychiatry},\n\tauthor = {Giacomel, Alessio and Martins, Daniel and Nordio, Giovanna and Easmin, Rubaida and Howes, Oliver and Selvaggi, Pierluigi and Williams, Steven C. R. and Turkheimer, Federico and De Groot, Marius and Dipasquale, Ottavia and Veronese, Mattia and {the FDOPA PET imaging working group} and Angelescu, Ilinca and Bloomfield, Micheal and Bonoldi, Ilaria and Borgan, Faith and Dahoun, Tarik and D’Ambrosio, Enrico and Demjaha, Arsime and Donocik, Jecek and Egerton, Alice and Kaar, Stephen and Kim, Euitae and Kim, Seoyoung and Maccabe, James and Matthews, Julian and McCutcheon, Robert and McGuire, Philip and Nosarti, Chiara and Nour, Matthew and Rogdaki, Maria and Rutigliano, Grazia and Talbot, Peter S. and Vano, Luke},\n\tmonth = feb,\n\tyear = {2025},\n\tkeywords = {SP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Electric Field Cycling of Physisorbed Antibodies Reduces Biolayer Polarization Dispersion.\n \n \n \n \n\n\n \n Di Franco, C.; Macchia, E.; Catacchio, M.; Caputo, M.; Scandurra, C.; Sarcina, L.; Bollella, P.; Tricase, A.; Innocenti, M.; Funari, R.; Piscitelli, M.; Scamarcio, G.; and Torsi, L.\n\n\n \n\n\n\n Advanced Science, 12(1): 2412347. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Electric$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{di_franco_electric_2025,\n\ttitle = {Electric {Field} {Cycling} of {Physisorbed} {Antibodies} {Reduces} {Biolayer} {Polarization} {Dispersion}},\n\tvolume = {12},\n\tissn = {2198-3844, 2198-3844},\n\turl = {https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.202412347},\n\tdoi = {10.1002/advs.202412347},\n\tabstract = {Abstract\n            The electric dipoles of proteins in a biolayer determine their dielectric properties through the polarization density P. Hence, its reproducibility is crucial for applications, particularly in bioelectronics. Biolayers encompassing capturing antibodies covalently bound at a biosensing interface are generally preferred for their assumed higher stability. However, surface physisorption is shown to offer advantages like easily scalable fabrication processes and high stability. The present study investigates the effects of electric‐field (EF)‐cycling of anti‐Immunoglobulin M (anti‐IgM) biolayers physisorbed on Au. The impact of EF‐cycling on the dielectric, optical, and mechanical properties of anti‐IgM biolayer is investigated. A reduction of the dispersion (standard deviation over a set of 31 samples) of the measured P values is observed, while the set median stays almost constant. Hence, physisorption combined with EF cycling, results in a biolayer with highly reproducible bioelectronic properties. Additionally, the study provides important insights into the mechanisms of dielectric rearrangement of dipole moments in capturing biolayers after EF‐cycling. Notably, EF‐cycling acts as an annealing process, driving the proteins in the biolayer into a statistically more probable and stable conformational state. Understanding these phenomena enhances the knowledge of the properties of physisorbed biolayers and can inform design strategies for bioelectronic devices.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-03-20},\n\tjournal = {Advanced Science},\n\tauthor = {Di Franco, Cinzia and Macchia, Eleonora and Catacchio, Michele and Caputo, Mariapia and Scandurra, Cecilia and Sarcina, Lucia and Bollella, Paolo and Tricase, Angelo and Innocenti, Massimo and Funari, Riccardo and Piscitelli, Matteo and Scamarcio, Gaetano and Torsi, Luisa},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {2412347},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Piercing the Shadows: Exploring the Influence of Signal Preprocessing on Interpreting Ultrasensitive Bioelectronic Sensor Data.\n \n \n \n \n\n\n \n Caputo, M.; Sarcina, L.; Scandurra, C.; Catacchio, M.; Piscitelli, M.; Franco, C. D.; Bollella, P.; Scamarcio, G.; Torsi, L.; and Macchia, E.\n\n\n \n\n\n\n ChemPlusChem, 90(2): e202400520. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Piercing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{caputo_piercing_2025,\n\ttitle = {Piercing the {Shadows}: {Exploring} the {Influence} of {Signal} {Preprocessing} on {Interpreting} {Ultrasensitive} {Bioelectronic} {Sensor} {Data}},\n\tvolume = {90},\n\tissn = {2192-6506, 2192-6506},\n\tshorttitle = {Piercing the {Shadows}},\n\turl = {https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cplu.202400520},\n\tdoi = {10.1002/cplu.202400520},\n\tabstract = {Abstract\n            The development of ultrasensitive electronic sensors for in vitro diagnostics is essential for the reliable monitoring of asymptomatic individuals before illness proliferation or progression. These platforms are increasingly valued for their potential to enable timely diagnosis and swift prognosis of infectious or progressive diseases. Typically, the responses from these analytical tools are recorded as digital signals, with electronic data offering simpler processing compared to spectral and optical data. However, preprocessing electronic data from potentiometric biosensor arrays is still in its infancy compared to more established optical technologies. This study utilized the Single‐Molecule with a Large Transistor (SiMoT) array, which has achieved a Technology Readiness Level of 5, to explore the impact of data preprocessing on electronic biosensor outcomes. A dataset consisting of plasma and cyst fluid samples from 37 patients with pancreatic precursor cyst lesions was analyzed. The findings revealed that standard signal preprocessing can produce misleading conclusions due to artifacts introduced by mathematical transformations. The study offers strategies to mitigate these effects, ensuring that data interpretation remains accurate and reflective of the underlying biochemical information in the samples.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2025-03-20},\n\tjournal = {ChemPlusChem},\n\tauthor = {Caputo, Mariapia and Sarcina, Lucia and Scandurra, Cecilia and Catacchio, Michele and Piscitelli, Matteo and Franco, Cinzia Di and Bollella, Paolo and Scamarcio, Gaetano and Torsi, Luisa and Macchia, Eleonora},\n\tmonth = feb,\n\tyear = {2025},\n\tkeywords = {SP3},\n\tpages = {e202400520},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Umbrella Review of Systematic Reviews and Meta-Analyses on the Consumption of Different Food Groups and the Risk of Overweight and Obesity.\n \n \n \n \n\n\n \n Kristoffersen, E.; Hjort, S. L.; Thomassen, L. M.; Arjmand, E. J.; Perillo, M.; Balakrishna, R.; Onni, A. T.; Sletten, I. S. K.; Lorenzini, A.; and Fadnes, L. T.\n\n\n \n\n\n\n Nutrients, 17(4): 662. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Umbrella$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{kristoffersen_umbrella_2025,\n\ttitle = {Umbrella {Review} of {Systematic} {Reviews} and {Meta}-{Analyses} on the {Consumption} of {Different} {Food} {Groups} and the {Risk} of {Overweight} and {Obesity}},\n\tvolume = {17},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2072-6643},\n\turl = {https://www.mdpi.com/2072-6643/17/4/662},\n\tdoi = {10.3390/nu17040662},\n\tabstract = {Background/Objectives: Dietary choices play an essential role in energy balance and weight gain. This systematic umbrella review investigates the association between the intake of various food groups (whole grains, refined grains, fruits, vegetables, nuts, legumes, fish, eggs, total dairy, red meat, white meat, processed meat, added sugar, and sugar-sweetened beverages) and their associations to the risk of obesity and being overweight. Methods: We systematically searched Medline, Embase, Web of Science, and Epistemonikos for systematic reviews and meta-analyses. A total of 2925 articles were screened, and 13 articles were included in our analysis. Results: For each food group, data included a mean of 166,100 participants and 36,760 cases, ranging from 19,885 participants and 7183 cases for red meat to 520,331 participants and 91,256 cases for nuts. Heterogeneity was high for most of the food groups except for whole grains and sugar-sweetened beverages. The quality of the most comprehensive meta-analyses was high for all food groups, except for processed meats, which was of low quality. High intakes of whole grains, legumes, nuts, and fruits are associated with a reduced risk of overweight and obesity. In contrast, high intakes of red meat and sugar-sweetened beverages are associated with increased risk of overweight and obesity. No significant results were found for the remaining food groups, and no meta-analysis was found for fish, eggs, white meat, and added sugars. Conclusions: Diets rich in whole grains, legumes, nuts, and fruits are associated with a lower risk of developing obesity and being overweight. In contrast, diets high in red meat and sugar-sweetened beverages are associated with an increased risk of overweight and obesity.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-03-20},\n\tjournal = {Nutrients},\n\tauthor = {Kristoffersen, Emilie and Hjort, Sofie Lassen and Thomassen, Lise M. and Arjmand, Elaheh Javadi and Perillo, Matteo and Balakrishna, Rajiv and Onni, Anindita Tasnim and Sletten, Ida Sofie Karlsen and Lorenzini, Antonello and Fadnes, Lars T.},\n\tmonth = feb,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {662},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Forecasting migraine attacks by managing daily lifestyle: a systematic review as a basis to develop predictive algorithms.\n \n \n \n \n\n\n \n Quartetti, U.; Brighina, F.; Gambino, G.; Frinchi, M.; Bellafiore, M.; Tabacchi, G.; Vasto, S.; Accardi, G.; Amato, A.; Giardina, M.; Mazzucco, W.; Boffetta, P.; Giglia, G.; and Di Liberto, V.\n\n\n \n\n\n\n PAIN Reports, 10(2): e1247. April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Forecasting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{quartetti_forecasting_2025,\n\ttitle = {Forecasting migraine attacks by managing daily lifestyle: a systematic review as a basis to develop predictive algorithms},\n\tvolume = {10},\n\tissn = {2471-2531},\n\tshorttitle = {Forecasting migraine attacks by managing daily lifestyle},\n\turl = {https://journals.lww.com/10.1097/PR9.0000000000001247},\n\tdoi = {10.1097/PR9.0000000000001247},\n\tabstract = {Abstract\n            Recent studies attempting to develop forecasting models for new migraine attack onsets, overviewing triggers and protectors, are encouraging but necessitate further improvements to produce forecasting models with high predictive accuracy. This updated review of available data holds the potential to enhance the precision of predicting a migraine attack. This study aims to evaluate how lifestyle factors affect migraine frequency in adults with episodic migraine, to contribute to the development of an effective migraine forecasting model. A comprehensive search of databases, including PubMed, ScienceDirect, Google Scholar, and Scopus, was conducted considering studies published from 2018 to December 2023, following the PRISMA guidelines. Critical evaluation was conducted using the Joanna Briggs Institute's appraisal tools. The lifestyle modifications examined in this review included dietary habits, physical activity, sleep, and stress management. Of the 36 studies analysed, which predominantly exhibited low to moderate bias, 18 investigated dietary habits, 7 explored physical activity, 11 assessed stress management, and 5 investigated sleep patterns. The evidence from these 36 studies advocates for the implementation of lifestyle modifications in migraine management. Furthermore, these outcomes carry valuable implications from the standpoint of migraine forecasting models. The most consistent results were observed in relation to specific diets, dietary supplements, and physical activity. Although trends were noted in stress management and sleep, further research is required to elucidate their influence on migraine frequency and their integration into a migraine forecasting model. This study is registered on PROSPERO (ID CRD42024511300).},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2025-03-20},\n\tjournal = {PAIN Reports},\n\tauthor = {Quartetti, Umberto and Brighina, Filippo and Gambino, Giuditta and Frinchi, Monica and Bellafiore, Marianna and Tabacchi, Garden and Vasto, Sonya and Accardi, Giulia and Amato, Antonella and Giardina, Marta and Mazzucco, Walter and Boffetta, Paolo and Giglia, Giuseppe and Di Liberto, Valentina},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {e1247},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Umbrella Review of Systematic Reviews and Meta-analyses on Consumption of Different Food Groups and Risk of All-cause Mortality.\n \n \n \n \n\n\n \n Onni, A. T.; Balakrishna, R.; Perillo, M.; Amato, M.; Javadi Arjmand, E.; Thomassen, L. M; Lorenzini, A.; and Fadnes, L. T\n\n\n \n\n\n\n Advances in Nutrition, 16(4): 100393. April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Umbrella$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{onni_umbrella_2025,\n\ttitle = {Umbrella {Review} of {Systematic} {Reviews} and {Meta}-analyses on {Consumption} of {Different} {Food} {Groups} and {Risk} of {All}-cause {Mortality}},\n\tvolume = {16},\n\tissn = {21618313},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2161831325000298},\n\tdoi = {10.1016/j.advnut.2025.100393},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-03-20},\n\tjournal = {Advances in Nutrition},\n\tauthor = {Onni, Anindita Tasnim and Balakrishna, Rajiv and Perillo, Matteo and Amato, Marco and Javadi Arjmand, Elaheh and Thomassen, Lise M and Lorenzini, Antonello and Fadnes, Lars T},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP2},\n\tpages = {100393},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Metrological evaluation of contactless sleep position recognition using an accelerometric smart bed and machine learning.\n \n \n \n \n\n\n \n Hoang, M. L.; Matrella, G.; and Ciampolini, P.\n\n\n \n\n\n\n Sensors and Actuators A: Physical, 385: 116309. April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Metrological$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{hoang_metrological_2025,\n\ttitle = {Metrological evaluation of contactless sleep position recognition using an accelerometric smart bed and machine learning},\n\tvolume = {385},\n\tissn = {09244247},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0924424725001153},\n\tdoi = {10.1016/j.sna.2025.116309},\n\tlanguage = {en},\n\turldate = {2025-03-20},\n\tjournal = {Sensors and Actuators A: Physical},\n\tauthor = {Hoang, Minh Long and Matrella, Guido and Ciampolini, Paolo},\n\tmonth = apr,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {116309},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Childhood BMI trajectories and sociodemographic factors in an Italian pediatric population.\n \n \n \n \n\n\n \n Batzella, E.; Gutierrez De Rubalcava Doblas, J.; Porcu, G.; Bressan, S.; Barbieri, E.; Giaquinto, C.; Cantarutti, A.; and Canova, C.\n\n\n \n\n\n\n Scientific Reports, 15(1): 3525. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Childhood$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{batzella_childhood_2025,\n\ttitle = {Childhood {BMI} trajectories and sociodemographic factors in an {Italian} pediatric population},\n\tvolume = {15},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/s41598-025-87997-3},\n\tdoi = {10.1038/s41598-025-87997-3},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-02-07},\n\tjournal = {Scientific Reports},\n\tauthor = {Batzella, Erich and Gutierrez De Rubalcava Doblas, Joaquin and Porcu, Gloria and Bressan, Silvia and Barbieri, Elisa and Giaquinto, Carlo and Cantarutti, Anna and Canova, Cristina},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP2, WP5},\n\tpages = {3525},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Towards real-world clinical data standardization: A modular FHIR-driven transformation pipeline to enhance semantic interoperability in healthcare.\n \n \n \n \n\n\n \n Marfoglia, A.; Nardini, F.; Arcobelli, V. A.; Moscato, S.; Mellone, S.; and Carbonaro, A.\n\n\n \n\n\n\n Computers in Biology and Medicine, 187: 109745. March 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{marfoglia_towards_2025,\n\ttitle = {Towards real-world clinical data standardization: {A} modular {FHIR}-driven transformation pipeline to enhance semantic interoperability in healthcare},\n\tvolume = {187},\n\tissn = {00104825},\n\tshorttitle = {Towards real-world clinical data standardization},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0010482525000952},\n\tdoi = {10.1016/j.compbiomed.2025.109745},\n\tlanguage = {en},\n\turldate = {2025-02-19},\n\tjournal = {Computers in Biology and Medicine},\n\tauthor = {Marfoglia, Alberto and Nardini, Filippo and Arcobelli, Valerio Antonio and Moscato, Serena and Mellone, Sabato and Carbonaro, Antonella},\n\tmonth = mar,\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n\tpages = {109745},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n The role of the circadian timing system in sarcopenia in old age: a scoping review.\n \n \n \n \n\n\n \n Palmese, F.; Druda, Y.; Del Toro, R.; Bedogni, G.; Domenicali, M.; and Silvani, A.\n\n\n \n\n\n\n European Geriatric Medicine. January 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{palmese_role_2025,\n\ttitle = {The role of the circadian timing system in sarcopenia in old age: a scoping review},\n\tissn = {1878-7657},\n\tshorttitle = {The role of the circadian timing system in sarcopenia in old age},\n\turl = {https://link.springer.com/10.1007/s41999-024-01129-0},\n\tdoi = {10.1007/s41999-024-01129-0},\n\tabstract = {Abstract \n             \n              Purpose \n              Sarcopenia is a progressive and generalized skeletal muscle disorder, involving the accelerated loss of skeletal muscle mass and function, associated with an increased probability of adverse outcomes including falls. The circadian timing system may be involved in molecular pathways leading to sarcopenia in older adults. We aimed to provide an updated and systematic map of the available evidence on the role of the circadian timing system in sarcopenia, specifically related to the aging process. \n             \n             \n              Methods \n              We developed a scoping review protocol following the PRISMA-ScR guidelines. Searches were conducted on PubMed, Scopus, Web of Science, \n             \n             \n              Results \n              We identified 373 papers from three online databases, screened 97 for full-text analysis. and selected 37 papers for inclusion. These papers included 17 primary research studies on human persons, focusing on cortisol and melatonin secretion, rest-activity rhythms, chrono-exercise, and chrono-dietary regimens, 9 primary research studies on animal models (mice, rats, fruit flies) focusing on direct expression measurement or mutations of core clock genes, and 11 narrative reviews. \n             \n             \n              Conclusion \n              While several reports supported the role of the circadian timing system in sarcopenia, specifically related to the aging process, the available evidence is fragmented and limited. The field is thus open to preclinical and clinical research that addresses the wide knowledge gaps in the available evidence, taking advantage of what has already been published to optimize and refine experimental and clinical protocols.},\n\tlanguage = {en},\n\turldate = {2025-02-14},\n\tjournal = {European Geriatric Medicine},\n\tauthor = {Palmese, Francesco and Druda, Ylenia and Del Toro, Rossella and Bedogni, Giorgio and Domenicali, Marco and Silvani, Alessandro},\n\tmonth = jan,\n\tyear = {2025},\n\tkeywords = {SP2, WP5},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Inside out: Exploring edible biocatalytic biosensors for health monitoring.\n \n \n \n \n\n\n \n Marchianò, V.; Tricase, A.; Cimino, A.; Cassano, B.; Catacchio, M.; Macchia, E.; Torsi, L.; and Bollella, P.\n\n\n \n\n\n\n Bioelectrochemistry, 161. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Inside$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{marchiano_inside_2025,\n\ttitle = {Inside out: {Exploring} edible biocatalytic biosensors for health monitoring},\n\tvolume = {161},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205395380&doi=10.1016%2fj.bioelechem.2024.108830&partnerID=40&md5=cf18f68d5a07360def00eb1b06f35367},\n\tdoi = {10.1016/j.bioelechem.2024.108830},\n\tjournal = {Bioelectrochemistry},\n\tauthor = {Marchianò, V. and Tricase, A. and Cimino, A. and Cassano, B. and Catacchio, M. and Macchia, E. and Torsi, L. and Bollella, P.},\n\tyear = {2025},\n\tkeywords = {SP3, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A protocol for trustworthy EEG decoding with neural networks.\n \n \n \n \n\n\n \n Borra, D.; Magosso, E.; and Ravanelli, M.\n\n\n \n\n\n\n Neural Networks, 182. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{borra_protocol_2025,\n\ttitle = {A protocol for trustworthy {EEG} decoding with neural networks},\n\tvolume = {182},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209086181&doi=10.1016%2fj.neunet.2024.106847&partnerID=40&md5=5bd4b708cfcf7d31eb2a0989a12a2402},\n\tdoi = {10.1016/j.neunet.2024.106847},\n\tjournal = {Neural Networks},\n\tauthor = {Borra, D. and Magosso, E. and Ravanelli, M.},\n\tyear = {2025},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n 2024\n \n \n (73)\n \n \n

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\n \n\n \n \n \n \n \n \n Diverting hepatic lipid fluxes with lifestyles revision and pharmacological interventions as a strategy to tackle steatotic liver disease (SLD) and hepatocellular carcinoma (HCC).\n \n \n \n \n\n\n \n Misceo, D.; Mocciaro, G.; D’Amore, S.; and Vacca, M.\n\n\n \n\n\n\n Nutrition and Metabolism, 21(1): 112. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Diverting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{misceo_diverting_2024,\n\ttitle = {Diverting hepatic lipid fluxes with lifestyles revision and pharmacological interventions as a strategy to tackle steatotic liver disease ({SLD}) and hepatocellular carcinoma ({HCC})},\n\tvolume = {21},\n\tissn = {1743-7075},\n\turl = {https://nutritionandmetabolism.biomedcentral.com/articles/10.1186/s12986-024-00871-3},\n\tdoi = {10.1186/s12986-024-00871-3},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-01-07},\n\tjournal = {Nutrition and Metabolism},\n\tauthor = {Misceo, Davide and Mocciaro, Gabriele and D’Amore, Simona and Vacca, Michele},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {112},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Exploring the relationship between cognition and symptomatology among patients with schizophrenia and individuals at risk for psychosis: a machine learning study.\n \n \n \n \n\n\n \n Rollo, S.; Raio, A.; Selvaggi, P.; Massari, F.; D'Ambrosio, E.; Quatraro, C.; Rampino, A.; Bertolino, A.; and Antonucci, L. A.\n\n\n \n\n\n\n In XXIV National Congress Italian Psychological Association Clinical and Dynamic Section, Salerno, 12nd – 15th September 2024, volume Vol 12, pages No 2 Suppl. (2024), September 2024. Mediterranean Journal of Clinical Psychology\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{rollo_exploring_2024,\n\ttitle = {Exploring the relationship between cognition and symptomatology among patients with schizophrenia and individuals at risk for psychosis: a machine learning study},\n\tvolume = {Vol 12},\n\turl = {https://cab.unime.it/journals/index.php/MJCP/article/view/4329},\n\tdoi = {10.13129/2282-1619/MJCP-4329},\n\tabstract = {Proceedings},\n\tlanguage = {en},\n\turldate = {2025-05-27},\n\tbooktitle = {{XXIV} {National} {Congress} {Italian} {Psychological} {Association} {Clinical} and {Dynamic} {Section}, {Salerno}, 12nd – 15th {September} 2024},\n\tpublisher = {Mediterranean Journal of Clinical Psychology},\n\tauthor = {Rollo, Simone and Raio, Alessandra and Selvaggi, Pierluigi and Massari, Francesco and D'Ambrosio, Enrico and Quatraro, Cristina and Rampino, Antonio and Bertolino, Alessandro and Antonucci, Linda Antonella},\n\tmonth = sep,\n\tyear = {2024},\n\tkeywords = {SP3},\n\tpages = {No 2 Suppl. (2024)},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Profiling the contribution of cognition and personality to psychosis proneness course in young adults via individual environmental loadings.\n \n \n \n \n\n\n \n Raio, A.; Wenzel, J.; Bertolino, A.; Kambeitz-Ilankovic, L.; Kambeitz, J.; and Pergola, G.\n\n\n \n\n\n\n In XXIV National Congress Italian Psychological Association Clinical and Dynamic Section, Salerno, 12nd – 15th September 2024, volume Vol 12, pages No 2 Suppl. (2024), September 2024. Mediterranean Journal of Clinical Psychology\n \n\n\n\n
\n\n\n\n \n \n $\"Profiling$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{raio_profiling_2024,\n\ttitle = {Profiling the contribution of cognition and personality to psychosis proneness course in young adults via individual environmental loadings},\n\tvolume = {Vol 12},\n\turl = {https://cab.unime.it/journals/index.php/MJCP/article/view/4329},\n\tdoi = {10.13129/2282-1619/MJCP-4329},\n\tabstract = {Proceedings},\n\tlanguage = {en},\n\turldate = {2025-05-27},\n\tbooktitle = {{XXIV} {National} {Congress} {Italian} {Psychological} {Association} {Clinical} and {Dynamic} {Section}, {Salerno}, 12nd – 15th {September} 2024},\n\tpublisher = {Mediterranean Journal of Clinical Psychology},\n\tauthor = {Raio, Alessandra and Wenzel, Julian and Bertolino, Alessandro and Kambeitz-Ilankovic, Lana and Kambeitz, Joseph and Pergola, Giulio},\n\tmonth = sep,\n\tyear = {2024},\n\tkeywords = {SP3},\n\tpages = {No 2 Suppl. (2024)},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Application of CBT-based protocols and techniques to psychological well-being promotion and risk for psychopathology prevention in real-life scenarios: promises and pitfalls.\n \n \n \n \n\n\n \n Antonucci, L.\n\n\n \n\n\n\n In XXIV National Congress Italian Psychological Association Clinical and Dynamic Section, Salerno, 12nd – 15th September 2024, volume Vol 12, pages No 2 Suppl. (2024), September 2024. Mediterranean Journal of Clinical Psychology\n \n\n\n\n
\n\n\n\n \n \n $\"Application$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@inproceedings{antonucci_application_2024,\n\ttitle = {Application of {CBT}-based protocols and techniques to psychological well-being promotion and risk for psychopathology prevention in real-life scenarios: promises and pitfalls},\n\tvolume = {Vol 12},\n\turl = {https://cab.unime.it/journals/index.php/MJCP/article/view/4329},\n\tdoi = {10.13129/2282-1619/MJCP-4329},\n\tabstract = {Proceedings},\n\tlanguage = {en},\n\turldate = {2025-05-27},\n\tbooktitle = {{XXIV} {National} {Congress} {Italian} {Psychological} {Association} {Clinical} and {Dynamic} {Section}, {Salerno}, 12nd – 15th {September} 2024},\n\tpublisher = {Mediterranean Journal of Clinical Psychology},\n\tauthor = {Antonucci, Linda},\n\tmonth = sep,\n\tyear = {2024},\n\tkeywords = {SP3},\n\tpages = {No 2 Suppl. (2024)},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Explainable Gait Analysis for Early Detection of Neurodegenerative Diseases Using Unsupervised Clustering Techniques.\n \n \n \n \n\n\n \n Dentamaro, V.; Franchini, F.; Massaro, I.; Musti, L.; Pirlo, G.; and Sblendorio, E.\n\n\n \n\n\n\n In 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pages 861–866, St Albans, United Kingdom, October 2024. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Explainable$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{dentamaro_explainable_2024,\n\taddress = {St Albans, United Kingdom},\n\ttitle = {Explainable {Gait} {Analysis} for {Early} {Detection} of {Neurodegenerative} {Diseases} {Using} {Unsupervised} {Clustering} {Techniques}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3503-7800-9},\n\turl = {https://ieeexplore.ieee.org/document/10796727/},\n\tdoi = {10.1109/MetroXRAINE62247.2024.10796727},\n\turldate = {2025-03-27},\n\tbooktitle = {2024 {IEEE} {International} {Conference} on {Metrology} for {eXtended} {Reality}, {Artificial} {Intelligence} and {Neural} {Engineering} ({MetroXRAINE})},\n\tpublisher = {IEEE},\n\tauthor = {Dentamaro, Vincenzo and Franchini, Felice and Massaro, Ignazio and Musti, Luca and Pirlo, Giuseppe and Sblendorio, Elena},\n\tmonth = oct,\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {861--866},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n An MLOps Approach for Deploying Machine Learning Models in Healthcare Systems.\n \n \n \n \n\n\n \n Mallardi, G.; Calefato, F.; Quaranta, L.; and Lanubile, F.\n\n\n \n\n\n\n In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 6832–6837, Lisbon, Portugal, December 2024. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{mallardi_mlops_2024,\n\taddress = {Lisbon, Portugal},\n\ttitle = {An {MLOps} {Approach} for {Deploying} {Machine} {Learning} {Models} in {Healthcare} {Systems}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {979-8-3503-8622-6},\n\turl = {https://ieeexplore.ieee.org/document/10822603/},\n\tdoi = {10.1109/BIBM62325.2024.10822603},\n\turldate = {2025-03-27},\n\tbooktitle = {2024 {IEEE} {International} {Conference} on {Bioinformatics} and {Biomedicine} ({BIBM})},\n\tpublisher = {IEEE},\n\tauthor = {Mallardi, Giulio and Calefato, Fabio and Quaranta, Luigi and Lanubile, Filippo},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {6832--6837},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Distorted insights from human mobility data.\n \n \n \n \n\n\n \n Gallotti, R.; Maniscalco, D.; Barthelemy, M.; and De Domenico, M.\n\n\n \n\n\n\n Communications Physics, 7(1): 421. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Distorted$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{gallotti_distorted_2024,\n\ttitle = {Distorted insights from human mobility data},\n\tvolume = {7},\n\tissn = {2399-3650},\n\turl = {https://www.nature.com/articles/s42005-024-01909-x},\n\tdoi = {10.1038/s42005-024-01909-x},\n\tabstract = {Abstract\n            The description of human mobility is at the core of many fundamental applications ranging from urbanism and transportation to epidemics containment. Data about human movements, once scarce, is now widely available thanks to new sources such as phone call detail records, GPS devices, or Smartphone apps. Nevertheless, it is still common to rely on a single dataset by implicitly assuming that the statistical properties observed are robust regardless of data gathering and processing techniques. Here, we test this assumption on a broad scale by comparing human mobility datasets obtained from 7 different data-sources, tracing 500+ millions individuals in 145 countries. We report wide quantifiable differences in the resulting mobility networks and in the displacement distribution. These variations impact processes taking place on these networks like epidemic spreading. Our results point to the need for disclosing the data processing and, overall, to follow good practices to ensure robust and reproducible results.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-03-20},\n\tjournal = {Communications Physics},\n\tauthor = {Gallotti, Riccardo and Maniscalco, Davide and Barthelemy, Marc and De Domenico, Manlio},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP2},\n\tpages = {421},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Two-year follow-up after drug desensitization in mucopolysaccharidosis.\n \n \n \n \n\n\n \n Spataro, F.; Ria, R.; Chaoul, N.; Solimando, A. G.; Desantis, V.; Vacca, A.; Di Bona, D.; Girolamo, A. D.; and Macchia, L.\n\n\n \n\n\n\n Orphanet Journal of Rare Diseases, 19(1): 491. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Two-year$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

@article{spataro_two-year_2024,\n\ttitle = {Two-year follow-up after drug desensitization in mucopolysaccharidosis},\n\tvolume = {19},\n\tissn = {1750-1172},\n\turl = {https://ojrd.biomedcentral.com/articles/10.1186/s13023-024-03516-z},\n\tdoi = {10.1186/s13023-024-03516-z},\n\tabstract = {Abstract\n            \n              Background\n              Mucopolysaccharidosis (MPS) type 1 S and type 2 are rare lysosomal storage disorders characterized by impaired enzyme production, resulting in glycosaminoglycans accumulation within lysosomes. Enzyme Replacement Therapy (ERT) with laronidase and idursulfase are first line treatments, respectively. However, infusion-related hypersensitivity reactions (HR) may lead to ERT discontinuation. Thus, desensitization can be performed to restore ERT.\n            \n            \n              Methods\n              We report on a two-year follow-up after a combined desensitization approach in two MPS patients experiencing HR to ERT. This approach consists of intravenous rapid desensitization combined with the subcutaneous allergen immunotherapy-like desensitization with the culprit recombinant enzyme.\n            \n            \n              Results\n              The first patient, suffering from MPS type I, underwent to the combined desensitization approach, and subsequently tolerated weekly standard laronidase infusions for 13 months when HR occurred again. Then, a monthly omalizumab (anti-IgE monoclonal antibody) administration was implemented allowing the patient to restore ERT. The second patient, diagnosed with MPS type 2, was subjected to a similar combined desensitization strategy with idursulfase, and achieved a total desensitization after one year, confirmed by negative skin tests. Thus, he continued standard ERT infusions without HR occurrence.\n            \n            \n              Conclusion\n              The combined desensitization approach proved effective in conferring immunotolerance for at least one year in both MPS patients, also demonstrated by the negative skin tests in one patient. However, when immunotolerance to ERT is lost, omalizumab administration can be a valid option in restoring ERT.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-03-20},\n\tjournal = {Orphanet Journal of Rare Diseases},\n\tauthor = {Spataro, Federico and Ria, Roberto and Chaoul, Nada and Solimando, Antonio Giovanni and Desantis, Vanessa and Vacca, Angelo and Di Bona, Danilo and Girolamo, Attilio Di and Macchia, Luigi},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP3},\n\tpages = {491},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Selective inference for fMRI cluster-wise analysis, issues, and recommendations for critical vector selection: A comment on Blain et al.\n \n \n \n \n\n\n \n Andreella, A.; Vesely, A.; Weeda, W.; and Goeman, J.\n\n\n \n\n\n\n Imaging Neuroscience, 2: 1–7. June 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Selective$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{andreella_selective_2024,\n\ttitle = {Selective inference for {fMRI} cluster-wise analysis, issues, and recommendations for critical vector selection: {A} comment on {Blain} et al.},\n\tvolume = {2},\n\tissn = {2837-6056},\n\tshorttitle = {Selective inference for {fMRI} cluster-wise analysis, issues, and recommendations for critical vector selection},\n\turl = {https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00198/121547/Selective-inference-for-fMRI-cluster-wise-analysis},\n\tdoi = {10.1162/imag_a_00198},\n\tabstract = {Abstract \n            Two permutation-based methods for simultaneous inference on the proportion of active voxels in cluster-wise brain imaging analysis have recently been published: Notip and pARI. Both rely on the definition of a critical vector of ordered p-values, chosen from a family of candidate vectors, but differ in how the family is defined: computed from randomization of external data for Notip and determined a priori for pARI. These procedures were compared to other proposals in the literature, but an extensive comparison between the two methods is missing due to their parallel publication. We provide such a comparison and find that pARI outperforms Notip if both methods are applied under their recommended settings. However, each method carries different advantages and drawbacks.},\n\tlanguage = {en},\n\turldate = {2025-02-27},\n\tjournal = {Imaging Neuroscience},\n\tauthor = {Andreella, Angela and Vesely, Anna and Weeda, Wouter and Goeman, Jelle},\n\tmonth = jun,\n\tyear = {2024},\n\tkeywords = {SP2, WP3},\n\tpages = {1--7},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Generalized Lotka-Volterra Systems with Time Correlated Stochastic Interactions.\n \n \n \n \n\n\n \n Suweis, S.; Ferraro, F.; Grilletta, C.; Azaele, S.; and Maritan, A.\n\n\n \n\n\n\n Physical Review Letters, 133(16). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Generalized$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{suweis_generalized_2024,\n\ttitle = {Generalized {Lotka}-{Volterra} {Systems} with {Time} {Correlated} {Stochastic} {Interactions}},\n\tvolume = {133},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207793169&doi=10.1103%2fPhysRevLett.133.167101&partnerID=40&md5=2776c33d440e11449334f67f4257d3e6},\n\tdoi = {10.1103/PhysRevLett.133.167101},\n\tnumber = {16},\n\tjournal = {Physical Review Letters},\n\tauthor = {Suweis, S. and Ferraro, F. and Grilletta, C. and Azaele, S. and Maritan, A.},\n\tyear = {2024},\n\tkeywords = {SP2, WP5},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Emergent ecological patterns and modelling of gut microbiomes in health and in disease.\n \n \n \n \n\n\n \n Pasqualini, J.; Facchin, S.; Rinaldo, A.; Maritan, A.; Savarino, E.; and Suweis, S.\n\n\n \n\n\n\n PLoS Computational Biology, 20(9). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Emergent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{pasqualini_emergent_2024,\n\ttitle = {Emergent ecological patterns and modelling of gut microbiomes in health and in disease},\n\tvolume = {20},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205146644&doi=10.1371%2fjournal.pcbi.1012482&partnerID=40&md5=eea6d7af30f8fd499c2222373052137e},\n\tdoi = {10.1371/journal.pcbi.1012482},\n\tnumber = {9},\n\tjournal = {PLoS Computational Biology},\n\tauthor = {Pasqualini, J. and Facchin, S. and Rinaldo, A. and Maritan, A. and Savarino, E. and Suweis, S.},\n\tyear = {2024},\n\tkeywords = {SP2, WP5},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Wearable sensors for monitoring caregivers of people with dementia: a scoping review.\n \n \n \n \n\n\n \n Palmese, F.; Druda, Y.; Benintende, V.; Fuda, D.; Sicbaldi, M.; Di Florio, P.; Butt, A.; Bedogni, G.; Chiari, L.; Silvani, A.; and Domenicali, M.\n\n\n \n\n\n\n European Geriatric Medicine. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Wearable$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{palmese_wearable_2024,\n\ttitle = {Wearable sensors for monitoring caregivers of people with dementia: a scoping review},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211780999&doi=10.1007%2fs41999-024-01113-8&partnerID=40&md5=c900a60d24a5a26c4ffb13eef29fded2},\n\tdoi = {10.1007/s41999-024-01113-8},\n\tjournal = {European Geriatric Medicine},\n\tauthor = {Palmese, F. and Druda, Y. and Benintende, V. and Fuda, D. and Sicbaldi, M. and Di Florio, P. and Butt, A.H. and Bedogni, G. and Chiari, L. and Silvani, A. and Domenicali, M.},\n\tyear = {2024},\n\tkeywords = {SP2, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Association Between Early-Life Exposure to Antibiotics and Development of Child Obesity: Population-Based Study in Italy.\n \n \n \n \n\n\n \n Cantarutti, A.; Rescigno, P.; Da Borso, C.; Gutierrez De Rubalcava Doblas, J.; Bressan, S.; Barbieri, E.; Giaquinto, C.; and Canova, C.\n\n\n \n\n\n\n JMIR Public Health and Surveillance, 10: e51734. May 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Association$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{cantarutti_association_2024,\n\ttitle = {Association {Between} {Early}-{Life} {Exposure} to {Antibiotics} and {Development} of {Child} {Obesity}: {Population}-{Based} {Study} in {Italy}},\n\tvolume = {10},\n\tissn = {2369-2960},\n\tshorttitle = {Association {Between} {Early}-{Life} {Exposure} to {Antibiotics} and {Development} of {Child} {Obesity}},\n\turl = {https://publichealth.jmir.org/2024/1/e51734},\n\tdoi = {10.2196/51734},\n\tabstract = {Background\n              Childhood obesity is a significant public health problem representing the most severe challenge in the world. Antibiotic exposure in early life has been identified as a potential factor that can disrupt the development of the gut microbiome, which may have implications for obesity.\n            \n            \n              Objective\n              This study aims to evaluate the risk of developing obesity among children exposed to antibiotics early in life.\n            \n            \n              Methods\n              An Italian retrospective pediatric population-based cohort study of children born between 2004 and 2018 was adopted using the Pedianet database. Children were required to be born at term, with normal weight, and without genetic diseases or congenital anomalies. We assessed the timing of the first antibiotic prescription from birth to 6, 12, and 24 months of life and the dose-response relationship via the number of antibiotic prescriptions recorded in the first year of life (none, 1, 2, and ≥3 prescriptions). Obesity was defined as a BMI z score {\\textgreater}3 for children aged ≤5 years and {\\textgreater}2 for children aged {\\textgreater}5 years, using the World Health Organization growth references. The obese incidence rate (IR) × 100 person-years and the relative 95\\% CI were computed using infant sex, area of residence, preschool and school age, and area deprivation index, which are the covariates of interest. A mixed-effect Cox proportional hazards model was used to estimate the hazard ratio and 95\\% CI for the association between antibiotic exposure in early life and child obesity between 24 months and 14 years of age, considering the family pediatricians as a random factor. Several subgroup and sensitivity analyses were performed to assess the robustness of our results.\n            \n            \n              Results\n              Among 121,540 children identified, 54,698 were prescribed at least an antibiotic within the first year of life and 26,990 were classified as obese during follow-up with an incidence rate of 4.05 cases (95\\% CI 4.01-4.10) × 100 person-year. The risk of obesity remained consistent across different timings of antibiotic prescriptions at 6 months, 1 year, and 2 years (fully adjusted hazard ratio [aHR] 1.07, 95\\% CI 1.04-1.10; aHR 1.06, 95\\% CI 1.03-1.09; and aHR 1.07, 95\\% CI 1.04-1.10, respectively). Increasing the number of antibiotic exposures increases the risk of obesity significantly (P trend{\\textless}.001). The individual-specific age analysis showed that starting antibiotic therapy very early (between 0 and 5 months) had the greatest impact (aHR 1.12, 95\\% CI 1.08-1.17) on childhood obesity with respect to what was observed among those who were first prescribed antibiotics after the fifth month of life. These results were consistent across subgroup and sensitivity analyses.\n            \n            \n              Conclusions\n              The results from this large population-based study support the association between early exposure to antibiotics and an increased risk of childhood obesity. This association becomes progressively stronger with both increasing numbers of antibiotic prescriptions and younger age at the time of the first prescription.},\n\tlanguage = {en},\n\turldate = {2024-10-03},\n\tjournal = {JMIR Public Health and Surveillance},\n\tauthor = {Cantarutti, Anna and Rescigno, Paola and Da Borso, Claudia and Gutierrez De Rubalcava Doblas, Joaquin and Bressan, Silvia and Barbieri, Elisa and Giaquinto, Carlo and Canova, Cristina},\n\tmonth = may,\n\tyear = {2024},\n\tkeywords = {SP2, WP5},\n\tpages = {e51734},\n}\n\n\n\n

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\n Background Childhood obesity is a significant public health problem representing the most severe challenge in the world. Antibiotic exposure in early life has been identified as a potential factor that can disrupt the development of the gut microbiome, which may have implications for obesity. Objective This study aims to evaluate the risk of developing obesity among children exposed to antibiotics early in life. Methods An Italian retrospective pediatric population-based cohort study of children born between 2004 and 2018 was adopted using the Pedianet database. Children were required to be born at term, with normal weight, and without genetic diseases or congenital anomalies. We assessed the timing of the first antibiotic prescription from birth to 6, 12, and 24 months of life and the dose-response relationship via the number of antibiotic prescriptions recorded in the first year of life (none, 1, 2, and ≥3 prescriptions). Obesity was defined as a BMI z score \\textgreater3 for children aged ≤5 years and \\textgreater2 for children aged \\textgreater5 years, using the World Health Organization growth references. The obese incidence rate (IR) × 100 person-years and the relative 95% CI were computed using infant sex, area of residence, preschool and school age, and area deprivation index, which are the covariates of interest. A mixed-effect Cox proportional hazards model was used to estimate the hazard ratio and 95% CI for the association between antibiotic exposure in early life and child obesity between 24 months and 14 years of age, considering the family pediatricians as a random factor. Several subgroup and sensitivity analyses were performed to assess the robustness of our results. Results Among 121,540 children identified, 54,698 were prescribed at least an antibiotic within the first year of life and 26,990 were classified as obese during follow-up with an incidence rate of 4.05 cases (95% CI 4.01-4.10) × 100 person-year. The risk of obesity remained consistent across different timings of antibiotic prescriptions at 6 months, 1 year, and 2 years (fully adjusted hazard ratio [aHR] 1.07, 95% CI 1.04-1.10; aHR 1.06, 95% CI 1.03-1.09; and aHR 1.07, 95% CI 1.04-1.10, respectively). Increasing the number of antibiotic exposures increases the risk of obesity significantly (P trend\\textless.001). The individual-specific age analysis showed that starting antibiotic therapy very early (between 0 and 5 months) had the greatest impact (aHR 1.12, 95% CI 1.08-1.17) on childhood obesity with respect to what was observed among those who were first prescribed antibiotics after the fifth month of life. These results were consistent across subgroup and sensitivity analyses. Conclusions The results from this large population-based study support the association between early exposure to antibiotics and an increased risk of childhood obesity. This association becomes progressively stronger with both increasing numbers of antibiotic prescriptions and younger age at the time of the first prescription.\n

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\n \n\n \n \n \n \n \n \n Factors Associated with Primary Liver Cancer Survival in a Southern Italian Setting in a Changing Epidemiological Scenario.\n \n \n \n \n\n\n \n Mazzola, S.; Vittorietti, M.; Fruscione, S.; De Bella, D.; Savatteri, A.; Belluzzo, M.; Ginevra, D.; Gioia, A.; Costanza, D.; Castellone, M.; Costantino, C.; Zarcone, M.; Ravazzolo, B.; Graziano, G.; Mannino, R.; Amodio, R.; Di Marco, V.; Vitale, F.; and Mazzucco, W.\n\n\n \n\n\n\n Cancers, 16(11). 2024.\n Number: 11\n\n\n\n
\n\n\n\n \n \n $\"Factors$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{mazzola_factors_2024,\n\ttitle = {Factors {Associated} with {Primary} {Liver} {Cancer} {Survival} in a {Southern} {Italian} {Setting} in a {Changing} {Epidemiological} {Scenario}},\n\tvolume = {16},\n\tissn = {20726694 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195798441&doi=10.3390%2fcancers16112046&partnerID=40&md5=8556472345cbcb195957387d87aacbca},\n\tdoi = {10.3390/cancers16112046},\n\tabstract = {A retrospective observational study utilising cancer incidence data from a population-based registry investigated determinants affecting primary liver cancer survival in a southern Italian region with high hepatitis viral infection rates and obesity prevalence. Among 2687 patients diagnosed between 2006 and 2019 (65.3\\% male), a flexible hazard-based regression model revealed factors influencing 5-year survival rates. High deprivation levels [HR = 1.41 (95\\%CI = 1.15–1.76); p {\\textless} 0.001], poor access to care [HR = 1.99 (95\\%IC = 1.70–2.35); p {\\textless} 0.0001], age between 65 and 75 [HR = 1.48 (95\\%IC = 1.09–2.01); p {\\textless} 0.05] or {\\textgreater}75 [HR = 2.21 (95\\%CI = 1.62–3.01); p {\\textless} 0.0001] and residing in non-urban areas [HR = 1.35 (95\\%CI = 1.08–1.69); p {\\textless} 0.01] were associated with poorer survival estimates. While deprivation appeared to be a risk factor for primary liver cancer patients residing within the urban area, the geographic distance from specialised treatment centres emerged as a potential determinant of lower survival estimates for residents in the non-urban areas. After balancing the groups of easy and poor access to care using a propensity score approach, poor access to care and a lower socioeconomic status resulted in potentially having a negative impact on primary liver cancer survival, particularly among urban residents. We emphasise the need to interoperate cancer registries with other data sources and to deploy innovative digital solutions to improve cancer prevention. © 2024 by the authors.},\n\tlanguage = {English},\n\tnumber = {11},\n\tjournal = {Cancers},\n\tpublisher = {Multidisciplinary Digital Publishing Institute (MDPI)},\n\tauthor = {Mazzola, S. and Vittorietti, M. and Fruscione, S. and De Bella, D.D. and Savatteri, A. and Belluzzo, M. and Ginevra, D. and Gioia, A. and Costanza, D. and Castellone, M.D. and Costantino, C. and Zarcone, M. and Ravazzolo, B. and Graziano, G. and Mannino, R. and Amodio, R. and Di Marco, V. and Vitale, F. and Mazzucco, W.},\n\tyear = {2024},\n\tnote = {Number: 11},\n\tkeywords = {Article, ICD-O-3, SP2, WP2, access to care, adult, aged, cancer incidence, cancer prevention, cancer registries, cancer survival, controlled study, digital prevention, epidemiology, female, health services, human, liver cancer, major clinical study, male, obesity, observational study, propensity score, retrospective study, risk factor, social status, socioeconomics, survival, urban area, virus infection},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n “Picture this from there”: spatial perspective-taking in developmental visuospatial disorder and developmental coordination disorder.\n \n \n \n \n\n\n \n Orefice, C.; Cardillo, R.; Lonciari, I.; Zoccante, L.; and Mammarella, I.\n\n\n \n\n\n\n Frontiers in Psychology, 15. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"“Picture$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{orefice_picture_2024,\n\ttitle = {“{Picture} this from there”: spatial perspective-taking in developmental visuospatial disorder and developmental coordination disorder},\n\tvolume = {15},\n\tissn = {16641078 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192084371&doi=10.3389%2ffpsyg.2024.1349851&partnerID=40&md5=cae7eb2ba6c613bd3efbd619b9ce1607},\n\tdoi = {10.3389/fpsyg.2024.1349851},\n\tabstract = {Introduction: Either Developmental Visuospatial Disorder (DVSD) and Developmental Coordination Disorder (DCD) present with difficulties in visuospatial processing, even though entailing different degrees of impairment. Among the visuospatial domain, spatial perspective taking is essential to interact with the environment and is significantly involved in many daily activities (e.g., environment navigation and spatial orienting). Notwithstanding, no previous studies have investigated this spatial domain in children with DVSD and limited evidence is available regarding DCD. Consistent with a transdiagnostic approach, the first goal of the present study was to compare spatial perspective taking abilities of these groups, also including a control group of not diagnosed peers (ND). Secondly, the role of different fine-motor and visuo-spatial predictors on the spatial perspective taking performance was considered. Method: A total of 85 participants (DVSD = 26; DCD = 26; ND = 33), aged between 8 and 16 years old, were included in the study. Tasks assessing spatial perspective taking, fine-motor, visual imagery, and mental rotation skills, as well as visuo-spatial working memory were administered. Results and Discussion: Overall, our results confirmed weaknesses in spatial perspective taking in both clinical groups, with the DVSD obtaining the lowest scores. Similarities and differences in the predictors accounting for the performance in the spatial perspective taking task emerged, suggesting the possible employment of different fine-motor or visuospatial strategies by group. Findings are discussed considering the potential impact they may have both in research and clinical practice. Copyright © 2024 Orefice, Cardillo, Lonciari, Zoccante and Mammarella.},\n\tlanguage = {English},\n\tjournal = {Frontiers in Psychology},\n\tpublisher = {Frontiers Media SA},\n\tauthor = {Orefice, C. and Cardillo, R. and Lonciari, I. and Zoccante, L. and Mammarella, I.C.},\n\tyear = {2024},\n\tkeywords = {SP2, WP5, developmental coordination disorder, developmental visuospatial disorder, fine-motor skills, visuospatial perspective-taking, visuospatial processing},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n An integrated pathway for influenza vaccination across primary and secondary care using a clinical decision support system: model definition and predictive impact analysis.\n \n \n \n \n\n\n \n Specchia, M. L.; Beccia, F.; Cacciuttolo, M. G.; Tona, D. M.; Di Pumpo, M.; Porcelli, M.; Lontano, A.; Corona, V. F.; Laurenti, P.; Boccia, S.; and Pastorino, R.\n\n\n \n\n\n\n European Journal of Public Health, 34(6): 1117–1124. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{specchia_integrated_2024,\n\ttitle = {An integrated pathway for influenza vaccination across primary and secondary care using a clinical decision support system: model definition and predictive impact analysis},\n\tvolume = {34},\n\tcopyright = {https://creativecommons.org/licenses/by-nc/4.0/},\n\tissn = {1101-1262, 1464-360X},\n\tshorttitle = {An integrated pathway for influenza vaccination across primary and secondary care using a clinical decision support system},\n\turl = {https://academic.oup.com/eurpub/article/34/6/1117/7758786},\n\tdoi = {10.1093/eurpub/ckae137},\n\tabstract = {Abstract\n            Influenza is an important public health issue given its significant burden of disease. In Italy, the unsatisfactory coverage rate in people ≥65 years underlines the need to improve the current vaccination pathway. This study aims to define an integrated pathway across primary and secondary care, facilitated by a digital clinical decision support system (CDSS), to enhance vaccination coverage in people ≥65 years by actively recruiting patients in hospitals and administering vaccination. Moreover, the study seeks to gauge the potential epidemiological and economic impact of this approach. The methodology consisted of two main phases: definition of the integrated pathway and CDSS and estimation of the potential epidemiological and economic impact resulting from the implementation of the pathway in the whole Lazio region. Assuming an increase of influenza vaccination coverage from the current rate of 60\\% to 65\\% in ≥65 years old population in the Lazio region thanks to the pathway implementation, an increase of 8\\% in avoided influenza cases, avoided influenza- or pneumonia-related hospitalizations and avoided influenza-related outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatient visits of up to 11.85\\%. Setting the vaccination coverage at 70\\%, the impact is doubled. Alongside offering a predictive estimate of the pathway’s potential impact, both epidemiological and economic, this project, with its robust methodology, may serve as a scalable and transferable model for enhancing vaccination coverage at national and international level.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2025-01-31},\n\tjournal = {European Journal of Public Health},\n\tauthor = {Specchia, Maria Lucia and Beccia, Flavia and Cacciuttolo, Maria Gabriella and Tona, Diego Maria and Di Pumpo, Matteo and Porcelli, Martina and Lontano, Alberto and Corona, Valerio Flavio and Laurenti, Patrizia and Boccia, Stefania and Pastorino, Roberta},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP2, WP4},\n\tpages = {1117--1124},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n LAWSUIT: a LArge expert-Written SUmmarization dataset of ITalian constitutional court verdicts.\n \n \n \n \n\n\n \n Ragazzi, L.; Moro, G.; Guidi, S.; and Frisoni, G.\n\n\n \n\n\n\n Artificial Intelligence and Law. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"LAWSUIT:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{ragazzi_lawsuit_2024,\n\ttitle = {{LAWSUIT}: a {LArge} expert-{Written} {SUmmarization} dataset of {ITalian} constitutional court verdicts},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203380648&doi=10.1007%2fs10506-024-09414-w&partnerID=40&md5=8b03d8f4b5c71487d911e00cec75a851},\n\tdoi = {10.1007/s10506-024-09414-w},\n\tjournal = {Artificial Intelligence and Law},\n\tauthor = {Ragazzi, L. and Moro, G. and Guidi, S. and Frisoni, G.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Exploring Intra-Articular Administration of Monoclonal Antibodies as a Novel Approach to Osteoarthritis Treatment: A Systematic Review.\n \n \n \n \n\n\n \n Smakaj, A.; Gasbarra, E.; Cardelli, T.; Salvati, C.; Bonanni, R.; Cariati, I.; Iundusi, R.; and Tarantino, U.\n\n\n \n\n\n\n Biomedicines, 12(10). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{smakaj_exploring_2024,\n\ttitle = {Exploring {Intra}-{Articular} {Administration} of {Monoclonal} {Antibodies} as a {Novel} {Approach} to {Osteoarthritis} {Treatment}: {A} {Systematic} {Review}},\n\tvolume = {12},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207686766&doi=10.3390%2fbiomedicines12102217&partnerID=40&md5=5a33af72a7e3ce2b3c48996e57bcd07d},\n\tdoi = {10.3390/biomedicines12102217},\n\tnumber = {10},\n\tjournal = {Biomedicines},\n\tauthor = {Smakaj, A. and Gasbarra, E. and Cardelli, T. and Salvati, C. and Bonanni, R. and Cariati, I. and Iundusi, R. and Tarantino, U.},\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Ruminative thinking mediates the effects of exposure to adverse life events on psychotic-like experiences.\n \n \n \n \n\n\n \n Fazio, L.; Raio, A.; Banaschewski, T.; Bokde, A. L. W.; Desrivières, S.; Flor, H.; Garavan, H.; Gowland, P.; Grigis, A.; Heinz, A.; Martinot, J.; Paillère Martinot, M.; Artiges, E.; Nees, F.; Papadopoulos Orfanos, D.; Paus, T.; Poustka, L.; Smolka, M. N.; Hohmann, S.; Holz, N.; Vaidya, N.; Walter, H.; Whelan, R.; Schumann, G.; Bertolino, A.; Pergola, G.; Antonucci, L. A.; and The IMAGEN Consortium\n\n\n \n\n\n\n Frontiers in Psychology, 15: 1434470. November 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Ruminative$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{fazio_ruminative_2024,\n\ttitle = {Ruminative thinking mediates the effects of exposure to adverse life events on psychotic-like experiences},\n\tvolume = {15},\n\tissn = {1664-1078},\n\turl = {https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1434470/full},\n\tdoi = {10.3389/fpsyg.2024.1434470},\n\tabstract = {Introduction: \n              A growing literature has shown that exposure to adverse life events during childhood or adolescence is associated with the presence of psychotic-like experiences (PLEs), which is in turn associated with the risk of psychotic outcomes. Ruminative thinking, i.e., the tendency to dwell on particular issues or ideas, may affect the perceived aversiveness and ability to cope with adverse life events. However, the role that rumination plays in the relationship between adverse life events and the presence of PLEs remains unclear. The purpose of this study is to assess the association between adverse life events and PLEs in a longitudinal sample of young adults and adolescents, and to investigate whether this relationship is mediated by ruminative thinking. \n             \n             \n              Methods \n              We used a longitudinal naturalistic sample of 706 volunteers assessed at ages 18 and 22 years, within the Imagen consortium. Lifetime occurrence of adverse life events (i.e., events perceived as strongly negative by participants) was investigated using the Life Events Questionnaire. The Community Assessment of Psychic Experience (CAPE-42) served to assess the presence of PLEs, while ruminative thinking was investigated through the Ruminative Response Scale. \n             \n             \n              Results \n               \n                Results showed that both frequency of PLEs and their persistence over time were associated with greater adverse life events exposure ( \n                r \n                = 0.32, \n                p \n                \\&lt; 0.001 and \n                F \n                1 \n                = 9.8; \n                p \n                \\&lt; 0.001, respectively) and greater ruminative response ( \n                r \n                = 0.66, \n                p \n                \\&lt; 0.001 and \n                F \n                1 \n                = 94.9; \n                p \n                \\&lt; 0.001, respectively). Mediation analyses showed that relationship between adverse life events and PLEs frequency was partially mediated by rumination (direct effect Z: 5.4, \n                p \n                \\&lt; 0.001; indirect effect Z: 6.9, \n                p \n                \\&lt; 0.001; total effect Z: 5.9, \n                p \n                \\&lt; 0.001). Considering changes between the two assessment timepoints, relationship between PLEs variation between 18 and 22 years and adverse life events occurred during the same period was partially mediated by changes in rumination (direct effect Z: 2.8, \n                p \n                \\&lt; 0.005; indirect effect Z: 4.3, \n                p \n                \\&lt; 0.001; total effect Z: 4.3; \n                p \n                \\&lt; 0.001). \n               \n             \n             \n              Discussion \n              Overall, our findings confirm that the presence of adverse life events may increase the risk of experiencing PLEs in healthy individuals and suggest that dysfunctional coping strategies, such as ruminative thinking, may be related to psychosis proneness. Results do not disentangle whether individuals with greater risk for psychosis tend to ruminate more or whether rumination exacerbates psychosis risk.},\n\turldate = {2025-01-30},\n\tjournal = {Frontiers in Psychology},\n\tauthor = {Fazio, Leonardo and Raio, Alessandra and Banaschewski, Tobias and Bokde, Arun L. W. and Desrivières, Sylvane and Flor, Herta and Garavan, Hugh and Gowland, Penny and Grigis, Antoine and Heinz, Andreas and Martinot, Jean-Luc and Paillère Martinot, Marie-Laure and Artiges, Eric and Nees, Frauke and Papadopoulos Orfanos, Dimitri and Paus, Tomáš and Poustka, Luise and Smolka, Michael N. and Hohmann, Sarah and Holz, Nathalie and Vaidya, Nilakshi and Walter, Henrik and Whelan, Robert and Schumann, Gunter and Bertolino, Alessandro and Pergola, Giulio and Antonucci, Linda A. and {The IMAGEN Consortium}},\n\tmonth = nov,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {1434470},\n}\n\n\n\n

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\n Introduction: A growing literature has shown that exposure to adverse life events during childhood or adolescence is associated with the presence of psychotic-like experiences (PLEs), which is in turn associated with the risk of psychotic outcomes. Ruminative thinking, i.e., the tendency to dwell on particular issues or ideas, may affect the perceived aversiveness and ability to cope with adverse life events. However, the role that rumination plays in the relationship between adverse life events and the presence of PLEs remains unclear. The purpose of this study is to assess the association between adverse life events and PLEs in a longitudinal sample of young adults and adolescents, and to investigate whether this relationship is mediated by ruminative thinking. Methods We used a longitudinal naturalistic sample of 706 volunteers assessed at ages 18 and 22 years, within the Imagen consortium. Lifetime occurrence of adverse life events (i.e., events perceived as strongly negative by participants) was investigated using the Life Events Questionnaire. The Community Assessment of Psychic Experience (CAPE-42) served to assess the presence of PLEs, while ruminative thinking was investigated through the Ruminative Response Scale. Results Results showed that both frequency of PLEs and their persistence over time were associated with greater adverse life events exposure ( r = 0.32, p < 0.001 and F 1 = 9.8; p < 0.001, respectively) and greater ruminative response ( r = 0.66, p < 0.001 and F 1 = 94.9; p < 0.001, respectively). Mediation analyses showed that relationship between adverse life events and PLEs frequency was partially mediated by rumination (direct effect Z: 5.4, p < 0.001; indirect effect Z: 6.9, p < 0.001; total effect Z: 5.9, p < 0.001). Considering changes between the two assessment timepoints, relationship between PLEs variation between 18 and 22 years and adverse life events occurred during the same period was partially mediated by changes in rumination (direct effect Z: 2.8, p < 0.005; indirect effect Z: 4.3, p < 0.001; total effect Z: 4.3; p < 0.001). Discussion Overall, our findings confirm that the presence of adverse life events may increase the risk of experiencing PLEs in healthy individuals and suggest that dysfunctional coping strategies, such as ruminative thinking, may be related to psychosis proneness. Results do not disentangle whether individuals with greater risk for psychosis tend to ruminate more or whether rumination exacerbates psychosis risk.\n

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\n \n\n \n \n \n \n \n \n kMetaShot: a fast and reliable taxonomy classifier for metagenome-assembled genomes.\n \n \n \n \n\n\n \n Defazio, G.; Tangaro, M. A.; Pesole, G.; and Fosso, B.\n\n\n \n\n\n\n Briefings in Bioinformatics, 26(1): bbae680. November 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"kMetaShot:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{defazio_kmetashot_2024,\n\ttitle = {{kMetaShot}: a fast and reliable taxonomy classifier for metagenome-assembled genomes},\n\tvolume = {26},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1467-5463, 1477-4054},\n\tshorttitle = {{kMetaShot}},\n\turl = {https://academic.oup.com/bib/article/doi/10.1093/bib/bbae680/7941744},\n\tdoi = {10.1093/bib/bbae680},\n\tabstract = {Abstract \n            The advent of high-throughput sequencing (HTS) technologies unlocked the complexity of the microbial world through the development of metagenomics, which now provides an unprecedented and comprehensive overview of its taxonomic and functional contribution in a huge variety of macro- and micro-ecosystems. In particular, shotgun metagenomics allows the reconstruction of microbial genomes, through the assembly of reads into MAGs (metagenome-assembled genomes). In fact, MAGs represent an information-rich proxy for inferring the taxonomic composition and the functional contribution of microbiomes, even if the relevant analytical approaches are not trivial and still improvable. In this regard, tools like CAMITAX and GTDBtk have implemented complex approaches, relying on marker gene identification and sequence alignments, requiring a large processing time. With the aim of deploying an effective tool for fast and reliable MAG taxonomic classification, we present here kMetaShot, a taxonomy classifier based on k-mer/minimizer counting. We benchmarked kMetaShot against CAMITAX and GTDBtk by using both in silico and real mock communities and demonstrated how, while implementing a fast and concise algorithm, it outperforms the other tools in terms of classification accuracy. Additionally, kMetaShot is an easy-to-install and easy-to-use bioinformatic tool that is also suitable for researchers with few command-line skills. It is available and documented at https://github.com/gdefazio/kMetaShot.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-01-30},\n\tjournal = {Briefings in Bioinformatics},\n\tauthor = {Defazio, Giuseppe and Tangaro, Marco Antonio and Pesole, Graziano and Fosso, Bruno},\n\tmonth = nov,\n\tyear = {2024},\n\tkeywords = {SP3, WP4},\n\tpages = {bbae680},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Changes in Angiogenesis and Bone Turnover Markers in Patients with Gaucher Disease Developing Osteonecrosis.\n \n \n \n \n\n\n \n D’Amore, S.; Poole, K. E.; Ramaswami, U.; Hughes, D.; Page, K.; Solimando, A. G.; Vacca, A.; Cox, T. M.; and Deegan, P.\n\n\n \n\n\n\n Metabolites, 14(11): 601. November 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Changes$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{damore_changes_2024,\n\ttitle = {Changes in {Angiogenesis} and {Bone} {Turnover} {Markers} in {Patients} with {Gaucher} {Disease} {Developing} {Osteonecrosis}},\n\tvolume = {14},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2218-1989},\n\turl = {https://www.mdpi.com/2218-1989/14/11/601},\n\tdoi = {10.3390/metabo14110601},\n\tabstract = {Background/Objectives: Patients with Gaucher disease have a high risk of bone disease, with osteonecrosis representing the most debilitating complication. The pathogenesis of osteonecrosis has not been fully elucidated yet, and there is an unmet need for predictive biomarkers of bone complications. We aimed to assess the utility of angiogenesis and bone turnover biomarkers as predictors of osteonecrosis in Gaucher disease. Methods: Angiogenesis and bone turnover biomarkers were measured in 146 Gaucher disease patients (70M:76F, median age 49.5 [IQR 36.7 to 61]) with/without osteonecrosis enrolled in the UK-based registry GAUCHERITE [enrolment 2015–2017]. Receiver-operating characteristic curve analysis was used to compare the osteonecrosis predictive value of angiogenesis and bone turnover biomarkers and determine the optimal cut-off values for each biomarker. Results: Sixty-two patients had osteonecrosis before study enrolment, 11 had osteonecrosis during follow-up, and 73 remained osteonecrosis-free. Patients with osteonecrosis showed increased osteopontin and matrix metalloproteinase (MMP)-2 levels and decreased MMP-9 and vascular endothelial growth factor (VEGF)-C compared with those free from osteonecrosis. MMP-9 predicted future osteonecrosis with higher sensitivity and specificity (area under the receiver operating characteristic curve [AUC] 0.84 [95\\% CI 0.84–0.99]; sensitivity/specificity 82\\%/75\\%; cutoff value ≤ 72,420 pg/mL) than osteopontin, MMP-2 and VEGF-C when taken alone. The combination of MMP-9 and VEGF-C further increased the discriminating accuracy. Conclusions: The osteopontin–MMPs–VEGF axis is dysregulated in Gaucher disease patients with osteonecrosis. The combination of MMP-9 and VEGF-C circulating levels may serve to identify Gaucher disease patients at risk of osteonecrosis.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2024-12-09},\n\tjournal = {Metabolites},\n\tauthor = {D’Amore, Simona and Poole, Kenneth Eric and Ramaswami, Uma and Hughes, Derralynn and Page, Kathleen and Solimando, Antonio Giovanni and Vacca, Angelo and Cox, Timothy Martin and Deegan, Patrick},\n\tmonth = nov,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {601},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Metabolic Syndrome and Cardiovascular Risk Factors in a Fishing Community in Southern Italy.\n \n \n \n \n\n\n \n Stufano, A.; D'Amore, S.; Schino, V.; Danza, P.; Iavicoli, I.; and Lovreglio, P.\n\n\n \n\n\n\n Safety and Health at Work, 15(4): 464–471. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Metabolic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{stufano_metabolic_2024,\n\ttitle = {Metabolic {Syndrome} and {Cardiovascular} {Risk} {Factors} in a {Fishing} {Community} in {Southern} {Italy}},\n\tvolume = {15},\n\tissn = {20937911},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2093791124000738},\n\tdoi = {10.1016/j.shaw.2024.10.001},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-01-07},\n\tjournal = {Safety and Health at Work},\n\tauthor = {Stufano, Angela and D'Amore, Simona and Schino, Valentina and Danza, Paolo and Iavicoli, Ivo and Lovreglio, Piero},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {464--471},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Efficacy and safety of benralizumab in eosinophilic granulomatosis with polyangiitis: A meta-analysis of eight studies.\n \n \n \n \n\n\n \n Spataro, F.; Solimando, A.; Di Girolamo, A.; Vacca, A.; and Ria, R.\n\n\n \n\n\n\n European Journal of Clinical Investigation. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficacy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{spataro_efficacy_2024,\n\ttitle = {Efficacy and safety of benralizumab in eosinophilic granulomatosis with polyangiitis: {A} meta-analysis of eight studies},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205891563&doi=10.1111%2feci.14333&partnerID=40&md5=02c2b545a7e73a61234c5ac1a78fd79f},\n\tdoi = {10.1111/eci.14333},\n\tjournal = {European Journal of Clinical Investigation},\n\tauthor = {Spataro, F. and Solimando, A.G. and Di Girolamo, A. and Vacca, A. and Ria, R.},\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Zinc metabolism and its role in immunity status in subjects with trisomy 21: chromosomal dosage effect.\n \n \n \n \n\n\n \n Ramacieri, G.; Locatelli, C.; Semprini, M.; Pelleri, M. C.; Caracausi, M.; Piovesan, A.; Cicilloni, M.; Vigna, M.; Vitale, L.; Sperti, G.; Corvaglia, L. T.; Pirazzoli, G. L.; Strippoli, P.; Catapano, F.; Vione, B.; and Antonaros, F.\n\n\n \n\n\n\n Frontiers in Immunology, 15: 1362501. April 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Zinc$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{ramacieri_zinc_2024,\n\ttitle = {Zinc metabolism and its role in immunity status in subjects with trisomy 21: chromosomal dosage effect},\n\tvolume = {15},\n\tissn = {1664-3224},\n\tshorttitle = {Zinc metabolism and its role in immunity status in subjects with trisomy 21},\n\turl = {https://www.frontiersin.org/articles/10.3389/fimmu.2024.1362501/full},\n\tdoi = {10.3389/fimmu.2024.1362501},\n\tabstract = {Introduction \n               \n                Trisomy 21 (T21), which causes Down syndrome (DS), is the most common chromosomal aneuploidy in humankind and includes different clinical comorbidities, among which the alteration of the immune system has a heavy impact on patient’s lives. A molecule with an important role in immune response is zinc and it is known that its concentration is significantly lower in children with T21. Different hypotheses were made about this metabolic alteration and one of the reasons might be the overexpression of superoxide dismutase 1 ( \n                SOD1 \n                ) gene, as zinc is part of the SOD1 active enzymatic center. \n               \n             \n             \n              Methods \n              The aim of our work is to explore if there is a linear correlation between zinc level and immune cell levels measured in a total of 217 blood samples from subjects with T21. Furthermore, transcriptome map analyses were performed using Transcriptome Mapper (TRAM) software to investigate whether a difference in gene expression is detectable between subjects with T21 and euploid control group in tissues and cells involved in the immune response such as lymphoblastoid cells, thymus and white blood cells. \n             \n             \n              Results \n              Our results have confirmed the literature data stating that the blood zinc level in subjects with T21 is lower compared to the general population; in addition, we report that the T21/control zinc concentration ratio is 2:3, consistent with a chromosomal dosage effect due to the presence of three copies of chromosome 21. The transcriptome map analyses showed an alteration of some gene’s expression which might explain low levels of zinc in the blood. \n             \n             \n              Discussion \n              Our data suggest that zinc level is not associated with the levels of immunity cells or proteins analyzed themselves and rather the main role of this ion might be played in altering immune cell function.},\n\turldate = {2025-01-30},\n\tjournal = {Frontiers in Immunology},\n\tauthor = {Ramacieri, Giuseppe and Locatelli, Chiara and Semprini, Michela and Pelleri, Maria Chiara and Caracausi, Maria and Piovesan, Allison and Cicilloni, Michela and Vigna, Marco and Vitale, Lorenza and Sperti, Giacomo and Corvaglia, Luigi Tommaso and Pirazzoli, Gian Luca and Strippoli, Pierluigi and Catapano, Francesca and Vione, Beatrice and Antonaros, Francesca},\n\tmonth = apr,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {1362501},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n β‐Sheets Orientation in Physisorbed Protein Layers.\n \n \n \n \n\n\n \n Piscitelli, M.; Bajrami, D.; Franco, C. D.; Sarcina, L.; Catacchio, M.; Macchia, E.; Torsi, L.; Mizaikoff, B.; and Scamarcio, G.\n\n\n \n\n\n\n Advanced Materials Interfaces,2400867. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"β‐Sheets$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{piscitelli_sheets_2024,\n\ttitle = {β‐{Sheets} {Orientation} in {Physisorbed} {Protein} {Layers}},\n\tissn = {2196-7350, 2196-7350},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/admi.202400867},\n\tdoi = {10.1002/admi.202400867},\n\tabstract = {Abstract \n            Physisorption of antibodies onto surfaces is a low‐cost, rapid, and effective approach for immobilizing bioreceptors in applications such as bioelectronic sensors. However, there is a prevailing notion that physisorbed protein layers lack structural order, thus potentially compromising their stability and sensitivity compared to antibody films that are covalently attached to the substrate surface. This study demonstrates the preferential orientation of β‐sheets within the secondary structure of protein layers, specifically anti‐immunoglobulin G (anti‐IgG) and bovine serum albumin (BSA), when physisorbed onto gold (Au) thin films. Using polarization modulation infrared reflection‐absorption spectroscopy (PM‐IRRAS) and infrared attenuated total reflection (IR‐ATR) spectroscopy, it has been confirmed that the β‐strands in these protein layers are tilted relative to the surface normal by average angles of 75.3° ± 0.4° for anti‐IgG and of 79.3 ± 0.2° for BSA. These results are obtained by analyzing the orientation of the transition dipole moments (TDMs) associated with the amide I molecular vibrations derived from a comparison between experimental and simulated mid‐infrared spectra assuming isotropically oriented TDMs. The simulations incorporate refractive and absorption index dispersions obtained from the IR‐ATR spectra. Thus obtained findings offer valuable molecular‐level insights facilitating the design and optimization of biofunctionalized interfaces in advanced biomedical and biosensing applications.},\n\tlanguage = {en},\n\turldate = {2025-01-30},\n\tjournal = {Advanced Materials Interfaces},\n\tauthor = {Piscitelli, Matteo and Bajrami, Diellza and Franco, Cinzia Di and Sarcina, Lucia and Catacchio, Michele and Macchia, Eleonora and Torsi, Luisa and Mizaikoff, Boris and Scamarcio, Gaetano},\n\tmonth = dec,\n\tyear = {2024},\n\tkeywords = {SP3, WP4},\n\tpages = {2400867},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MR protocol optimization for hepatobiliary phase imaging with Gd-EOB-DTPA at 1.5 T: comparison between breath-hold T1-weighted and high-resolution navigated 3D T1-weighted sequences.\n \n \n \n \n\n\n \n Picchi, E.; Ferrazzoli, V.; Liberto, V.; Toti, L.; Da Ros, V.; Pucci, N.; Minosse, S.; Garaci, F.; and Di Giuliano, F.\n\n\n \n\n\n\n Egyptian Journal of Radiology and Nuclear Medicine, 55(1). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"MR$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{picchi_mr_2024,\n\ttitle = {{MR} protocol optimization for hepatobiliary phase imaging with {Gd}-{EOB}-{DTPA} at 1.5 {T}: comparison between breath-hold {T1}-weighted and high-resolution navigated {3D} {T1}-weighted sequences},\n\tvolume = {55},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211376258&doi=10.1186%2fs43055-024-01408-7&partnerID=40&md5=a0e558f7ffad3bfe3becf57caeb4760d},\n\tdoi = {10.1186/s43055-024-01408-7},\n\tnumber = {1},\n\tjournal = {Egyptian Journal of Radiology and Nuclear Medicine},\n\tauthor = {Picchi, E. and Ferrazzoli, V. and Liberto, V. and Toti, L. and Da Ros, V. and Pucci, N. and Minosse, S. and Garaci, F. and Di Giuliano, F.},\n\tyear = {2024},\n\tkeywords = {SP3, WP2},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis.\n \n \n \n \n\n\n \n Picchi, E.; Minosse, S.; Pucci, N.; Di Pietro, F.; Serio, M.; Ferrazzoli, V.; Da Ros, V.; Giocondo, R.; Garaci, F.; and Di Giuliano, F.\n\n\n \n\n\n\n Diagnostics, 14(15). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Compressed$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{picchi_compressed_2024,\n\ttitle = {Compressed {SENSitivity} {Encoding} ({SENSE}): {Qualitative} and {Quantitative} {Analysis}},\n\tvolume = {14},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200734544&doi=10.3390%2fdiagnostics14151693&partnerID=40&md5=98cf923d569df2ef8b54c21bd0845626},\n\tdoi = {10.3390/diagnostics14151693},\n\tnumber = {15},\n\tjournal = {Diagnostics},\n\tauthor = {Picchi, E. and Minosse, S. and Pucci, N. and Di Pietro, F. and Serio, M.L. and Ferrazzoli, V. and Da Ros, V. and Giocondo, R. and Garaci, F. and Di Giuliano, F.},\n\tyear = {2024},\n\tkeywords = {SP3, WP2},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Deterioration of Vestibular Motion Perception: A Risk Factor for Postural Instability and Falls in Elderly With Type 2 Diabetes.\n \n \n \n \n\n\n \n La Scaleia, B.; Siena, A.; D'Onofrio, L.; Celli, A.; Capuzzi, G.; Latino, A.; Nateri Cara, G.; Maddaloni, E.; Zampetti, S.; Buzzetti, R.; Zago, M.; and Lacquaniti, F.\n\n\n \n\n\n\n Diabetes/Metabolism Research and Reviews, 40(7). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Deterioration$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{la_scaleia_deterioration_2024,\n\ttitle = {Deterioration of {Vestibular} {Motion} {Perception}: {A} {Risk} {Factor} for {Postural} {Instability} and {Falls} in {Elderly} {With} {Type} 2 {Diabetes}},\n\tvolume = {40},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205527166&doi=10.1002%2fdmrr.3845&partnerID=40&md5=12575ad9f12e286c107e0a5ba5e1068c},\n\tdoi = {10.1002/dmrr.3845},\n\tnumber = {7},\n\tjournal = {Diabetes/Metabolism Research and Reviews},\n\tauthor = {La Scaleia, B. and Siena, A. and D'Onofrio, L. and Celli, A. and Capuzzi, G. and Latino, A. and Nateri Cara, G. and Maddaloni, E. and Zampetti, S. and Buzzetti, R. and Zago, M. and Lacquaniti, F.},\n\tyear = {2024},\n\tkeywords = {SP3, WP2},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n To Generate or to Retrieve? On the Effectiveness of Artificial Contexts for Medical Open-Domain Question Answering.\n \n \n \n \n\n\n \n Frisoni, G.; Cocchieri, A.; Presepi, A.; Moro, G.; and Meng, Z.\n\n\n \n\n\n\n In volume 1, pages 9878–9919, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"To$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{frisoni_generate_2024,\n\ttitle = {To {Generate} or to {Retrieve}? {On} the {Effectiveness} of {Artificial} {Contexts} for {Medical} {Open}-{Domain} {Question} {Answering}},\n\tvolume = {1},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204491582&partnerID=40&md5=f89209e0a98ee4d070be870f40aa1793},\n\tdoi = {http://dx.doi.org/10.18653/v1/2024.acl-long.533},\n\tauthor = {Frisoni, G. and Cocchieri, A. and Presepi, A. and Moro, G. and Meng, Z.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {9878--9919},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n INDIGO IAM migration to Spring Authorization Server framework with a new customizable React user dashboard.\n \n \n \n \n\n\n \n Agostini, F.; Casale, A.; Gasparetto, J.; Giacomini, F.; Marcato, D.; Miccoli, R.; Vianello, E.; and Zotti, S.\n\n\n \n\n\n\n In volume 458, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"INDIGO$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{agostini_indigo_2024,\n\ttitle = {{INDIGO} {IAM} migration to {Spring} {Authorization} {Server} framework with a new customizable {React} user dashboard},\n\tvolume = {458},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208618416&partnerID=40&md5=ab3ead40ab72405a5886f084f8db996b},\n\tdoi = {https://doi.org/10.22323/1.458.0029},\n\tauthor = {Agostini, F. and Casale, A. and Gasparetto, J. and Giacomini, F. and Marcato, D. and Miccoli, R. and Vianello, E. and Zotti, S.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI.\n \n \n \n \n\n\n \n Ceccarelli, F.; Prinzi, F.; Liò, P.; Vitabile, S.; and Holden, S.\n\n\n \n\n\n\n In 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"MUGI-MRI:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{ceccarelli_mugi-mri_2024,\n\ttitle = {{MUGI}-{MRI}: {Enhancing} {Breast} {Cancer} {Classification} through {Multiplex} {Graph} {Neural} {Networks} in {DCE}-{MRI}},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204950542&doi=10.1109%2fIJCNN60899.2024.10650117&partnerID=40&md5=2754949e9c6235107cd2c3693ad7af37},\n\tdoi = {10.1109/IJCNN60899.2024.10650117},\n\tauthor = {Ceccarelli, F. and Prinzi, F. and Liò, P. and Vitabile, S. and Holden, S.B.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Professional Insights into Benefits and Limitations of Implementing MLOps Principles.\n \n \n \n \n\n\n \n Araujo, G.; Kalinowski, M.; Endler, M.; and Calefato, F.\n\n\n \n\n\n\n In volume 2, pages 305–312, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Professional$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{araujo_professional_2024,\n\ttitle = {Professional {Insights} into {Benefits} and {Limitations} of {Implementing} {MLOps} {Principles}},\n\tvolume = {2},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194000799&doi=10.5220%2f0012741100003690&partnerID=40&md5=75dc5746b17a4225be2c3cbcc8277df2},\n\tdoi = {10.5220/0012741100003690},\n\tauthor = {Araujo, G. and Kalinowski, M. and Endler, M. and Calefato, F.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {305--312},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n What Are You Token About? Differentiable Perturbed Top-k Token Selection for Scientific Document Summarization.\n \n \n \n \n\n\n \n Ragazzi, L.; Italiani, P.; Moro, G.; and Panni, M.\n\n\n \n\n\n\n In pages 9427–9440, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"What$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{ragazzi_what_2024,\n\ttitle = {What {Are} {You} {Token} {About}? {Differentiable} {Perturbed} {Top}-k {Token} {Selection} for {Scientific} {Document} {Summarization}},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203372057&partnerID=40&md5=f72171aed38d91b8c8a47d9d1a10adbb},\n\tauthor = {Ragazzi, L. and Italiani, P. and Moro, G. and Panni, M.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {9427--9440},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n From Voxels to Insights: Exploring the Effectiveness and Transparency of Graph Neural Networks in Brain Tumor Segmentation.\n \n \n \n \n\n\n \n Amendola, D.; Basile, A.; Castellano, G.; Vessio, G.; and Zaza, G.\n\n\n \n\n\n\n In 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"From$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{amendola_voxels_2024,\n\ttitle = {From {Voxels} to {Insights}: {Exploring} the {Effectiveness} and {Transparency} of {Graph} {Neural} {Networks} in {Brain} {Tumor} {Segmentation}},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205008733&doi=10.1109%2fIJCNN60899.2024.10650146&partnerID=40&md5=3aa2a3c9f8ea749706213192c9a2986e},\n\tdoi = {10.1109/IJCNN60899.2024.10650146},\n\tauthor = {Amendola, D. and Basile, A. and Castellano, G. and Vessio, G. and Zaza, G.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Artificial Intelligence Implementation in Internet of Things Embedded System for Real-Time Person Presence in Bed Detection and Sleep Behaviour Monitor.\n \n \n \n \n\n\n \n Hoang, M.; Matrella, G.; and Ciampolini, P.\n\n\n \n\n\n\n Electronics (Switzerland), 13(11). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Artificial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{hoang_artificial_2024,\n\ttitle = {Artificial {Intelligence} {Implementation} in {Internet} of {Things} {Embedded} {System} for {Real}-{Time} {Person} {Presence} in {Bed} {Detection} and {Sleep} {Behaviour} {Monitor}},\n\tvolume = {13},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195822834&doi=10.3390%2felectronics13112210&partnerID=40&md5=5be93a30025f2a5e6676b8b0ac5e552b},\n\tdoi = {10.3390/electronics13112210},\n\tnumber = {11},\n\tjournal = {Electronics (Switzerland)},\n\tauthor = {Hoang, M.L. and Matrella, G. and Ciampolini, P.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices.\n \n \n \n \n\n\n \n Iovino, M.; Lazic, I.; Loncar-Turukalo, T.; Javorka, M.; Pernice, R.; and Faes, L.\n\n\n \n\n\n\n Physiological Measurement, 45(11). 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{iovino_comparison_2024,\n\ttitle = {Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices},\n\tvolume = {45},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210322902&doi=10.1088%2f1361-6579%2fad9234&partnerID=40&md5=071a36e37833c008f34132ff4153c507},\n\tdoi = {10.1088/1361-6579/ad9234},\n\tnumber = {11},\n\tjournal = {Physiological Measurement},\n\tauthor = {Iovino, M. and Lazic, I. and Loncar-Turukalo, T. and Javorka, M. and Pernice, R. and Faes, L.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Explaining Network Decision Provides Insights on the Causal Interaction Between Brain Regions in a Motor Imagery Task.\n \n \n \n \n\n\n \n Borra, D.; and Ravanelli, M.\n\n\n \n\n\n\n In volume 15154 LNAI, pages 156–167, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Explaining$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{borra_explaining_2024,\n\ttitle = {Explaining {Network} {Decision} {Provides} {Insights} on the {Causal} {Interaction} {Between} {Brain} {Regions} in a {Motor} {Imagery} {Task}},\n\tvolume = {15154 LNAI},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205366273&doi=10.1007%2f978-3-031-71602-7_14&partnerID=40&md5=42cd43cfaca499b2637c9a1fc5d6720a},\n\tdoi = {10.1007/978-3-031-71602-7_14},\n\tauthor = {Borra, D. and Ravanelli, M.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {156--167},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n EEG Features Learned by Convolutional Neural Networks Reflect Alterations of Social Stimuli Processing in Autism.\n \n \n \n \n\n\n \n Borra, D.; Diciotti, S.; and Magosso, E.\n\n\n \n\n\n\n In volume 15019 LNCS, pages 124–136, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"EEG$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{borra_eeg_2024,\n\ttitle = {{EEG} {Features} {Learned} by {Convolutional} {Neural} {Networks} {Reflect} {Alterations} of {Social} {Stimuli} {Processing} in {Autism}},\n\tvolume = {15019 LNCS},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205284720&doi=10.1007%2f978-3-031-72341-4_9&partnerID=40&md5=1906410a98f7e7de5fe56ef8ccf41b0e},\n\tdoi = {10.1007/978-3-031-72341-4_9},\n\tauthor = {Borra, D. and Diciotti, S. and Magosso, E.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n\tpages = {124--136},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Computational Genomics platform: a Cloud-enabled approach.\n \n \n \n \n\n\n \n Gasparetto, J.; Magenta, L.; Sinisi, F.; Zotti, S.; Costantini, A.; Martelli, B.; Giangregorio, T.; and Pippucci, T.\n\n\n \n\n\n\n In volume 458, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Computational$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{gasparetto_computational_2024,\n\ttitle = {Computational {Genomics} platform: a {Cloud}-enabled approach},\n\tvolume = {458},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208652703&doi=10.22323%2f1.458.0042&partnerID=40&md5=72ebd0cac960e0b88f6833249725100b},\n\tdoi = {10.22323/1.458.0042},\n\tauthor = {Gasparetto, J. and Magenta, L. and Sinisi, F. and Zotti, S. and Costantini, A. and Martelli, B. and Giangregorio, T. and Pippucci, T.},\n\tyear = {2024},\n\tkeywords = {SP1, WP3},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n HA Kubernetes cluster using Octavia Ingress Controller.\n \n \n \n \n\n\n \n Sinisi, F.; Alkhansa, A.; Michelotto, D.; and Costantini, A.\n\n\n \n\n\n\n In volume 458, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"HA$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{sinisi_ha_2024,\n\ttitle = {{HA} {Kubernetes} cluster using {Octavia} {Ingress} {Controller}},\n\tvolume = {458},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208619244&doi=10.22323%2f1.458.0028&partnerID=40&md5=c62522bdf98f16b54bb2d7517eec7df8},\n\tdoi = {10.22323/1.458.0028},\n\tauthor = {Sinisi, F. and Alkhansa, A. and Michelotto, D. and Costantini, A.},\n\tyear = {2024},\n\tkeywords = {SP1, WP3},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Comparison of entropy rate measures for the evaluation of time series complexity: Simulations and application to heart rate and respiratory variability.\n \n \n \n \n\n\n \n Barà, C.; Pernice, R.; Catania, C.; Hilal, M.; Porta, A.; Humeau-Heurtier, A.; and Faes, L.\n\n\n \n\n\n\n Biocybernetics and Biomedical Engineering, 44(2): 380–392. 2024.\n Number: 2\n\n\n\n
\n\n\n\n \n \n $\"Comparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{bara_comparison_2024,\n\ttitle = {Comparison of entropy rate measures for the evaluation of time series complexity: {Simulations} and application to heart rate and respiratory variability},\n\tvolume = {44},\n\tissn = {02085216 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192827276&doi=10.1016%2fj.bbe.2024.04.004&partnerID=40&md5=b225ef3852bdb6e8466fe203e3de7c40},\n\tdoi = {10.1016/j.bbe.2024.04.004},\n\tabstract = {Most real-world systems are characterised by dynamics and correlations emerging at multiple time scales, and are therefore referred to as complex systems. In this work, the complexity of time series produced by complex systems was investigated in the frame of information theory computing the entropy rate via the conditional entropy (CE) measure. A comparative investigation of several CE estimators, based on linear parametric and non-linear model-free representations of the process dynamics, was performed considering simulated linear autoregressive (AR) and mixed non-linear deterministic and linear stochastic dynamics processes, as well as physiological time series reflecting short-term cardiorespiratory dynamics. In simulations, the estimated CE values decreased when reducing the system complexity through an increase in the pole radius of the AR process or with the predominance of the deterministic behaviour in the mixed dynamics. In the application to cardiorespiratory dynamics, a reduction in physiological complexity was observed resulting from a regularization of the time series of heart rate and respiratory volume when decreasing the breathing rate. Our results evidence how simple and fast approaches based on linear parametric or permutation-based model-free estimators allow efficient discrimination of complexity changes in the short-term evolution of complex dynamic systems. However, in the presence of non-linear dynamics, the superiority of the more general but computationally expensive nearest-neighbour method is highlighted. These findings have implications for the assessment of complex dynamics both in clinical settings and in physiological monitoring. © 2024 The Author(s)},\n\tlanguage = {English},\n\tnumber = {2},\n\tjournal = {Biocybernetics and Biomedical Engineering},\n\tpublisher = {Elsevier B.V.},\n\tauthor = {Barà, C. and Pernice, R. and Catania, C.A. and Hilal, M. and Porta, A. and Humeau-Heurtier, A. and Faes, L.},\n\tyear = {2024},\n\tnote = {Number: 2},\n\tkeywords = {Cardiorespiratory dynamics, Complexity, Conditional entropy, Linear parametric entropy estimation, Non-linear model-free entropy estimation, SP1, WP4, article, breathing rate, controlled study, entropy, female, heart rate, human, lung volume, physiologic monitoring, simulation, time series analysis},\n\tpages = {380--392},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Italian normative data for the Unhelpful Thoughts and Beliefs about Stuttering (UTBAS) Scales for adults who stutter.\n \n \n \n \n\n\n \n Bernardini, S.; Onnivello, S.; and Lanfranchi, S.\n\n\n \n\n\n\n Journal of Fluency Disorders, 81. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Italian$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{bernardini_italian_2024,\n\ttitle = {Italian normative data for the {Unhelpful} {Thoughts} and {Beliefs} about {Stuttering} ({UTBAS}) {Scales} for adults who stutter},\n\tvolume = {81},\n\tissn = {0094730X (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197418521&doi=10.1016%2fj.jfludis.2024.106074&partnerID=40&md5=22edd15d8e78eb82e6dc6fc48e851b65},\n\tdoi = {10.1016/j.jfludis.2024.106074},\n\tabstract = {Purpose: This study aimed to assess the reliability and validity of the Italian translation of the Unhelpful Thoughts and Beliefs about Stuttering (UTBAS) scales for adults who stutter, as there are no assessment tools currently available in Italy. The UTBAS scales provide a comprehensive stuttering-specific measure of the unhelpful thoughts and beliefs that can be used to screen for indicators of social anxiety in adults who stutter. Additionally, the UTBAS scales also allow the identification of negative thoughts and beliefs that negatively impact speech treatment outcomes. Method: The translation of the UTBAS scales into Italian (UTBAS-ITA) was completed using the forward-backward translation process and it was administered to 98 adults who stutter (AWS) and 98 adults who do not stutter (AWNS). Both groups were matched for gender and age. We also administered the UTBAS-ITA to 76 AWS a second time within a two-week interval to assess test-retest reliability. Additionally, we administered the State-Trait Anxiety Inventory and the Fear of Negative Evaluation Scale to 20 AWS to assess concurrent validity. Results: The UTBAS-ITA showed good power of discrimination between AWS and AWNS, high internal validity, high internal consistency, good construct validity, and good test-retest reliability. Conclusion: Since there is a scarcity of clinical assessment tools for adults who stutter in Italy, the UTBAS-ITA could serve as an assessment tool and outcome measure for clinical and research environments. © 2024 The Authors},\n\tlanguage = {English},\n\tjournal = {Journal of Fluency Disorders},\n\tpublisher = {Elsevier Inc.},\n\tauthor = {Bernardini, S. and Onnivello, S. and Lanfranchi, S.},\n\tyear = {2024},\n\tkeywords = {Adults who stutter, Article, Italian (language), Negative thoughts, Reliability, SP3, State Trait Anxiety Inventory, UTBAS scales, Validity, WP3, adult, age, clinical assessment tool, concurrent validity, construct validity, controlled study, fear of negative evaluation scale, female, gender, human, internal consistency, internal validity, major clinical study, male, reliability, social anxiety, speech, stuttering, test retest reliability, treatment outcome, unhelpful thoughts and beliefs about stuttering scale, validity},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Lot of Talk and a Badge: An Exploratory Analysis of Personal Achievements in GitHub.\n \n \n \n \n\n\n \n Calefato, F.; Quaranta, L.; and Lanubile, F.\n\n\n \n\n\n\n Information and Software Technology, 176: 107561. December 2024.\n arXiv:2303.14702 [cs]\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

@article{calefato_lot_2024,\n\ttitle = {A {Lot} of {Talk} and a {Badge}: {An} {Exploratory} {Analysis} of {Personal} {Achievements} in {GitHub}},\n\tvolume = {176},\n\tissn = {09505849},\n\tshorttitle = {A {Lot} of {Talk} and a {Badge}},\n\turl = {http://arxiv.org/abs/2303.14702},\n\tdoi = {10.1016/j.infsof.2024.107561},\n\tabstract = {Context. GitHub has introduced a new gamification element through personal achievements, whereby badges are unlocked and displayed on developers' personal profile pages in recognition of their development activities. Objective. In this paper, we present an exploratory analysis using mixed methods to study the diffusion of personal badges in GitHub, in addition to the effects and reactions to their introduction. Method. First, we conduct an observational study by mining longitudinal data from more than 6,000 developers and performed correlation and regression analysis. Then, we conduct a survey and analyze over 300 GitHub community discussions on the topic of personal badges to gauge how the community responded to the introduction of the new feature. Results. We find that most of the developers sampled own at least a badge, but we also observe an increasing number of users who choose to keep their profile private and opt out of displaying badges. Besides, badges are generally poorly correlated with developers' qualities and dispositions such as timeliness and desire to collaborate. We also find that, except for the Starstruck badge (reflecting the number of followers), their introduction does not have an effect. Finally, the reaction of the community has been in general mixed, as developers find them appealing in principle but without a clear purpose and hardly reflecting their abilities in the current form. Conclusions. We provide recommendations to GitHub platform designers on how to improve the current implementation of personal badges as both a gamification mechanism and as sources of reliable cues of ability for developers' assessment},\n\turldate = {2024-10-02},\n\tjournal = {Information and Software Technology},\n\tauthor = {Calefato, Fabio and Quaranta, Luigi and Lanubile, Filippo},\n\tmonth = dec,\n\tyear = {2024},\n\tnote = {arXiv:2303.14702 [cs]},\n\tkeywords = {Computer Science - Software Engineering, SP1, WP4},\n\tpages = {107561},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Perspectives on systematic optimization of ultrasensitive biosensors through experimental design.\n \n \n \n \n\n\n \n Caputo, M.; Tricase, A.; Marchianò, V.; Scandurra, C.; Piscitelli, M.; Sarcina, L.; Catacchio, M.; Di Franco, C.; Bollella, P.; Torsi, L.; and Macchia, E.\n\n\n \n\n\n\n Journal of Materials Chemistry C, 12(38): 15382–15400. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Perspectives$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{caputo_perspectives_2024,\n\ttitle = {Perspectives on systematic optimization of ultrasensitive biosensors through experimental design},\n\tvolume = {12},\n\tissn = {2050-7526, 2050-7534},\n\turl = {https://xlink.rsc.org/?DOI=D4TC02131B},\n\tdoi = {10.1039/D4TC02131B},\n\tabstract = {Biosensors are versatile in many applications, but their adoption as reliable point-of-care tests is hindered by challenges in systematic optimization. Experimental design provides a solution by guiding their effective development and refinement. \n          ,  \n            Biosensors have demonstrated versatility across numerous applications; however, their systematic optimization remains a primary obstacle, limiting their widespread adoption as dependable point-of-care tests. Experimental design, a powerful chemometric tool, offers a solution by effectively guiding the development and optimization of ultrasensitive biosensors. This perspective review provides an overview of recent applications of experimental design in the deployment of optical and electrical ultrasensitive biosensors. Various experimental designs, including full factorial, central composite, and mixture designs, are examined as systematic methodologies for optimizing biosensor fabrication, accounting for both individual variable effects and their interactions. Illustrative examples showcasing the optimization of optical and electronic biosensors through design of experiments are presented and critically analyzed. Finally, the future prospects of experimental design in the biosensor community are outlined, highlighting its potential to expedite development and bolster the performance of biosensing devices for point-of-care diagnostics, thereby facilitating their sustainable and reliable integration.},\n\tlanguage = {en},\n\tnumber = {38},\n\turldate = {2024-10-14},\n\tjournal = {Journal of Materials Chemistry C},\n\tauthor = {Caputo, Mariapia and Tricase, Angelo and Marchianò, Verdiana and Scandurra, Cecilia and Piscitelli, Matteo and Sarcina, Lucia and Catacchio, Michele and Di Franco, Cinzia and Bollella, Paolo and Torsi, Luisa and Macchia, Eleonora},\n\tyear = {2024},\n\tkeywords = {SP3, WP4},\n\tpages = {15382--15400},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Corrigendum: CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization(Front. Digit. Health, (2023), 5, (1322428), 10.3389/fdgth.2023.1322428).\n \n \n \n \n\n\n \n Carbonaro, A.; Marfoglia, A.; Nardini, F.; and Mellone, S.\n\n\n \n\n\n\n Frontiers in Digital Health, 6. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Corrigendum:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{carbonaro_corrigendum_2024,\n\ttitle = {Corrigendum: {CONNECTED}: leveraging digital twins and personal knowledge graphs in healthcare digitalization({Front}. {Digit}. {Health}, (2023), 5, (1322428), 10.3389/fdgth.2023.1322428)},\n\tvolume = {6},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195363922&doi=10.3389%2ffdgth.2024.1416390&partnerID=40&md5=3d2dc39fe7551c36733e77cac3691d34},\n\tdoi = {10.3389/fdgth.2024.1416390},\n\tabstract = {In the published article, there was an error in the Funding statement. We used an incorrect CUP number in the following statement “This study was partially supported by the Italian Ministry of University and Research under PNRR-PNC Project PNC0000002 “DARE—Digital Lifelong Prevention” (CUP: B53C22006240001).” The correct Funding statement appears below.” 2024 Carbonaro, Marfoglia, Nardini and Mellone.},\n\tjournal = {Frontiers in Digital Health},\n\tauthor = {Carbonaro, A. and Marfoglia, A. and Nardini, F. and Mellone, S.},\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease.\n \n \n \n \n\n\n \n Chumin, E.; Burton, C.; Silvola, R.; Miner, E.; Persohn, S.; Veronese, M.; and Territo, P.\n\n\n \n\n\n\n Alzheimer's and Dementia, 20(3): 1538–1549. 2024.\n Number: 3\n\n\n\n
\n\n\n\n \n \n $\"Brain$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{chumin_brain_2024,\n\ttitle = {Brain metabolic network covariance and aging in a mouse model of {Alzheimer}'s disease},\n\tvolume = {20},\n\tissn = {15525260 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178205572&doi=10.1002%2falz.13538&partnerID=40&md5=3c578bfdcff54ff4805c2b20672e29d6},\n\tdoi = {10.1002/alz.13538},\n\tabstract = {INTRODUCTION: Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. METHODS: We performed 18F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis. RESULTS: The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. DISCUSSION: The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models. © 2023 The Authors. Alzheimer's \\& Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.},\n\tlanguage = {English},\n\tnumber = {3},\n\tjournal = {Alzheimer's and Dementia},\n\tpublisher = {John Wiley and Sons Inc},\n\tauthor = {Chumin, E.J. and Burton, C.P. and Silvola, R. and Miner, E.W. and Persohn, S.C. and Veronese, M. and Territo, P.R.},\n\tyear = {2024},\n\tnote = {Number: 3},\n\tkeywords = {5xFAD mouse, Aging, Alzheimer Disease, Alzheimer disease, Alzheimer's disease, Animals, Article, Brain, C57BL 6 mouse, Female, Fluorodeoxyglucose F18, Humans, Infant, Male, Metabolic Networks and Pathways, Mice, Positron-Emission Tomography, SP3, T2 weighted imaging, WP4, aging, animal, animal experiment, animal model, animal tissue, brain, brain fornix, brain metabolism, brain region, cohort analysis, connectomics, controlled study, degree of freedom, diagnostic imaging, false discovery rate, female, filtered back projection, fluorodeoxyglucose f 18, glucose, glucose transport, hippocampus, human, infant, isoflurane, male, metabolic covariance networks, metabolism, mouse, nerve cell network, nonhuman, orbital cortex, partial volume (imaging), positron emission tomography, post hoc analysis, preclinical models, procedures, standardized uptake value ratio},\n\tpages = {1538--1549},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Impact of data quality for automatic issue classification using pre-trained language models.\n \n \n \n \n\n\n \n Colavito, G.; Lanubile, F.; Novielli, N.; and Quaranta, L.\n\n\n \n\n\n\n Journal of Systems and Software, 210. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Impact$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{colavito_impact_2024,\n\ttitle = {Impact of data quality for automatic issue classification using pre-trained language models},\n\tvolume = {210},\n\tissn = {01641212 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182430751&doi=10.1016%2fj.jss.2023.111838&partnerID=40&md5=4dabff585908fe8354d90e273b50e26e},\n\tdoi = {10.1016/j.jss.2023.111838},\n\tabstract = {Issue classification aims to recognize whether an issue reports a bug, a request for enhancement or support. In this paper we use pre-trained models for the automatic classification of issues and investigate how the quality of data affects the performance of classifiers. Despite the application of data quality filters, none of our attempts had a significant effect on model quality. As root cause we identify a threat to construct validity underlying the issue labeling. Editor's note: Open Science material was validated by the Journal of Systems and Software Open Science Board. © 2023 Elsevier Inc.},\n\tlanguage = {English},\n\tjournal = {Journal of Systems and Software},\n\tpublisher = {Elsevier Inc.},\n\tauthor = {Colavito, G. and Lanubile, F. and Novielli, N. and Quaranta, L.},\n\tyear = {2024},\n\tkeywords = {BERT, Classification (of information), Data quality, GitHub, Github, Issue labeling, Issue tracker, Issue trackers, Label correctness, Labelings, Language model, Model quality, Modeling quality, Open science, SP1, WP4},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Leveraging GPT-like LLMs to Automate Issue Labeling.\n \n \n \n \n\n\n \n Colavito, G.; Lanubile, F.; Novielli, N.; and Quaranta, L.\n\n\n \n\n\n\n In Proc. - IEEE/ACM Int. Conf. Min. Softw. Repos., MSR, pages 469–480, 2024. Institute of Electrical and Electronics Engineers Inc.\n Journal Abbreviation: Proc. - IEEE/ACM Int. Conf. Min. Softw. Repos., MSR\n\n\n\n
\n\n\n\n \n \n $\"Leveraging$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{colavito_leveraging_2024,\n\ttitle = {Leveraging {GPT}-like {LLMs} to {Automate} {Issue} {Labeling}},\n\tisbn = {979-840070587-8 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197463687&doi=10.1145%2f3643991.3644903&partnerID=40&md5=2c66959db54a3e5c1093465a2ce81c8b},\n\tdoi = {10.1145/3643991.3644903},\n\tabstract = {Issue labeling is a crucial task for the effective management of software projects. To date, several approaches have been put forth for the automatic assignment of labels to issue reports. In particular, supervised approaches based on the fine-tuning of BERT-like language models have been proposed, achieving state-of-the-art performance. More recently, decoder-only models such as GPT have become prominent in SE research due to their surprising capabilities to achieve state-of-the-art performance even for tasks they have not been trained for. To the best of our knowledge, GPT-like models have not been applied yet to the problem of issue classification, despite the promising results achieved for many other software engineering tasks. In this paper, we investigate to what extent we can leverage GPT-like LLMs to automate the issue labeling task. Our results demonstrate the ability of GPT-like models to correctly classify issue reports in the absence of labeled data that would be required to fine-tune BERT-like LLMs.CCS CONCEPTS• Software and its engineering → Documentation; Software evolution; Maintaining software; • Information systems → Clustering and classification;  © 2024 ACM.},\n\tlanguage = {English},\n\tbooktitle = {Proc. - {IEEE}/{ACM} {Int}. {Conf}. {Min}. {Softw}. {Repos}., {MSR}},\n\tpublisher = {Institute of Electrical and Electronics Engineers Inc.},\n\tauthor = {Colavito, G. and Lanubile, F. and Novielli, N. and Quaranta, L.},\n\tyear = {2024},\n\tnote = {Journal Abbreviation: Proc. - IEEE/ACM Int. Conf. Min. Softw. Repos., MSR},\n\tkeywords = {Classification (of information), Effective management, GPT, Issue Labeling, Issue labeling, LLM, Labeling Unstructured Data, Labeling unstructured data, Labelings, SP1, Software Maintenance and Evolution, Software engineering, Software maintenance and evolution, State-of-the-art performance, Unstructured data, WP4},\n\tpages = {469--480},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Children with perinatally acquired HIV exhibit distinct immune responses to 4CMenB vaccine.\n \n \n \n \n\n\n \n Cotugno, N.; Neri, A.; Sanna, M.; Santilli, V.; Manno, E.; Pascucci, G.; Morrocchi, E.; Amodio, D.; Ruggiero, A.; degl Atti, M.; Barneschi, I.; Grappi, S.; Cocchi, I.; Giacomet, V.; Trabattoni, D.; Olivieri, G.; Bernardi, S.; O’Connor, D.; Montomoli, E.; Pollard, A.; and Palma, P.\n\n\n \n\n\n\n JCI Insight, 9(10). 2024.\n Number: 10\n\n\n\n
\n\n\n\n \n \n $\"Children$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cotugno_children_2024,\n\ttitle = {Children with perinatally acquired {HIV} exhibit distinct immune responses to {4CMenB} vaccine},\n\tvolume = {9},\n\tissn = {23793708 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194024095&doi=10.1172%2fjci.insight.177182&partnerID=40&md5=67f0c7b2345f7f480b86710e52657afb},\n\tdoi = {10.1172/jci.insight.177182},\n\tabstract = {Children with perinatally acquired HIV (PHIV) have special vaccination needs, as they make suboptimal immune responses. Here, we evaluated safety and immunogenicity of 2 doses of 4-component group B meningococcal vaccine in antiretroviral therapy–treated children with PHIV and healthy controls (HCs). Assessments included the standard human serum bactericidal antibody (hSBA) assay and measurement of IgG titers against capsular group B Neisseria meningitidis antigens (fHbp, NHBA, NadA). The B cell compartment and vaccine-induced antigen-specific (fHbp+) B cells were investigated by flow cytometry, and gene expression was investigated by multiplexed real-time PCR. A good safety and immunogenicity profile was shown in both groups; however, PHIV demonstrated a reduced immunogenicity compared with HCs. Additionally, PHIV showed a reduced frequency of fHbp+ and an altered B cell subset distribution, with higher fHbp+ frequency in activated memory and tissue-like memory B cells. Gene expression analyses on these cells revealed distinct mechanisms between PHIV and HC seroconverters. Overall, these data suggest that PHIV presents a diverse immune signature following vaccination. The impact of such perturbation on long-term maintenance of vaccine-induced immunity should be further evaluated in vulnerable populations, such as people with PHIV. © 2024, Cotugno et al.},\n\tlanguage = {English},\n\tnumber = {10},\n\tjournal = {JCI Insight},\n\tpublisher = {American Society for Clinical Investigation},\n\tauthor = {Cotugno, N. and Neri, A. and Sanna, M. and Santilli, V. and Manno, E.C. and Pascucci, G.R. and Morrocchi, E. and Amodio, D. and Ruggiero, A. and degl Atti, M.L.C. and Barneschi, I. and Grappi, S. and Cocchi, I. and Giacomet, V. and Trabattoni, D. and Olivieri, G. and Bernardi, S. and O’Connor, D. and Montomoli, E. and Pollard, A.J. and Palma, P.},\n\tyear = {2024},\n\tnote = {Number: 10},\n\tkeywords = {Antibodies, Bacterial, Article, B lymphocyte, B-Lymphocytes, CD4+ T lymphocyte, Child, Child, Preschool, Female, HIV Infections, Human immunodeficiency virus, Human immunodeficiency virus infection, Humans, Immunogenicity, Vaccine, Immunoglobulin G, Infectious Disease Transmission, Vertical, Male, Meningococcal Infections, Meningococcal Vaccines, Meningococcus vaccine, Neisseria meningitidis, SP3, STAT3 protein, WP3, acute disease, adolescent, adult, adverse event, antiretroviral therapy, arthralgia, bacterium antibody, blood, centrifugation, child, colony forming unit, controlled study, data availability, enzyme linked immunosorbent assay, erythema, female, fever, flow cytometry, gene expression, gene ontology, headache, human, immune response, immunoglobulin, immunoglobulin G, immunology, loss of appetite, lymphoproliferative disease, major clinical study, male, meningococcosis, myalgia, myelodysplastic syndrome, nausea, pain, perinatally acquired Human immunodeficiency virus, preschool child, prevention and control, real time polymerase chain reaction, serum bactericidal antibody assay, skin induration, swelling, tripartite motif protein 5, vaccination, vaccine immunogenicity, vertical transmission},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Enhancing early Parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database.\n \n \n \n \n\n\n \n Dentamaro, V.; Impedovo, D.; Musti, L.; Pirlo, G.; and Taurisano, P.\n\n\n \n\n\n\n Scientific Reports, 14(1): 20941. September 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Enhancing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{dentamaro_enhancing_2024,\n\ttitle = {Enhancing early {Parkinson}’s disease detection through multimodal deep learning and explainable {AI}: insights from the {PPMI} database},\n\tvolume = {14},\n\tcopyright = {2024 The Author(s)},\n\tissn = {2045-2322},\n\tshorttitle = {Enhancing early {Parkinson}’s disease detection through multimodal deep learning and explainable {AI}},\n\turl = {https://www.nature.com/articles/s41598-024-70165-4},\n\tdoi = {10.1038/s41598-024-70165-4},\n\tabstract = {Parkinson’s is the second most common neurodegenerative disease, affecting nearly 8.5M people and steadily increasing. In this research, Multimodal Deep Learning is investigated for the Prodromal stage detection of Parkinson's Disease (PD), combining different 3D architectures with the novel Excitation Network (EN) and supported by Explainable Artificial Intelligence (XAI) techniques. Utilizing data from the Parkinson’s Progression Markers Initiative, this study introduces a joint co-learning approach for multimodal fusion, enabling end-to-end training of deep neural networks and facilitating the learning of complementary information from both imaging and clinical modalities. DenseNet with EN outperformed other models, showing a substantial increase in accuracy when supplemented with clinical data. XAI methods, such as Integrated Gradients for ResNet and DenseNet, and Attention Heatmaps for Vision Transformer (ViT), revealed that DenseNet focused on brain regions believed to be critical to prodromal pathophysiology, including the right temporal and left pre-frontal areas. Similarly, ViT highlighted the lateral ventricles associated with cognitive decline, indicating their potential in the Prodromal stage. These findings underscore the potential of these regions as early-stage PD biomarkers and showcase the proposed framework's efficacy in predicting subtypes of PD and aiding in early diagnosis, paving the way for innovative diagnostic tools and precision medicine.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-10-03},\n\tjournal = {Scientific Reports},\n\tpublisher = {Nature Publishing Group},\n\tauthor = {Dentamaro, Vincenzo and Impedovo, Donato and Musti, Luca and Pirlo, Giuseppe and Taurisano, Paolo},\n\tmonth = sep,\n\tyear = {2024},\n\tkeywords = {Computational science, Computer science, Neurodegenerative diseases, SP1, Scientific data, Software, WP4},\n\tpages = {20941},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A method for the synchronization of inertial sensor signals and local field potentials from deep brain stimulation systems.\n \n \n \n \n\n\n \n D’Ascanio, I.; Giannini, G.; Baldelli, L.; Cani, I.; Giannoni, A.; Leogrande, G.; Lopane, G.; Calandra-Buonaura, G.; Cortelli, P.; Chiari, L.; and Palmerini, L.\n\n\n \n\n\n\n Biomedical Physics and Engineering Express, 10(5). 2024.\n Number: 5\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{dascanio_method_2024,\n\ttitle = {A method for the synchronization of inertial sensor signals and local field potentials from deep brain stimulation systems},\n\tvolume = {10},\n\tissn = {20571976 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199125743&doi=10.1088%2f2057-1976%2fad5e83&partnerID=40&md5=70ee413b6fd4703e8df523a5f4b9928a},\n\tdoi = {10.1088/2057-1976/ad5e83},\n\tabstract = {Objective. Recent innovative neurostimulators allow recording local field potentials (LFPs) while performing motor tasks monitored by wearable sensors. Inertial sensors can provide quantitative measures of motor impairment in people with subthalamic nucleus deep brain stimulation. To the best of our knowledge, there is no validated method to synchronize inertial sensors and neurostimulators without an additional device. This study aims to define a new synchronization method to analyze disease-related brain activity patterns during specific motor tasks and evaluate how LFPs are affected by stimulation and medication. Approach. Fourteen male subjects treated with subthalamic nucleus deep brain stimulation were recruited to perform motor tasks in four different medication and stimulation conditions. In each condition, a synchronization protocol was performed consisting of taps on the implanted neurostimulator, which produces artifacts in the LFPs that a nearby inertial sensor can simultaneously record. Main results. In 64\\% of the recruited subjects, induced artifacts were detected at least in one condition. Among those subjects, 83\\% of the recordings could be synchronized offline analyzing LFPs and wearables data. The remaining recordings were synchronized by video analysis. Significance. The proposed synchronization method does not require an external system (e.g., TENS electrodes) and can be easily integrated into clinical practice. The procedure is simple and can be carried out in a short time. A proper and simple synchronization will also be useful to analyze subthalamic neural activity in the presence of specific events (e.g., freezing of gait events) to identify predictive biomarkers. © 2024 The Author(s). Published by IOP Publishing Ltd.},\n\tlanguage = {English},\n\tnumber = {5},\n\tjournal = {Biomedical Physics and Engineering Express},\n\tpublisher = {Institute of Physics},\n\tauthor = {D’Ascanio, I. and Giannini, G. and Baldelli, L. and Cani, I. and Giannoni, A. and Leogrande, G. and Lopane, G. and Calandra-Buonaura, G. and Cortelli, P. and Chiari, L. and Palmerini, L.},\n\tyear = {2024},\n\tnote = {Number: 5},\n\tkeywords = {Adult, Aged, Artifacts, Brain, Condition, Deep Brain Stimulation, Deep brain stimulation, Electrophysiology, Humans, Inertial navigation systems, Inertial sensor, Local field potentials, Male, Middle Aged, Motor tasks, Neurons, Neurostimulators, Parkinson Disease, Parkinson disease, Parkinson’s disease, SP1, Signal Processing, Computer-Assisted, Simple++, Subthalamic Nucleus, Subthalamic nucleus, Synchronization, Synchronization method, Taps, WP4, Wearable Electronic Devices, Wearable sensors, adult, aged, artifact, biological marker, brain, brain depth stimulation, clinical practice, controlled study, deep brain stimulation, deep brain stimulator, devices, electrode, electroencephalogram, freezing of gait, human, implantable neurostimulator, inertial sensor, local field potential, male, middle aged, motor dysfunction, nerve stimulator, pathophysiology, procedures, protocol, review, signal processing, subthalamic nucleus, subthalamus, synchronization, thalamus ventral nucleus, therapy, videorecording, wearable computer, wearable device, wearable sensor, wearable sensors},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Comprehensive analysis of clinical outcomes, infectious complications and microbiological data in newly diagnosed multiple myeloma patients: a retrospective observational study of 92 subjects.\n \n \n \n \n\n\n \n Desantis, V.; Borrelli, P.; Panebianco, T.; Fusillo, A.; Bochicchio, D.; Solito, A.; Pappagallo, F.; Mascolo, A.; Ancona, A.; Cicco, S.; Cerchione, C.; Romano, A.; Montagnani, M.; Ria, R.; Vacca, A.; and Solimando, A.\n\n\n \n\n\n\n Clinical and Experimental Medicine, 24(1). 2024.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"Comprehensive$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{desantis_comprehensive_2024,\n\ttitle = {Comprehensive analysis of clinical outcomes, infectious complications and microbiological data in newly diagnosed multiple myeloma patients: a retrospective observational study of 92 subjects},\n\tvolume = {24},\n\tissn = {15918890 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197118816&doi=10.1007%2fs10238-024-01411-2&partnerID=40&md5=1d60923564cafd2396b4e0c613262843},\n\tdoi = {10.1007/s10238-024-01411-2},\n\tabstract = {Patients with multiple myeloma (MM) have an increased risk of sepsis due to underlying disease- and treatment-related immunosuppression. However, data on sepsis incidence, causative pathogens, and impact on outcomes in newly diagnosed MM (NDMM) are limited. We conducted a retrospective observational study of 92 NDMM patients who developed sepsis between 2022 and 2023 at a tertiary care center in Italy. Patient characteristics, sepsis criteria [Quick Sequential Organ Failure Assessment, Systemic Inflammatory Response Syndrome (SIRS)], microbiology results, and associations with progression-free survival (PFS) were analyzed. In this cohort of 92 critically-ill patients, pathogenic organisms were identified via microbiological culture in 74 cases. However, among the remaining 18 culture-negative patients, 9 exhibited a SIRS score of 2 and another 9 had a SIRS score of 4, suggestive of a clinical presentation consistent with sepsis despite negative cultures. Common comorbidities included renal failure (60\\%), anemia (71\\%), and bone disease (83\\%). Gram-negative (28\\%) and Gram-positive (23\\%) bacteria were frequent causative organisms, along with fungi (20\\%). Cox Univariate analyses for PFS showed statically significant HR in patients with albumin ≥ 3.5 vs {\\textless} 3.5 (HR = 5.04, p {\\textless} 0.001), Karnofsky performance status ≥ 80 vs {\\textless} 80 (HR = 2.01, p = 0.002), and early-stage vs late-stage disease by International Staging System (HR = 4.76 and HR = 12.52, both p {\\textless} 0.001) and Revised International Staging System (R-ISS III vs R-ISS I, HR = 7.38, p {\\textless} 0.001). Sepsis is common in NDMM and associated with poor outcomes. Risk stratification incorporating sepsis severity, comorbidities, and disease stage may help guide preventive strategies and optimize MM management. © The Author(s) 2024.},\n\tlanguage = {English},\n\tnumber = {1},\n\tjournal = {Clinical and Experimental Medicine},\n\tpublisher = {Springer Science and Business Media Deutschland GmbH},\n\tauthor = {Desantis, V. and Borrelli, P. and Panebianco, T. and Fusillo, A. and Bochicchio, D. and Solito, A. and Pappagallo, F. and Mascolo, A. and Ancona, A. and Cicco, S. and Cerchione, C. and Romano, A. and Montagnani, M. and Ria, R. and Vacca, A. and Solimando, A.G.},\n\tyear = {2024},\n\tnote = {Number: 1},\n\tkeywords = {Adult, Aged, Aged, 80 and over, Anti-CD38 antibody therapy, Article, Female, Humans, International Staging System, Italy, Karnofsky Performance Status, Listeria monocytogenes, Male, Middle Aged, Multiple Myeloma, Multiple myeloma, Retrospective Studies, SP3, Sepsis, Septic shock, Sequential Organ Failure Assessment Score, Tertiary Care Centers, WP3, aciclovir, adult, aged, albumin, anemia, bone disease, cancer diagnosis, cancer survival, cefazolin, clinical outcome, comorbidity, complication, controlled study, critically ill patient, daptomycin, demographics, epidemiology, female, follow up, health care quality, human, infectious complication, informed consent, kidney failure, major clinical study, male, microbiology, middle aged, multiple myeloma, observational study, oxacillin, progression free survival, proteasome inhibitor, retrospective study, sepsis, septic shock, sulfamethoxazole, systemic inflammatory response syndrome, teicoplanin, tertiary care center, trimethoprim, vancomycin, very elderly},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Lactobacilli Cell-Free Supernatants Modulate Inflammation and Oxidative Stress in Human Microglia via NRF2-SOD1 Signaling.\n \n \n \n \n\n\n \n Di Chiano, M.; Rocchetti, M. T.; Spano, G.; Russo, P.; Allegretta, C.; Milior, G.; Gadaleta, R. M.; Sallustio, F.; Pontrelli, P.; Gesualdo, L.; Avolio, C.; Fiocco, D.; and Gallone, A.\n\n\n \n\n\n\n Cellular and Molecular Neurobiology, 44(1): 60. September 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Lactobacilli$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{di_chiano_lactobacilli_2024,\n\ttitle = {Lactobacilli {Cell}-{Free} {Supernatants} {Modulate} {Inflammation} and {Oxidative} {Stress} in {Human} {Microglia} via {NRF2}-{SOD1} {Signaling}},\n\tvolume = {44},\n\tissn = {1573-6830},\n\turl = {https://doi.org/10.1007/s10571-024-01494-1},\n\tdoi = {10.1007/s10571-024-01494-1},\n\tabstract = {Microglia are macrophage cells residing in the brain, where they exert a key role in neuronal protection. Through the gut–brain axis, metabolites produced by gut commensal microbes can influence brain functions, including microglial activity. The nuclear factor erythroid 2-related factor 2 (NRF2) is a key regulator of the oxidative stress response in microglia, controlling the expression of cytoprotective genes. Lactobacilli-derived cell-free supernatants (CFSs) are postbiotics that have shown antioxidant and immunomodulatory effects in several in vitro and in vivo studies. This study aimed to explore the effects of lactobacilli CFSs on modulating microglial responses against oxidative stress and inflammation. HMC3 microglia were exposed to lipopolysaccaride (LPS), as an inflammatory trigger, before and after administration of CFSs from three human gut probiotic species. The NRF2 nuclear protein activation and the expression of NRF2-controlled antioxidant genes were investigated by immunoassay and quantitative RT-PCR, respectively. Furthermore, the level of pro- and anti-inflammatory cytokines was evaluated by immunoassay. All CFSs induced a significant increase of NRF2 nuclear activity in basal conditions and upon inflammation. The transcription of antioxidant genes, namely heme oxygenase 1, superoxide dismutase (SOD), glutathione-S transferase, glutathione peroxidase, and catalase also increased, especially after inflammatory stimulus. Besides, higher SOD1 activity was detected relative to inflamed microglia. In addition, CFSs pre-treatment of microglia attenuated pro-inflammatory TNF-α levels while increasing anti-inflammatory IL-10 levels. These findings confirmed that gut microorganisms’ metabolites can play a relevant role in adjuvating the microglia cellular response against neuroinflammation and oxidative stress, which are known to cause neurodegenerative diseases.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-10-03},\n\tjournal = {Cellular and Molecular Neurobiology},\n\tauthor = {Di Chiano, Mariagiovanna and Rocchetti, Maria Teresa and Spano, Giuseppe and Russo, Pasquale and Allegretta, Caterina and Milior, Giampaolo and Gadaleta, Raffaella Maria and Sallustio, Fabio and Pontrelli, Paola and Gesualdo, Loreto and Avolio, Carlo and Fiocco, Daniela and Gallone, Anna},\n\tmonth = sep,\n\tyear = {2024},\n\tkeywords = {Cytokines, Gut–brain axis, LPS, Lactobacilli CFS, NRF2, Postbiotics, SP3, WP5},\n\tpages = {60},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.\n \n \n \n \n\n\n \n Hoang, M.; Matrella, G.; and Ciampolini, P.\n\n\n \n\n\n\n Sensors, 24(6). 2024.\n Number: 6\n\n\n\n
\n\n\n\n \n \n $\"Comparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{hoang_comparison_2024,\n\ttitle = {Comparison of {Machine} {Learning} {Algorithms} for {Heartbeat} {Detection} {Based} on {Accelerometric} {Signals} {Produced} by a {Smart} {Bed}},\n\tvolume = {24},\n\tissn = {14248220 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188939464&doi=10.3390%2fs24061900&partnerID=40&md5=4213af4d2d9b673b8b3415e344bccc16},\n\tdoi = {10.3390/s24061900},\n\tabstract = {This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users’ heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed through an STM 32-bit microcontroller board and transmitted to a PC for recording. A photoplethysmographic sensor is simultaneously checked for ground truth reference. A dataset has been built, by acquiring measures in a real-world set-up: 10 participants were involved, resulting in 120 min of acceleration traces which were utilized to train and evaluate various Artificial Intelligence (AI) algorithms. The experimental analysis utilizes K-fold cross-validation to ensure robust model testing across different subsets of the dataset. Various ML and DL algorithms are compared, each being trained and tested using the collected data. The Random Forest algorithm exhibited the highest accuracy among all compared models. While it requires longer training time compared to some ML models such as Naïve Bayes, Linear Discrimination Analysis, and K-Nearest Neighbour Classification, it keeps substantially faster than Support Vector Machine and Deep Learning models. The Random Forest model demonstrated robust performance metrics, including recall, precision, F1-scores, macro average, weighted average, and overall accuracy well above 90\\%. The study highlights the better performance of the Random Forest algorithm for the specific use case, achieving superior accuracy and performance metrics in detecting user heartbeats in comparison to other ML and DL models tested. The drawback of longer training times is not too relevant in the long-term monitoring target scenario, so the Random Forest model stands out as a viable solution for real-time ballistocardiographic heartbeat detection, showcasing potential for healthcare and wellness monitoring applications. © 2024 by the authors.},\n\tlanguage = {English},\n\tnumber = {6},\n\tjournal = {Sensors},\n\tpublisher = {Multidisciplinary Digital Publishing Institute (MDPI)},\n\tauthor = {Hoang, M.L. and Matrella, G. and Ciampolini, P.},\n\tyear = {2024},\n\tnote = {Number: 6},\n\tkeywords = {Acceleration, Accelerometer sensor, Accelerometers, Algorithms, Artificial Intelligence, Artificial intelligence algorithms, Bayes Theorem, Bayes theorem, Deep learning, Forestry, Heart Rate, Heart beat detections, Humans, Learning algorithms, Learning models, Learning systems, Machine Learning, Machine-learning, Nearest neighbor search, Performance, Random forest algorithm, SP1, Smart beds, Statistical tests, Support Vector Machine, Support vector machines, Training time, WP4, accelerometer sensor, algorithm, artificial intelligence, artificial intelligence algorithm, deep learning, heart rate, heartbeat detection, human, machine learning, smart bed, support vector machine},\n}\n\n\n\n\n\n\n\n

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\n This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users’ heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed through an STM 32-bit microcontroller board and transmitted to a PC for recording. A photoplethysmographic sensor is simultaneously checked for ground truth reference. A dataset has been built, by acquiring measures in a real-world set-up: 10 participants were involved, resulting in 120 min of acceleration traces which were utilized to train and evaluate various Artificial Intelligence (AI) algorithms. The experimental analysis utilizes K-fold cross-validation to ensure robust model testing across different subsets of the dataset. Various ML and DL algorithms are compared, each being trained and tested using the collected data. The Random Forest algorithm exhibited the highest accuracy among all compared models. While it requires longer training time compared to some ML models such as Naïve Bayes, Linear Discrimination Analysis, and K-Nearest Neighbour Classification, it keeps substantially faster than Support Vector Machine and Deep Learning models. The Random Forest model demonstrated robust performance metrics, including recall, precision, F1-scores, macro average, weighted average, and overall accuracy well above 90%. The study highlights the better performance of the Random Forest algorithm for the specific use case, achieving superior accuracy and performance metrics in detecting user heartbeats in comparison to other ML and DL models tested. The drawback of longer training times is not too relevant in the long-term monitoring target scenario, so the Random Forest model stands out as a viable solution for real-time ballistocardiographic heartbeat detection, showcasing potential for healthcare and wellness monitoring applications. © 2024 by the authors.\n

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\n \n\n \n \n \n \n \n \n A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions.\n \n \n \n \n\n\n \n Kumar, B.; Lorusso, E.; Fosso, B.; and Pesole, G.\n\n\n \n\n\n\n Frontiers in Microbiology, 15. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kumar_comprehensive_2024,\n\ttitle = {A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions},\n\tvolume = {15},\n\tissn = {1664302X (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185912167&doi=10.3389%2ffmicb.2024.1343572&partnerID=40&md5=1b619be2a17664bffd46d626eff8b51f},\n\tdoi = {10.3389/fmicb.2024.1343572},\n\tabstract = {Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development. Copyright © 2024 Kumar, Lorusso, Fosso and Pesole.},\n\tlanguage = {English},\n\tjournal = {Frontiers in Microbiology},\n\tpublisher = {Frontiers Media SA},\n\tauthor = {Kumar, B. and Lorusso, E. and Fosso, B. and Pesole, G.},\n\tyear = {2024},\n\tkeywords = {DNA sequence, RNA 16S, RNA sequence, Review, SP3, WP4, adulthood, amplicon, antibiotic therapy, bacterium, biological activity, comprehension, contamination, data accuracy, data analysis, data quality assessment, disease prediction, diversity index, fungus, gene expression, gene sequence, high throughput sequencing, inflammatory bowel disease, laboratory test, machine learning, metabolomics, metadata, metagenome, metagenomics, metaproteomics, metatranscriptomics, microbial activity, microbiome, nonhuman, phenotype, polymerase chain reaction, prokaryotic cell, reproducibility, short chain fatty acid, shotgun sequencing},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Evidence, my Dear Watson: Abstractive dialogue summarization on learnable relevant utterances.\n \n \n \n \n\n\n \n Italiani, P.; Frisoni, G.; Moro, G.; Carbonaro, A.; and Sartori, C.\n\n\n \n\n\n\n Neurocomputing, 572. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Evidence,$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{italiani_evidence_2024,\n\ttitle = {Evidence, my {Dear} {Watson}: {Abstractive} dialogue summarization on learnable relevant utterances},\n\tvolume = {572},\n\tissn = {09252312 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181762400&doi=10.1016%2fj.neucom.2023.127132&partnerID=40&md5=74781956f754f3f5b5c52922cfc0e639},\n\tdoi = {10.1016/j.neucom.2023.127132},\n\tabstract = {Abstractive dialogue summarization requires distilling and rephrasing key information from noisy multi-speaker documents. Combining pre-trained language models with input augmentation techniques has recently led to significant research progress. However, existing solutions still struggle to select relevant chat segments, primarily relying on open-domain and unsupervised annotators not tailored to the actual needs of the summarization task. In this paper, we propose DEARWATSON, a task-aware utterance-level annotation framework for improving the effectiveness and interpretability of pre-trained dialogue summarization models. Precisely, we learn relevant utterances in the source document and mark them with special tags, that then act as supporting evidence for the generated summary. Quantitative experiments are conducted on two datasets made up of real-life messenger conversations. The results show that DEARWATSON allows model attention to focus on salient tokens, achieving new state-of-the-art results in three evaluation metrics, including semantic and factuality measures. Human evaluation proves the superiority of our solution in semantic consistency and recall. Finally, extensive ablation studies confirm each module's importance, also exploring different annotation strategies and parameter-efficient fine-tuning of large generative language models. © 2023 The Author(s)},\n\tlanguage = {English},\n\tjournal = {Neurocomputing},\n\tpublisher = {Elsevier B.V.},\n\tauthor = {Italiani, P. and Frisoni, G. and Moro, G. and Carbonaro, A. and Sartori, C.},\n\tyear = {2024},\n\tkeywords = {Abstractive dialog summarization, Abstractive dialogue summarization, Augmentation techniques, Classification (of information), Computational linguistics, Gumbel-softmax trick, Input augmentation, Interpretable natural language processing, Language model, Language processing, Natural language processing systems, Natural languages, SP1, Semantics, Task-aware, Text classification, Text processing, WP4, article, benchmarking, classification, conversation, human, language model, natural language processing},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Training Future Machine Learning Engineers: A Project-Based Course on MLOps.\n \n \n \n \n\n\n \n Lanubile, F.; Martinez-Fernandez, S.; and Quaranta, L.\n\n\n \n\n\n\n IEEE Software, 41(2): 60–67. 2024.\n Number: 2\n\n\n\n
\n\n\n\n \n \n $\"Training$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{lanubile_training_2024,\n\ttitle = {Training {Future} {Machine} {Learning} {Engineers}: {A} {Project}-{Based} {Course} on {MLOps}},\n\tvolume = {41},\n\tissn = {07407459 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171588752&doi=10.1109%2fMS.2023.3310768&partnerID=40&md5=b6ad26ba8688de84b81b71003130bc93},\n\tdoi = {10.1109/MS.2023.3310768},\n\tabstract = {In this paper, we present an overview of a project-based course on MLOps by showcasing a couple of sample projects developed by our students. Additionally, we share the lessons learned from offering the course at two different institutions.  © 1984-2012 IEEE.},\n\tlanguage = {English},\n\tnumber = {2},\n\tjournal = {IEEE Software},\n\tpublisher = {IEEE Computer Society},\n\tauthor = {Lanubile, F. and Martinez-Fernandez, S. and Quaranta, L.},\n\tyear = {2024},\n\tnote = {Number: 2},\n\tkeywords = {Code, Engineers, Job market, Personnel training, Project-based course, Reproducibilities, Reproducibility of result, SP1, Software engineering, Traditional computers, University course, WP4},\n\tpages = {60--67},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients.\n \n \n \n \n\n\n \n Lawn, T.; Giacomel, A.; Martins, D.; Veronese, M.; Howard, M.; Turkheimer, F.; and Dipasquale, O.\n\n\n \n\n\n\n Communications Biology, 7(1). 2024.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"Normative$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{lawn_normative_2024,\n\ttitle = {Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients},\n\tvolume = {7},\n\tissn = {23993642 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195351262&doi=10.1038%2fs42003-024-06391-3&partnerID=40&md5=0c01df470db8945dfd7cb447899aa1c0},\n\tdoi = {10.1038/s42003-024-06391-3},\n\tabstract = {Advanced methods such as REACT have allowed the integration of fMRI with the brain’s receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments. © The Author(s) 2024.},\n\tlanguage = {English},\n\tnumber = {1},\n\tjournal = {Communications Biology},\n\tpublisher = {Nature Research},\n\tauthor = {Lawn, T. and Giacomel, A. and Martins, D. and Veronese, M. and Howard, M. and Turkheimer, F.E. and Dipasquale, O.},\n\tyear = {2024},\n\tnote = {Number: 1},\n\tkeywords = {Adult, Attention Deficit Disorder with Hyperactivity, Bipolar Disorder, Brain, Female, Humans, Magnetic Resonance Imaging, Male, Mental Disorders, Middle Aged, Models, Neurological, Nerve Net, SP3, Schizophrenia, WP3, Young Adult, adult, attention deficit hyperactivity disorder, biological model, bipolar disorder, brain, diagnostic imaging, female, human, male, mental disease, middle aged, nerve cell network, nuclear magnetic resonance imaging, pathophysiology, schizophrenia, young adult},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Label-free electronic detection of peptide post-translational modification with functional enzyme-driven assay at the physical limit.\n \n \n \n \n\n\n \n Macchia, E.; Björkström, K.; Tewari, A.; Eskonen, V.; Luukkonen, A.; Ghafari, A.; Sarcina, L.; Caputo, M.; Tong-Ochoa, N.; Kopra, K.; Pettersson, F.; Gounani, Z.; Torsi, L.; Härmä, H.; and Österbacka, R.\n\n\n \n\n\n\n Cell Reports Physical Science. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Label-free$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{macchia_label-free_2024,\n\ttitle = {Label-free electronic detection of peptide post-translational modification with functional enzyme-driven assay at the physical limit},\n\tissn = {26663864 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189680655&doi=10.1016%2fj.xcrp.2024.101874&partnerID=40&md5=39133c5d69e151c175f9b31b05c3870d},\n\tdoi = {10.1016/j.xcrp.2024.101874},\n\tabstract = {High-performance, ultra-sensitive, and universal protein post-translational modification (PTM) and protein-protein interaction (PPI) technologies are eagerly pursued in the pharmaceutical industry and bioanalytical research. Novel PTM and PPI detection methods outperform traditional assays in scope and scalability, enabling the collection of information on multiple biochemical targets. Detecting peptides and proteins at the single-molecule level is done by utilizing nanosized transducing elements and assaying solutions at very high analyte concentrations, in the nanomolar range or higher. Here, a proof of principle of a biosensing platform for single-molecule PTM detection is demonstrated. This platform is based on the single molecule with a large transistor (SiMoT) technology, encompassing a millimeter-sized electrolyte-gated organic field-effect transistor, for label-free PTM detection with a zeptomolar limit of detection. Sensitivity is improved 106- to 1012-fold compared with mass-spectrometry and luminescence-based assay methods. A functional assay for detecting enzyme-driven peptide PTMs in the zeptomolar concentration range is demonstrated using multivariate data processing, opening the way for future applications to monitor PTMs. © 2024 The Author(s)},\n\tlanguage = {English},\n\tjournal = {Cell Reports Physical Science},\n\tpublisher = {Cell Press},\n\tauthor = {Macchia, E. and Björkström, K. and Tewari, A. and Eskonen, V. and Luukkonen, A. and Ghafari, A.M. and Sarcina, L. and Caputo, M. and Tong-Ochoa, N. and Kopra, K. and Pettersson, F. and Gounani, Z. and Torsi, L. and Härmä, H. and Österbacka, R.},\n\tyear = {2024},\n\tkeywords = {SP3, SiMoT, WP4, multivariate data processing, organic bioelectronics, peptide detection, single-molecule assay with large transistors, single-molecule detection},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Point-Of-Care Ultra-Portable Single-Molecule Bioassays for One-Health.\n \n \n \n \n\n\n \n Macchia, E.; Torricelli, F.; Caputo, M.; Sarcina, L.; Scandurra, C.; Bollella, P.; Catacchio, M.; Piscitelli, M.; Di Franco, C.; Scamarcio, G.; and Torsi, L.\n\n\n \n\n\n\n Advanced Materials, 36(13). 2024.\n Number: 13\n\n\n\n
\n\n\n\n \n \n $\"Point-Of-Care$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{macchia_point--care_2024,\n\ttitle = {Point-{Of}-{Care} {Ultra}-{Portable} {Single}-{Molecule} {Bioassays} for {One}-{Health}},\n\tvolume = {36},\n\tissn = {09359648 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180656497&doi=10.1002%2fadma.202309705&partnerID=40&md5=d6dec205f7aaea7249a542f255281e68},\n\tdoi = {10.1002/adma.202309705},\n\tabstract = {Screening asymptomatic organisms (humans, animals, plants) with a high-diagnostic accuracy using point-of-care-testing (POCT) technologies, though still visionary holds great potential. Convenient surveillance requires easy-to-use, cost-effective, ultra-portable but highly reliable, in-vitro-diagnostic devices that are ready for use wherever they are needed. Currently, there are not yet such devices available on the market, but there are a couple more promising technologies developed at readiness-level 5: the Clustered-Regularly-Interspaced-Short-Palindromic-Repeats (CRISPR) lateral-flow-strip tests and the Single-Molecule-with-a-large-Transistor (SiMoT) bioelectronic palmar devices. They both hold key features delineated by the World-Health-Organization for POCT systems and an occurrence of false-positive and false-negative errors {\\textless}1–5\\% resulting in diagnostic-selectivity and sensitivity {\\textgreater}95–99\\%, while limit-of-detections are of few markers. CRISPR-strip is a molecular assay that, can detect down to few copies of DNA/RNA markers in blood while SiMoT immunometric and molecular test can detect down to a single oligonucleotide, protein marker, or pathogens in 0.1mL of blood, saliva, and olive-sap. These technologies can prospectively enable the systematic and reliable surveillance of asymptomatic ones prior to worsening/proliferation of illnesses allowing for timely diagnosis and swift prognosis. This could establish a proactive healthcare ecosystem that results in effective treatments for all living organisms generating diffuse and well-being at efficient costs. © 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.},\n\tlanguage = {English},\n\tnumber = {13},\n\tjournal = {Advanced Materials},\n\tpublisher = {John Wiley and Sons Inc},\n\tauthor = {Macchia, E. and Torricelli, F. and Caputo, M. and Sarcina, L. and Scandurra, C. and Bollella, P. and Catacchio, M. and Piscitelli, M. and Di Franco, C. and Scamarcio, G. and Torsi, L.},\n\tyear = {2024},\n\tnote = {Number: 13},\n\tkeywords = {Blood, Clustered regularly interspaced short palindromic repeat/cas, Cost effectiveness, Health care, Lateral Flow, Lateral flow strip test, Molecules, Oligonucleotides, One health, Palindromic, Point of care testing, Point-of-care testing, Preventing healthcare, SP3, Single molecule, Single-molecule with a large transistor(SiMoT), Single-molecule with a large transistor(single-molecule-with-a-large-transistor), WP4, clustered regularly interspaced short palindromic repeats/Cas (CRISPR/Cas), lateral flow strip test, one health, point of care testing (POCT), preventing healthcare},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging.\n \n \n \n \n\n\n \n Maccioni, L.; Michelle, C.; Brusaferri, L.; Silvestri, E.; Bertoldo, A.; Schubert, J.; Nettis, M.; Mondelli, V.; Howes, O.; Turkheimer, F.; Bottlaender, M.; Bodini, B.; Stankoff, B.; Loggia, M.; and Veronese, M.\n\n\n \n\n\n\n Frontiers in Neuroscience, 18. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{maccioni_blood-free_2024,\n\ttitle = {A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in {TSPO} {PET} imaging},\n\tvolume = {18},\n\tissn = {16624548 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200392667&doi=10.3389%2ffnins.2024.1395769&partnerID=40&md5=deb826647b335417fa9de81b8da8a843},\n\tdoi = {10.3389/fnins.2024.1395769},\n\tabstract = {Introduction: Recent evidence suggests the blood-to-brain influx rate (K1) in TSPO PET imaging as a promising biomarker of blood–brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test–retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03–0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers’ unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal. Copyright © 2024 Maccioni, Carranza Mellana, Brusaferri, Silvestri, Bertoldo, Schubert, Nettis, Mondelli, Howes, Turkheimer, Bottlaender, Bodini, Stankoff, Loggia and Veronese.},\n\tlanguage = {English},\n\tjournal = {Frontiers in Neuroscience},\n\tpublisher = {Frontiers Media SA},\n\tauthor = {Maccioni, L. and Michelle, C.M. and Brusaferri, L. and Silvestri, E. and Bertoldo, A. and Schubert, J.J. and Nettis, M.A. and Mondelli, V. and Howes, O. and Turkheimer, F.E. and Bottlaender, M. and Bodini, B. and Stankoff, B. and Loggia, M.L. and Veronese, M.},\n\tyear = {2024},\n\tkeywords = {Article, BBB, BOLD signal, DNA methylation, Doppler flowmetry, IDIF, PET, SP3, TSPO, TSPO gene, WP4, adult, biological marker, blood brain barrier, blood free modeling approach, brain perfusion, cardiovascular magnetic resonance, cesium 137, computer assisted tomography, controlled study, cytochrome c oxidase, dopamine transporter, female, gene, gray matter, human, hypoxia, image analysis, inflammation, insula, ischemia, kinetic modeling, knee osteoarthritis, major clinical study, male, middle aged, musculoskeletal pain, nervous system inflammation, neuroinflammation, pleocytosis, positron emission tomography, schizophrenia, signal noise ratio, volume of distribution, white matter},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n Introduction: Recent evidence suggests the blood-to-brain influx rate (K1) in TSPO PET imaging as a promising biomarker of blood–brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test–retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03–0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers’ unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal. Copyright © 2024 Maccioni, Carranza Mellana, Brusaferri, Silvestri, Bertoldo, Schubert, Nettis, Mondelli, Howes, Turkheimer, Bottlaender, Bodini, Stankoff, Loggia and Veronese.\n

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\n \n\n \n \n \n \n \n \n Representation of Machine Learning Models to Enhance Simulation Capabilities Within Digital Twins in Personalized Healthcare.\n \n \n \n \n\n\n \n Marfoglia, A.; Nardini, F.; Mellone, S.; and Carbonaro, A.\n\n\n \n\n\n\n In IEEE Int. Conf. Pervasive Comput. Commun. Workshops other Affil. Events, PerCom Workshops, pages 100–105, 2024. Institute of Electrical and Electronics Engineers Inc.\n Journal Abbreviation: IEEE Int. Conf. Pervasive Comput. Commun. Workshops other Affil. Events, PerCom Workshops\n\n\n\n
\n\n\n\n \n \n $\"Representation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{marfoglia_representation_2024,\n\ttitle = {Representation of {Machine} {Learning} {Models} to {Enhance} {Simulation} {Capabilities} {Within} {Digital} {Twins} in {Personalized} {Healthcare}},\n\tisbn = {979-835030436-7 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192491299&doi=10.1109%2fPerComWorkshops59983.2024.10502444&partnerID=40&md5=a3db1cdafa0cd1581b752002add187dc},\n\tdoi = {10.1109/PerComWorkshops59983.2024.10502444},\n\tabstract = {Healthcare has always been a strategic area where innovative technologies can be applied to increase the effectiveness of services and the quality of patient care. Recent progress has been made in the adoption of machine-learning models within digital twins and knowledge graphs. Nevertheless, their deployment needs to address the complex nature of the framework itself, which entails numerous technical, organizational, legal, and ethical challenges. In this paper, we propose an evolution of the CONNECTED conceptual framework, a multi-layered system in which heterogeneous data sources are integrated, standardized, and used to realize digital twins supported by knowledge graphs accessible through dedicated APIs. The extension involves the integration of machine learning models into digital twins, thereby enabling simulation capabilities. The inclusion of a formal and machine-readable self-description with these models serves as a foundation for semantic reasoning. This pivotal feature empowers our architecture with the capability for automatic indexing, aggregation, and querying of the models. © 2024 IEEE.},\n\tlanguage = {English},\n\tbooktitle = {{IEEE} {Int}. {Conf}. {Pervasive} {Comput}. {Commun}. {Workshops} other {Affil}. {Events}, {PerCom} {Workshops}},\n\tpublisher = {Institute of Electrical and Electronics Engineers Inc.},\n\tauthor = {Marfoglia, A. and Nardini, F. and Mellone, S. and Carbonaro, A.},\n\tyear = {2024},\n\tnote = {Journal Abbreviation: IEEE Int. Conf. Pervasive Comput. Commun. Workshops other Affil. Events, PerCom Workshops},\n\tkeywords = {Complex nature, Digital Twins, E-learning, Health care, Healthcare, Indexing (of information), Innovative technology, Knowledge graph, Knowledge graphs, Machine Learning Models, Machine learning, Machine learning models, Organisational, Patient care, Personal Knowledge Graphs, Personal knowledge graph, Personalized healthcare, Recent progress, SP1, Semantics, WP4},\n\tpages = {100--105},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Cross-sectional developmental trajectories in the adaptive functioning of children and adolescents with Down syndrome.\n \n \n \n \n\n\n \n Onnivello, S.; Locatelli, C.; Pulina, F.; Ramacieri, G.; Marcolin, C.; Antonaros, F.; Vione, B.; Catapano, F.; and Lanfranchi, S.\n\n\n \n\n\n\n Research in Developmental Disabilities, 144. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Cross-sectional$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{onnivello_cross-sectional_2024,\n\ttitle = {Cross-sectional developmental trajectories in the adaptive functioning of children and adolescents with {Down} syndrome},\n\tvolume = {144},\n\tissn = {08914222 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181019242&doi=10.1016%2fj.ridd.2023.104641&partnerID=40&md5=f78959ab1164b423833106d1c65dfb71},\n\tdoi = {10.1016/j.ridd.2023.104641},\n\tabstract = {Background: Persons with Down syndrome (DS) reveal adaptive functioning (AF) difficulties. Studies on AF in DS have focused mainly on describing the profile (i.e., strengths in socialization, and weaknesses in communication), while less is known about age-related differences. This study aimed to elucidate how AF changes with age in children and adolescents with DS, taking a cross-sectional developmental trajectory approach. Moreover, the contribution of both chronological age (CA) and mental age (MA) on AF development was explored. Method: This study involved 115 children and adolescents (between 3 and 16 years old) with DS. Parents were interviewed about their children's AF on communication, daily living and socialization skills. Children and adolescents with DS were assessed on their developmental level. Results: While participants’ standard scores on AF decreased linearly over time, their age-equivalent scores increased with linear or segmented patterns, depending on the skill considered. CA and MA were related to daily living skills and socialization to much the same degree, while MA correlated more strongly than CA with communication. Conclusion: This study contributes to the understanding of how AF develops in children and adolescents with DS, showing that CA and MA both contribute to shaping the skills involved. © 2023},\n\tlanguage = {English},\n\tjournal = {Research in Developmental Disabilities},\n\tpublisher = {Elsevier Inc.},\n\tauthor = {Onnivello, S. and Locatelli, C. and Pulina, F. and Ramacieri, G. and Marcolin, C. and Antonaros, F. and Vione, B. and Catapano, F. and Lanfranchi, S.},\n\tyear = {2024},\n\tkeywords = {Adaptive functioning, Adolescent, Article, Child, Child, Preschool, Communication, Cross-Sectional Studies, Developmental trajectories, Down Syndrome, Down syndrome, Humans, Intelligence, Italian (citizen), Italy, SP3, Socialization, WP3, adaptive behavior, adaptive functioning, adolescent, adolescent development, age, child, child development, controlled study, cross-sectional study, daily life activity, developmental trajectory, female, human, intelligence, interpersonal communication, interview, linear system, major clinical study, male, mental age, mental health, parent, preschool child, socialization},\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images.\n \n \n \n \n\n\n \n Piccinini, F.; Tazzari, M.; Tumedei, M.; Stellato, M.; Remondini, D.; Giampieri, E.; Martinelli, G.; Castellani, G.; and Carbonaro, A.\n\n\n \n\n\n\n Sensors, 24(2). 2024.\n Number: 2\n\n\n\n
\n\n\n\n \n \n $\"Data$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{piccinini_data_2024,\n\ttitle = {Data {Science} for {Health} {Image} {Alignment}: {A} {User}-{Friendly} {Open}-{Source} {ImageJ}/{Fiji} {Plugin} for {Aligning} {Multimodality}/{Immunohistochemistry}/{Immunofluorescence} {2D} {Microscopy} {Images}},\n\tvolume = {24},\n\tissn = {14248220 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183216886&doi=10.3390%2fs24020451&partnerID=40&md5=2b5f2e1059e75f28f5d2e52d8a475ad8},\n\tdoi = {10.3390/s24020451},\n\tabstract = {Most of the time, the deep analysis of a biological sample requires the acquisition of images at different time points, using different modalities and/or different stainings. This information gives morphological, functional, and physiological insights, but the acquired images must be aligned to be able to proceed with the co-localisation analysis. Practically speaking, according to Aristotle’s principle, “The whole is greater than the sum of its parts”, multi-modal image registration is a challenging task that involves fusing complementary signals. In the past few years, several methods for image registration have been described in the literature, but unfortunately, there is not one method that works for all applications. In addition, there is currently no user-friendly solution for aligning images that does not require any computer skills. In this work, DS4H Image Alignment (DS4H-IA), an open-source ImageJ/Fiji plugin for aligning multimodality, immunohistochemistry (IHC), and/or immunofluorescence (IF) 2D microscopy images, designed with the goal of being extremely easy to use, is described. All of the available solutions for aligning 2D microscopy images have also been revised. The DS4H-IA source code; standalone applications for MAC, Linux, and Windows; video tutorials; manual documentation; and sample datasets are publicly available. © 2024 by the authors.},\n\tlanguage = {English},\n\tnumber = {2},\n\tjournal = {Sensors},\n\tpublisher = {Multidisciplinary Digital Publishing Institute (MDPI)},\n\tauthor = {Piccinini, F. and Tazzari, M. and Tumedei, M.M. and Stellato, M. and Remondini, D. and Giampieri, E. and Martinelli, G. and Castellani, G. and Carbonaro, A.},\n\tyear = {2024},\n\tnote = {Number: 2},\n\tkeywords = {Computer operating systems, Correlative microscopies, Data Science, Documentation, Fluorescent Antibody Technique, Histology/histopathology, Image acquisition, Image alignment, Image analysis, Image registration, Images registration, Immunofluorescence techniques, Immunohistochemistry, Immunohistochemistry/immunofluorescence technique, Microscopy images, Microscopy, Fluorescence, Multi-modal, Multimodal micrograph, SP1, WP4, correlative microscopy, data science, documentation, fluorescence microscopy, fluorescent antibody technique, histology/histopathology, image registration, immunohistochemistry, immunohistochemistry/immunofluorescence techniques, multimodal micrographs},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Breast cancer classification through multivariate radiomic time series analysis in DCE-MRI sequences.\n \n \n \n \n\n\n \n Prinzi, F.; Orlando, A.; Gaglio, S.; and Vitabile, S.\n\n\n \n\n\n\n Expert Systems with Applications, 249. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Breast$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{prinzi_breast_2024,\n\ttitle = {Breast cancer classification through multivariate radiomic time series analysis in {DCE}-{MRI} sequences},\n\tvolume = {249},\n\tissn = {09574174 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186392770&doi=10.1016%2fj.eswa.2024.123557&partnerID=40&md5=a5c27c70f2831d641823048038fbcb36},\n\tdoi = {10.1016/j.eswa.2024.123557},\n\tabstract = {Breast cancer is the most prevalent disease that poses a significant threat to women's health. Despite the Dynamic Contrast-Enhanced MRI (DCE-MRI) has been widely used for breast cancer classification, its diagnostic performance is still suboptimal. In this work, the Radiomic workflow was implemented to classify the whole DCE-MRI sequence based on the distinction in contrast agent uptake between benign and malignant lesions. The radiomic features extracted from each of the seven time instants within the DCE-MRI sequence were fed into a multi-instant features selection strategy to select the discriminative features for time series classification. Several time series classification algorithms including Rocket, MultiRocket, K-Nearest Neighbor, Time Series Forest, and Supervised Time Series Forest were compared. Firstly, a univariate classification was performed to find the five most informative radiomic series, and then, a multivariate time series classification was implemented via a voting mechanism. The Multivariate Rocket model was the most accurate (Accuracy = 0.852, AUC-ROC = 0.852, Specificity = 0.823, Sensitivity = 0.882). The intelligible radiomic features enabled model findings explanations and clinical validation. In particular, the Energy and TotalEnergy were among the most important features, and the most descriptive for the change in signal intensity, which is the main effect of the contrast agent. © 2024 The Authors},\n\tlanguage = {English},\n\tjournal = {Expert Systems with Applications},\n\tpublisher = {Elsevier Ltd},\n\tauthor = {Prinzi, F. and Orlando, A. and Gaglio, S. and Vitabile, S.},\n\tyear = {2024},\n\tkeywords = {Breast cancer classifications, Classification (of information), Contrast agent, Diagnosis, Diseases, Dynamic contrast enhanced MRI, Explainable AI, Forestry, Harmonic analysis, Health risks, MRI sequences, Machine learning, Machine-learning, Nearest neighbor search, Radiomic, Radiomics, Rockets, SP1, Time series analysis, Time series classifications, Time-series analysis, Times series, WP4},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n ALLSTAR : inference of reliAble causaL ruLes between Somatic muTAtions and canceR phenotypes.\n \n \n \n \n\n\n \n Simionato, D.; Collesei, A.; Miglietta, F.; and Vandin, F.\n\n\n \n\n\n\n Bioinformatics, 40(7): btae449. July 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"ALLSTAR$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{simionato_allstar_2024,\n\ttitle = {{ALLSTAR} : inference of {reliAble} {causaL} {ruLes} between {Somatic} {muTAtions} and {canceR} phenotypes},\n\tvolume = {40},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1367-4811},\n\tshorttitle = {{ALLSTAR}},\n\turl = {https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btae449/7717991},\n\tdoi = {10.1093/bioinformatics/btae449},\n\tabstract = {Abstract \n             \n              Motivation \n              Recent advances in DNA sequencing technologies have allowed the detailed characterization of genomes in large cohorts of tumors, highlighting their extreme heterogeneity, with no two tumors sharing the same complement of somatic mutations. Such heterogeneity hinders our ability to identify somatic mutations important for the disease, including mutations that determine clinically relevant phenotypes (e.g. cancer subtypes). Several tools have been developed to identify somatic mutations related to cancer phenotypes. However, such tools identify correlations between somatic mutations and cancer phenotypes, with no guarantee of highlighting causal relations. \n             \n             \n              Results \n              We describe ALLSTAR, a novel tool to infer reliable causal relations between somatic mutations and cancer phenotypes. ALLSTAR identifies reliable causal rules highlighting combinations of somatic mutations with the highest impact in terms of average effect on the phenotype. While we prove that the underlying computational problem is NP-hard, we develop a branch-and-bound approach that employs protein–protein interaction networks and novel bounds for pruning the search space, while properly correcting for multiple hypothesis testing. Our extensive experimental evaluation on synthetic data shows that our tool is able to identify reliable causal relations in large cancer cohorts. Moreover, the reliable causal rules identified by our tool in cancer data show that our approach identifies several somatic mutations known to be relevant for cancer phenotypes as well as novel biologically meaningful relations. \n             \n             \n              Availability and implementation \n              Code, data, and scripts to reproduce the experiments available at https://github.com/VandinLab/ALLSTAR.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-10-14},\n\tjournal = {Bioinformatics},\n\tauthor = {Simionato, Dario and Collesei, Antonio and Miglietta, Federica and Vandin, Fabio},\n\teditor = {Robinson, Peter},\n\tmonth = jul,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {btae449},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n An MLOps Solution Framework for Transitioning Machine Learning Models into eHealth Systems.\n \n \n \n \n\n\n \n Basile, A.; Calefato, F.; Lanubile, F.; Mallardi, G.; and Quaranta, L.\n\n\n \n\n\n\n In Napoli, Italia, May 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{basile_mlops_2024,\n\taddress = {Napoli, Italia},\n\ttitle = {An {MLOps} {Solution} {Framework} for {Transitioning} {Machine} {Learning} {Models} into {eHealth} {Systems}},\n\turl = {https://ceur-ws.org/Vol-3762/524.pdf},\n\tauthor = {Basile, Andrea and Calefato, Fabio and Lanubile, Filippo and Mallardi, Giulio and Quaranta, Luigi},\n\tmonth = may,\n\tyear = {2024},\n\tkeywords = {SP1, WP4},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n The financial burden of healthcare- associated infections: A propensity score analysis in an Italian healthcare setting.\n \n \n \n \n\n\n \n Orlando, S.; Cicala, M.; DeSanto, C.; Mosconi, C.; Ciccacci, F.; Guarente, L.; Carestia, M.; Liotta, G.; Di Giovanni, D.; Buonomo, E.; Riccardi, F.; Palombi, L.; and Emberti Gialloreti, L.\n\n\n \n\n\n\n Infection Prevention in Practice,100406. October 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{orlando_financial_2024,\n\ttitle = {The financial burden of healthcare- associated infections: {A} propensity score analysis in an {Italian} healthcare setting},\n\tissn = {25900889},\n\tshorttitle = {The financial burden of healthcare- associated infections},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2590088924000702},\n\tdoi = {10.1016/j.infpip.2024.100406},\n\tlanguage = {en},\n\turldate = {2024-10-15},\n\tjournal = {Infection Prevention in Practice},\n\tauthor = {Orlando, S. and Cicala, M. and DeSanto, C. and Mosconi, C. and Ciccacci, F. and Guarente, L. and Carestia, M. and Liotta, G. and Di Giovanni, D. and Buonomo, E. and Riccardi, F. and Palombi, L. and Emberti Gialloreti, L.},\n\tmonth = oct,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {100406},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Cellular Senescence: The Driving Force of Musculoskeletal Diseases.\n \n \n \n \n\n\n \n Falvino, A.; Gasperini, B.; Cariati, I.; Bonanni, R.; Chiavoghilefu, A.; Gasbarra, E.; Botta, A.; Tancredi, V.; and Tarantino, U.\n\n\n \n\n\n\n Biomedicines, 12(9): 1948. August 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Cellular$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{falvino_cellular_2024,\n\ttitle = {Cellular {Senescence}: {The} {Driving} {Force} of {Musculoskeletal} {Diseases}},\n\tvolume = {12},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2227-9059},\n\tshorttitle = {Cellular {Senescence}},\n\turl = {https://www.mdpi.com/2227-9059/12/9/1948},\n\tdoi = {10.3390/biomedicines12091948},\n\tabstract = {The aging of the world population is closely associated with an increased prevalence of musculoskeletal disorders, such as osteoporosis, sarcopenia, and osteoarthritis, due to common genetic, endocrine, and mechanical risk factors. These conditions are characterized by degeneration of bone, muscle, and cartilage tissue, resulting in an increased risk of fractures and reduced mobility. Importantly, a crucial role in the pathophysiology of these diseases has been proposed for cellular senescence, a state of irreversible cell cycle arrest induced by factors such as DNA damage, telomere shortening, and mitochondrial dysfunction. In addition, senescent cells secrete pro-inflammatory molecules, called senescence-associated secretory phenotype (SASP), which can alter tissue homeostasis and promote disease progression. Undoubtedly, targeting senescent cells and their secretory profiles could promote the development of integrated strategies, including regular exercise and a balanced diet or the use of senolytics and senomorphs, to improve the quality of life of the aging population. Therefore, our review aimed to highlight the role of cellular senescence in age-related musculoskeletal diseases, summarizing the main underlying mechanisms and potential anti-senescence strategies for the treatment of osteoporosis, sarcopenia, and osteoarthritis.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2024-10-14},\n\tjournal = {Biomedicines},\n\tauthor = {Falvino, Angela and Gasperini, Beatrice and Cariati, Ida and Bonanni, Roberto and Chiavoghilefu, Angela and Gasbarra, Elena and Botta, Annalisa and Tancredi, Virginia and Tarantino, Umberto},\n\tmonth = aug,\n\tyear = {2024},\n\tkeywords = {SP3, WP3},\n\tpages = {1948},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n The functional roles of S‐adenosyl‐methionine and S‐adenosyl‐homocysteine and their involvement in trisomy 21.\n \n \n \n \n\n\n \n Caracausi, M.; Ramacieri, G.; Catapano, F.; Cicilloni, M.; Lajin, B.; Pelleri, M. C.; Piovesan, A.; Vitale, L.; Locatelli, C.; Pirazzoli, G. L.; Strippoli, P.; Antonaros, F.; and Vione, B.\n\n\n \n\n\n\n BioFactors, 50(4): 709–724. July 2024.\n Number: 4\n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{caracausi_functional_2024,\n\ttitle = {The functional roles of {S}‐adenosyl‐methionine and {S}‐adenosyl‐homocysteine and their involvement in trisomy 21},\n\tvolume = {50},\n\tissn = {0951-6433, 1872-8081},\n\turl = {https://iubmb.onlinelibrary.wiley.com/doi/10.1002/biof.2044},\n\tdoi = {10.1002/biof.2044},\n\tabstract = {Abstract\n            The one‐carbon metabolism pathway is involved in critical human cellular functions such as cell proliferation, mitochondrial respiration, and epigenetic regulation. In the homocysteine‐methionine cycle S‐adenosyl‐methionine (SAM) and S‐adenosyl‐homocysteine (SAH) are synthetized, and their levels are finely regulated to ensure proper functioning of key enzymes which control cellular growth and differentiation. Here we review the main biological mechanisms involving SAM and SAH and the known related human diseases. It was recently demonstrated that SAM and SAH levels are altered in plasma of subjects with trisomy 21 (T21) but how this metabolic dysregulation influences the clinical manifestation of T21 phenotype has not been previously described. This review aims at providing an overview of the biological mechanisms which are altered in response to changes in the levels of SAM and SAH observed in DS.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-09-10},\n\tjournal = {BioFactors},\n\tauthor = {Caracausi, Maria and Ramacieri, Giuseppe and Catapano, Francesca and Cicilloni, Michela and Lajin, Bassam and Pelleri, Maria Chiara and Piovesan, Allison and Vitale, Lorenza and Locatelli, Chiara and Pirazzoli, Gian Luca and Strippoli, Pierluigi and Antonaros, Francesca and Vione, Beatrice},\n\tmonth = jul,\n\tyear = {2024},\n\tnote = {Number: 4},\n\tkeywords = {SP3, WP3},\n\tpages = {709--724},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Shallow and deep learning classifiers in medical image analysis.\n \n \n \n \n\n\n \n Prinzi, F.; Currieri, T.; Gaglio, S.; and Vitabile, S.\n\n\n \n\n\n\n European Radiology Experimental, 8(1). 2024.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"Shallow$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{prinzi_shallow_2024,\n\ttitle = {Shallow and deep learning classifiers in medical image analysis},\n\tvolume = {8},\n\tissn = {25099280 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186845857&doi=10.1186%2fs41747-024-00428-2&partnerID=40&md5=10c6a7057ba8275c0f3609fb84fab5e6},\n\tdoi = {10.1186/s41747-024-00428-2},\n\tabstract = {An increasingly strong connection between artificial intelligence and medicine has enabled the development of predictive models capable of supporting physicians’ decision-making. Artificial intelligence encompasses much more than machine learning, which nevertheless is its most cited and used sub-branch in the last decade. Since most clinical problems can be modeled through machine learning classifiers, it is essential to discuss their main elements. This review aims to give primary educational insights on the most accessible and widely employed classifiers in radiology field, distinguishing between “shallow” learning (i.e., traditional machine learning) algorithms, including support vector machines, random forest and XGBoost, and “deep” learning architectures including convolutional neural networks and vision transformers. In addition, the paper outlines the key steps for classifiers training and highlights the differences between the most common algorithms and architectures. Although the choice of an algorithm depends on the task and dataset dealing with, general guidelines for classifier selection are proposed in relation to task analysis, dataset size, explainability requirements, and available computing resources. Considering the enormous interest in these innovative models and architectures, the problem of machine learning algorithms interpretability is finally discussed, providing a future perspective on trustworthy artificial intelligence. Relevance statement The growing synergy between artificial intelligence and medicine fosters predictive models aiding physicians. Machine learning classifiers, from shallow learning to deep learning, are offering crucial insights for the development of clinical decision support systems in healthcare. Explainability is a key feature of models that leads systems toward integration into clinical practice. Key points • Training a shallow classifier requires extracting disease-related features from region of interests (e.g., radiomics). • Deep classifiers implement automatic feature extraction and classification. • The classifier selection is based on data and computational resources availability, task, and explanation needs. Graphical Abstract: (Figure presented.). © The Author(s) 2024.},\n\tlanguage = {English},\n\tnumber = {1},\n\tjournal = {European Radiology Experimental},\n\tpublisher = {Springer Science and Business Media Deutschland GmbH},\n\tauthor = {Prinzi, F. and Currieri, T. and Gaglio, S. and Vitabile, S.},\n\tyear = {2024},\n\tnote = {Number: 1},\n\tkeywords = {Algorithms, Artificial Intelligence, Artificial intelligence, Deep Learning, Deep learning, Explainable AI, Machine Learning, Machine learning classifiers, Neural Networks, Computer, SP1, Shallow learning, WP4, algorithm, artificial intelligence, artificial neural network, classifier, clinical decision support system, clinical practice, convolutional neural network, decision making, deep learning, feature extraction, female, human, image analysis, learning, learning algorithm, machine learning, physician, practice guideline, predictive model, radiomics, random forest, review, support vector machine},\n}\n\n\n\n

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\n An increasingly strong connection between artificial intelligence and medicine has enabled the development of predictive models capable of supporting physicians’ decision-making. Artificial intelligence encompasses much more than machine learning, which nevertheless is its most cited and used sub-branch in the last decade. Since most clinical problems can be modeled through machine learning classifiers, it is essential to discuss their main elements. This review aims to give primary educational insights on the most accessible and widely employed classifiers in radiology field, distinguishing between “shallow” learning (i.e., traditional machine learning) algorithms, including support vector machines, random forest and XGBoost, and “deep” learning architectures including convolutional neural networks and vision transformers. In addition, the paper outlines the key steps for classifiers training and highlights the differences between the most common algorithms and architectures. Although the choice of an algorithm depends on the task and dataset dealing with, general guidelines for classifier selection are proposed in relation to task analysis, dataset size, explainability requirements, and available computing resources. Considering the enormous interest in these innovative models and architectures, the problem of machine learning algorithms interpretability is finally discussed, providing a future perspective on trustworthy artificial intelligence. Relevance statement The growing synergy between artificial intelligence and medicine fosters predictive models aiding physicians. Machine learning classifiers, from shallow learning to deep learning, are offering crucial insights for the development of clinical decision support systems in healthcare. Explainability is a key feature of models that leads systems toward integration into clinical practice. Key points • Training a shallow classifier requires extracting disease-related features from region of interests (e.g., radiomics). • Deep classifiers implement automatic feature extraction and classification. • The classifier selection is based on data and computational resources availability, task, and explanation needs. Graphical Abstract: (Figure presented.). © The Author(s) 2024.\n

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\n \n\n \n \n \n \n \n \n FHIR-standardized data collection on the clinical rehabilitation pathway of trans-femoral amputation patients.\n \n \n \n \n\n\n \n Arcobelli, V. A.; Moscato, S.; Palumbo, P.; Marfoglia, A.; Nardini, F.; Randi, P.; Davalli, A.; Carbonaro, A.; Chiari, L.; and Mellone, S.\n\n\n \n\n\n\n Scientific Data, 11(1): 806. 2024.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"FHIR-standardized$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{arcobelli_fhir-standardized_2024,\n\ttitle = {{FHIR}-standardized data collection on the clinical rehabilitation pathway of trans-femoral amputation patients},\n\tvolume = {11},\n\tissn = {2052-4463},\n\turl = {https://www.nature.com/articles/s41597-024-03593-6},\n\tdoi = {10.1038/s41597-024-03593-6},\n\tabstract = {Abstract\n            Lower limb amputation is a medical intervention which causes motor disability and may compromise quality of life. Several factors determine patients’ health outcomes, including an appropriate prosthetic provision and an effective rehabilitation program, necessitating a thorough quantitative observation through different data sources. In this context, the role of interoperability becomes essential, facilitating the reuse of real-world data through the provision of structured and easily accessible databases. This study introduces a comprehensive 10-year dataset encompassing clinical features, mobility measurements, and prosthetic knees of 1006 trans-femoral amputees during 1962 hospital stays for rehabilitation. The dataset is made available in both comma-separated values (CSV) format and HL7 Fast Healthcare Interoperability Resources (FHIR)-based representation, ensuring broad utility and compatibility for researchers and healthcare practitioners. This initiative contributes to advancing community understanding of post-amputation rehabilitation and underscores the significance of interoperability in promoting seamless data sharing for meaningful insights into healthcare outcomes.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-09-10},\n\tjournal = {Scientific Data},\n\tauthor = {Arcobelli, Valerio Antonio and Moscato, Serena and Palumbo, Pierpaolo and Marfoglia, Alberto and Nardini, Filippo and Randi, Pericle and Davalli, Angelo and Carbonaro, Antonella and Chiari, Lorenzo and Mellone, Sabato},\n\tyear = {2024},\n\tnote = {Number: 1},\n\tkeywords = {SP1, WP4},\n\tpages = {806},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective.\n \n \n \n \n\n\n \n Amato, D.; Calderaro, S.; Lo Bosco, G.; Rizzo, R.; and Vella, F.\n\n\n \n\n\n\n Cognitive Computation. June 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Explainable$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{amato_explainable_2024,\n\ttitle = {Explainable {Histopathology} {Image} {Classification} with {Self}-organizing {Maps}: {A} {Granular} {Computing} {Perspective}},\n\tissn = {1866-9964},\n\tshorttitle = {Explainable {Histopathology} {Image} {Classification} with {Self}-organizing {Maps}},\n\turl = {https://doi.org/10.1007/s12559-024-10312-1},\n\tdoi = {10.1007/s12559-024-10312-1},\n\tabstract = {The automatic analysis of histology images is an open research field where machine learning techniques and neural networks, especially deep architectures, are considered successful tools due to their abilities in image classification. This paper proposes a granular computing methodology for histopathological image classification. It is based on embedding tiles of histopathology images using deep metric learning, where a self-organizing map is adopted to generate the granular structure in this learned embedding space. The SOM enables the implementation of an explainable mechanism by visualizing a knowledge space that the experts can use to analyze and classify the new images. Additionally, it provides confidence in the classification results while highlighting each important image fragment, with the benefit of reducing the number of false negatives. An exemplary case is when an image detail is indicated, with small confidence, as malignant in an image globally classified as benign. Another implemented feature is the proposal of additional labelled image tiles sharing the same characteristics to specify the context of the output decision. The proposed system was tested using three histopathology image datasets, obtaining the accuracy of the state-of-the-art black-box methods based on deep learning neural networks. Differently from the methodologies proposed so far for the same purpose, this paper introduces a novel explainable method for medical image analysis where the advantages of the deep learning neural networks used to build the embedding space for the image tiles are combined with the intrinsic explainability of the granular process obtained using the clustering property of a self-organizing map.},\n\tlanguage = {en},\n\turldate = {2024-09-23},\n\tjournal = {Cognitive Computation},\n\tauthor = {Amato, Domenico and Calderaro, Salvatore and Lo Bosco, Giosué and Rizzo, Riccardo and Vella, Filippo},\n\tmonth = jun,\n\tyear = {2024},\n\tkeywords = {Artificial Intelligence, Embedding, Explainability, Metric learning, SP1, Self-organizing maps, WP4, XAI},\n}\n

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\n \n 2023\n \n \n (16)\n \n \n

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\n \n\n \n \n \n \n \n \n GLP-1RAs and cardiovascular disease: is the endothelium a relevant platform?.\n \n \n \n \n\n\n \n Menghini, R.; Casagrande, V.; Rizza, S.; and Federici, M.\n\n\n \n\n\n\n Acta Diabetologica, 60(11): 1441–1448. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"GLP-1RAs$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{menghini_glp-1ras_2023,\n\ttitle = {{GLP}-{1RAs} and cardiovascular disease: is the endothelium a relevant platform?},\n\tvolume = {60},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164001512&doi=10.1007%2fs00592-023-02124-w&partnerID=40&md5=1a82a1d1023394664dc9ef823d7b1b3d},\n\tdoi = {10.1007/s00592-023-02124-w},\n\tnumber = {11},\n\tjournal = {Acta Diabetologica},\n\tauthor = {Menghini, R. and Casagrande, V. and Rizza, S. and Federici, M.},\n\tyear = {2023},\n\tkeywords = {SP3, WP3},\n\tpages = {1441--1448},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Carburacy: Summarization Models Tuning and Comparison in Eco-Sustainable Regimes with a Novel Carbon-Aware Accuracy.\n \n \n \n \n\n\n \n Moro, G.; Ragazzi, L.; and Valgimigli, L.\n\n\n \n\n\n\n In Williams B.; Chen Y.; and Neville J., editor(s), Proc. AAAI Conf. Artif. Intell., AAAI, volume 37, pages 14417–14425, 2023. AAAI Press\n Journal Abbreviation: Proc. AAAI Conf. Artif. Intell., AAAI\n\n\n\n
\n\n\n\n \n \n $\"Carburacy:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{moro_carburacy_2023,\n\ttitle = {Carburacy: {Summarization} {Models} {Tuning} and {Comparison} in {Eco}-{Sustainable} {Regimes} with a {Novel} {Carbon}-{Aware} {Accuracy}},\n\tvolume = {37},\n\tisbn = {978-157735880-0 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167995147&partnerID=40&md5=0207febe2da6b2afc18631d5c8361e22},\n\tdoi = {https://doi.org/10.1609/aaai.v37i12.26686},\n\tabstract = {Generative transformer-based models have reached cutting-edge performance in long document summarization. Nevertheless, this task is witnessing a paradigm shift in developing ever-increasingly computationally-hungry solutions, focusing on effectiveness while ignoring the economic, environmental, and social costs of yielding such results. Accordingly, such extensive resources impact climate change and raise barriers to small and medium organizations distinguished by low-resource regimes of hardware and data. As a result, this unsustainable trend has lifted many concerns in the community, which directs the primary efforts on the proposal of tools to monitor models’ energy costs. Despite their importance, no evaluation measure considering models’ eco-sustainability exists yet. In this work, we propose Carburacy, the first carbon-aware accuracy measure that captures both model effectiveness and eco-sustainability. We perform a comprehensive benchmark for long document summarization, comparing multiple state-of-the-art quadratic and linear transformers on several datasets under eco-sustainable regimes. Finally, thanks to Carburacy, we found optimal combinations of hyperparameters that let models be competitive in effectiveness with significantly lower costs. Copyright © 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.},\n\tlanguage = {English},\n\tbooktitle = {Proc. {AAAI} {Conf}. {Artif}. {Intell}., {AAAI}},\n\tpublisher = {AAAI Press},\n\tauthor = {Moro, G. and Ragazzi, L. and Valgimigli, L.},\n\teditor = {{Williams B.} and {Chen Y.} and {Neville J.}},\n\tyear = {2023},\n\tnote = {Journal Abbreviation: Proc. AAAI Conf. Artif. Intell., AAAI},\n\tkeywords = {Artificial intelligence, Carbon, Climate change, Cutting edges, Document summarization, Eco-sustainability, Economic costs, Environmental costs, Model tuning, Models comparisons, Paradigm shifts, Performance, SP1, Summarization models, Sustainable development, WP4},\n\tpages = {14417--14425},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MOTU on FHIR: A preliminary strategy to enable interoperability for retrospective dataset standardization.\n \n \n \n \n\n\n \n Arcobelli, V.; Moscato, S.; Marfoglia, A.; Nardini, F.; Randi, P.; Davalli, A.; Carbonaro, A.; Palumbo, P.; Chiari, L.; and Mellone, S.\n\n\n \n\n\n\n In IEEE EMBS Spec. Topic Conf. Data Sci. Eng. Healthc., Med. Biol., IEEECONF, pages 81–82, 2023. Institute of Electrical and Electronics Engineers Inc.\n Journal Abbreviation: IEEE EMBS Spec. Topic Conf. Data Sci. Eng. Healthc., Med. Biol., IEEECONF\n\n\n\n
\n\n\n\n \n \n $\"MOTU$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{arcobelli_motu_2023,\n\ttitle = {{MOTU} on {FHIR}: {A} preliminary strategy to enable interoperability for retrospective dataset standardization},\n\tisbn = {979-835038338-6 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185556922&doi=10.1109%2fIEEECONF58974.2023.10404816&partnerID=40&md5=1864c3bf613493b2c7ec945712cb8cad},\n\tdoi = {10.1109/IEEECONF58974.2023.10404816},\n\tabstract = {We present the application of HL7-FHIR to standardize a retrospective heterogeneous dataset, enhancing human/machine readability and interoperability.Clinical Relevance: The adopted strategy enables secondary use of clinical data in scientific medical research.  © 2023 IEEE.},\n\tlanguage = {English},\n\tbooktitle = {{IEEE} {EMBS} {Spec}. {Topic} {Conf}. {Data} {Sci}. {Eng}. {Healthc}., {Med}. {Biol}., {IEEECONF}},\n\tpublisher = {Institute of Electrical and Electronics Engineers Inc.},\n\tauthor = {Arcobelli, V.A. and Moscato, S. and Marfoglia, A. and Nardini, F. and Randi, P. and Davalli, A. and Carbonaro, A. and Palumbo, P. and Chiari, L. and Mellone, S.},\n\tyear = {2023},\n\tnote = {Journal Abbreviation: IEEE EMBS Spec. Topic Conf. Data Sci. Eng. Healthc., Med. Biol., IEEECONF},\n\tkeywords = {Clinical data, Clinical research, Heterogeneous datasets, Human-machine, Interoperability, Medical research, SP1, Secondary use, Standardization, WP4},\n\tpages = {81--82},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization.\n \n \n \n \n\n\n \n Carbonaro, A.; Marfoglia, A.; Nardini, F.; and Mellone, S.\n\n\n \n\n\n\n Frontiers in Digital Health, 5. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"CONNECTED:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{carbonaro_connected_2023,\n\ttitle = {{CONNECTED}: leveraging digital twins and personal knowledge graphs in healthcare digitalization},\n\tvolume = {5},\n\tissn = {2673253X (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180261340&doi=10.3389%2ffdgth.2023.1322428&partnerID=40&md5=6b02c75cd7051d9a3d10dac62cbcc6f2},\n\tdoi = {10.3389/fdgth.2023.1322428},\n\tabstract = {Healthcare has always been a strategic domain in which innovative technologies can be applied to increase the effectiveness of services and patient care quality. Recent advancements have been made in the adoption of Digital Twins (DTs) and Personal Knowledge Graphs (PKGs) in this field. Despite this, their introduction has been hindered by the complex nature of the context itself which leads to many challenges both technical and organizational. In this article, we reviewed the literature about these technologies and their integrations, identifying the most critical requirements for clinical platforms. These latter have been used to design CONNECTED (COmpreheNsive and staNdardized hEalth-Care plaTforms to collEct and harmonize clinical Data), a conceptual framework aimed at defining guidelines to overcome the crucial issues related to the development of healthcare applications. It is structured in a multi-layer shape, in which heterogeneous data sources are first integrated, then standardized, and finally used to realize general-purpose DTs of patients backed by PKGs and accessible through dedicated APIs. These DTs will be the foundation on which smart applications can be built. 2023 Carbonaro, Marfoglia, Nardini and Mellone.},\n\tlanguage = {English},\n\tjournal = {Frontiers in Digital Health},\n\tpublisher = {Frontiers Media SA},\n\tauthor = {Carbonaro, A. and Marfoglia, A. and Nardini, F. and Mellone, S.},\n\tyear = {2023},\n\tkeywords = {Article, SP1, WP4, architectural framework, artificial intelligence, conceptual framework, data integration, digital twin, digital twins, digitalization, health care, health care delivery, healthcare, nerve cell network, osteoporosis, patient care, personal knowledge graphs, total quality management},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Kelvin probe force microscopy on patterned large-area biofunctionalized surfaces: a reliable ultrasensitive platform for biomarker detection.\n \n \n \n \n\n\n \n Di Franco, C.; Piscitelli, M.; Macchia, E.; Scandurra, C.; Catacchio, M.; Torsi, L.; and Scamarcio, G.\n\n\n \n\n\n\n Journal of Materials Chemistry C, 12(1): 73–79. 2023.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"Kelvin$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{di_franco_kelvin_2023,\n\ttitle = {Kelvin probe force microscopy on patterned large-area biofunctionalized surfaces: a reliable ultrasensitive platform for biomarker detection},\n\tvolume = {12},\n\tissn = {20507526 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180977964&doi=10.1039%2fd3tc03110a&partnerID=40&md5=2fae5de72dcccb1eaf48a3f2257d1d6f},\n\tdoi = {10.1039/d3tc03110a},\n\tabstract = {Kelvin probe force microscopy (KPFM) allows the detection of single binding events between immunoglobulins (IgM, IgG) and their cognate antibodies (anti-IgM, anti-IgG). Here an insight into the reliability and robustness of the methodology is provided. Our method is based on imaging the surface potential shift occurring on a dense layer of ∼5 × 107 antibodies physisorbed on a 50 μm × 90 μm area when assayed with increasing concentrations of antigens in phosphate buffer saline (PBS) standard solutions, in air and at a fixed scanning location. A comprehensive investigation of the influence of the main experimental parameters that may interfere with the outcomes of KPFM immune-assay is provided, showing the robustness and reliability of our approach. The data are supported also by a thorough polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS) analysis of the physisorbed biolayer, in the spectral region of the amide I, amide II and amide A bands. Our findings demonstrate that a 10 min incubation in 500 μL PBS encompassing ≈ 30 antigens (100 zM) triggers an extended surface potential shift that involves the whole investigated area. Such a shift quickly saturates at increasing ligand concentration, showing that the developed sensing platform works as an OFF/ON detector, capable of assessing the presence of a few specific biomarkers in a given assay volume. The reliability of the developed methodology KPFM is an important asset in single molecule detections at a wide electrode interface. © 2024 The Royal Society of Chemistry.},\n\tlanguage = {English},\n\tnumber = {1},\n\tjournal = {Journal of Materials Chemistry C},\n\tpublisher = {Royal Society of Chemistry},\n\tauthor = {Di Franco, C. and Piscitelli, M. and Macchia, E. and Scandurra, C. and Catacchio, M. and Torsi, L. and Scamarcio, G.},\n\tyear = {2023},\n\tnote = {Number: 1},\n\tkeywords = {Absorption spectroscopy, Amides, Antibodies, Antigens, Binding events, Biomarkers, Chemical detection, Dense layer, Experimental parameters, Kelvin probe force microscopy, Phosphate buffer salines, Physisorbed, Potential shift, Probes, Reliability, Reliability and robustness, SP3, Standard solutions, Surface potential, Ultrasensitive, WP4},\n\tpages = {73--79},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI.\n \n \n \n \n\n\n \n Dipasquale, O.; Cohen, A.; Martins, D.; Zelaya, F.; Turkheimer, F.; Veronese, M.; Mehta, M.; Williams, S.; Yang, B.; Banerjee, S.; and Wang, Y.\n\n\n \n\n\n\n Scientific Reports, 13(1). 2023.\n Number: 1\n\n\n\n
\n\n\n\n \n \n $\"Molecular-enriched$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{dipasquale_molecular-enriched_2023,\n\ttitle = {Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous {ASL}/{BOLD} {fMRI}},\n\tvolume = {13},\n\tissn = {20452322 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165341158&doi=10.1038%2fs41598-023-38573-0&partnerID=40&md5=59a6067b8648697fd6cdc797c552a755},\n\tdoi = {10.1038/s41598-023-38573-0},\n\tabstract = {Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test–retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits. © 2023, The Author(s).},\n\tlanguage = {English},\n\tnumber = {1},\n\tjournal = {Scientific Reports},\n\tpublisher = {Nature Research},\n\tauthor = {Dipasquale, O. and Cohen, A. and Martins, D. and Zelaya, F. and Turkheimer, F. and Veronese, M. and Mehta, M.A. and Williams, S.C.R. and Yang, B. and Banerjee, S. and Wang, Y.},\n\tyear = {2023},\n\tnote = {Number: 1},\n\tkeywords = {Brain, Brain Mapping, Cerebrovascular Circulation, Humans, Magnetic Resonance Imaging, Reproducibility of Results, SP3, WP4, brain, brain circulation, brain mapping, diagnostic imaging, human, nuclear magnetic resonance imaging, physiology, procedures, reproducibility},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Cogito Ergo Summ: Abstractive Summarization of Biomedical Papers via Semantic Parsing Graphs and Consistency Rewards.\n \n \n \n \n\n\n \n Frisoni, G.; Italiani, P.; Salvatori, S.; and Moro, G.\n\n\n \n\n\n\n In Williams B.; Chen Y.; and Neville J., editor(s), Proc. AAAI Conf. Artif. Intell., AAAI, volume 37, pages 12781–12789, 2023. AAAI Press\n Journal Abbreviation: Proc. AAAI Conf. Artif. Intell., AAAI\n\n\n\n
\n\n\n\n \n \n $\"Cogito$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{frisoni_cogito_2023,\n\ttitle = {Cogito {Ergo} {Summ}: {Abstractive} {Summarization} of {Biomedical} {Papers} via {Semantic} {Parsing} {Graphs} and {Consistency} {Rewards}},\n\tvolume = {37},\n\tisbn = {978-157735880-0 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168014584&partnerID=40&md5=e1ed524e25408b6208e603c5ff8303d6},\n\tabstract = {The automatic synthesis of biomedical publications catalyzes a profound research interest elicited by literature congestion. Current sequence-to-sequence models mainly rely on the lexical surface and seldom consider the deep semantic interconnections between the entities mentioned in the source document. Such superficiality translates into fabricated, poorly informative, redundant, and near-extractive summaries that severely restrict their real-world application in biomedicine, where the specialized jargon and the convoluted facts further emphasize task complexity. To fill this gap, we argue that the summarizer should acquire semantic interpretation over input, exploiting structured and unambiguous representations to capture and conserve the most relevant parts of the text content. This paper presents COGITOERGOSUMM, the first framework for biomedical abstractive summarization equipping large pre-trained language models with rich semantic graphs. Precisely, we infuse graphs from two complementary semantic parsing techniques with different goals and granularities-Event Extraction and Abstract Meaning Representation, also designing a reward signal to maximize information content preservation through reinforcement learning. Extensive quantitative and qualitative evaluations on the CDSR dataset show that our solution achieves competitive performance according to multiple metrics, despite using 2.5× fewer parameters. Results and ablation studies indicate that our joint text-graph model generates more enlightening, readable, and consistent summaries. Code available at: https://github.com/disi-unibo-nlp/cogito-ergo-summ. Copyright © 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.},\n\tlanguage = {English},\n\tbooktitle = {Proc. {AAAI} {Conf}. {Artif}. {Intell}., {AAAI}},\n\tpublisher = {AAAI Press},\n\tauthor = {Frisoni, G. and Italiani, P. and Salvatori, S. and Moro, G.},\n\teditor = {{Williams B.} and {Chen Y.} and {Neville J.}},\n\tyear = {2023},\n\tnote = {Journal Abbreviation: Proc. AAAI Conf. Artif. Intell., AAAI},\n\tkeywords = {'current, Abstracting, Automatic synthesis, Catalyse, Graphic methods, Real-world, Reinforcement learning, Research interests, SP1, Semantic interpretation, Semantic parsing, Semantics, Sequence models, Task complexity, Text content, WP4},\n\tpages = {12781--12789},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Align-then-abstract representation learning for low-resource summarization.\n \n \n \n \n\n\n \n Moro, G.; and Ragazzi, L.\n\n\n \n\n\n\n Neurocomputing, 548. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Align-then-abstract$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{moro_align-then-abstract_2023,\n\ttitle = {Align-then-abstract representation learning for low-resource summarization},\n\tvolume = {548},\n\tissn = {09252312 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162157503&doi=10.1016%2fj.neucom.2023.126356&partnerID=40&md5=63b9e3b42c526cc41f2f47af9cd2fd77},\n\tdoi = {10.1016/j.neucom.2023.126356},\n\tabstract = {Generative transformer-based models have achieved state-of-the-art performance in text summarization. Nevertheless, they still struggle in real-world scenarios with long documents when trained in low-resource settings of a few dozen labeled training instances, namely in low-resource summarization (LRS). This paper bridges the gap by addressing two key research challenges when summarizing long documents, i.e., long-input processing and document representation, in one coherent model trained for LRS. Specifically, our novel align-then-abstract representation learning model (ATHENA) jointly trains a segmenter and a summarizer by maximizing the alignment between the chunk-target pairs in output from the text segmentation. Extensive experiments reveal that ATHENA outperforms the current state-of-the-art approaches in LRS on multiple long document summarization datasets from different domains. © 2023 Elsevier B.V.},\n\tlanguage = {English},\n\tjournal = {Neurocomputing},\n\tpublisher = {Elsevier B.V.},\n\tauthor = {Moro, G. and Ragazzi, L.},\n\tyear = {2023},\n\tkeywords = {Abstract representation, Abstractive summarization, Document summarization, Long document summarization, Low-resource, Low-resource settings, NLP, Real-world scenario, Representation learning, SP1, State-of-the-art performance, Text Summarisation, Text processing, WP4, article, feature learning (machine learning)},\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Graph-Based Abstractive Summarization of Extracted Essential Knowledge for Low-Resource Scenarios.\n \n \n \n \n\n\n \n Moro, G.; Ragazzi, L.; and Valgimigli, L.\n\n\n \n\n\n\n In Gal K.; Gal K.; Nowe A.; Nalepa G.J.; Fairstein R.; and Radulescu R., editor(s), Front. Artif. Intell. Appl., volume 372, pages 1747–1754, 2023. IOS Press BV\n Journal Abbreviation: Front. Artif. Intell. Appl.\n\n\n\n
\n\n\n\n \n \n $\"Graph-Based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{moro_graph-based_2023,\n\ttitle = {Graph-{Based} {Abstractive} {Summarization} of {Extracted} {Essential} {Knowledge} for {Low}-{Resource} {Scenarios}},\n\tvolume = {372},\n\tisbn = {09226389 (ISSN); 978-164368436-9 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175806277&doi=10.3233%2fFAIA230460&partnerID=40&md5=f0a4ce3e42f5486ce661be69bda7c3fb},\n\tdoi = {10.3233/FAIA230460},\n\tabstract = {Although current summarization models can process increasingly long text sequences, they still struggle to capture salient related information spread across the lengthy size of inputs with few labeled training instances. Today's research still relies on standard input truncation without considering graph-based modeling of multiple semantic units to summarize only crucial facets. This paper proposes G-SEEK, a graph-based summarization of extracted essential knowledge. By representing the long source with a heterogeneous graph, our method extracts and provides salient sentences to an abstractive summarization model to generate the summary. Experimental results in low-resource scenarios, distinguished by data scarcity, reveal that G-SEEK consistently improves both the long- and multi-document summarization performance and accuracy across several datasets. © 2023 The Authors.},\n\tlanguage = {English},\n\tbooktitle = {Front. {Artif}. {Intell}. {Appl}.},\n\tpublisher = {IOS Press BV},\n\tauthor = {Moro, G. and Ragazzi, L. and Valgimigli, L.},\n\teditor = {{Gal K.} and {Gal K.} and {Nowe A.} and {Nalepa G.J.} and {Fairstein R.} and {Radulescu R.}},\n\tyear = {2023},\n\tnote = {Journal Abbreviation: Front. Artif. Intell. Appl.},\n\tkeywords = {'current, Data mining, Data scarcity, Graph-based, Graph-based models, Graphic methods, Heterogeneous graph, Input truncation, Multi documents summarization, SP1, Semantic units, Semantics, Standard input, Summarization models, WP4},\n\tpages = {1747--1754},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Retrieve-and-Rank End-to-End Summarization of Biomedical Studies.\n \n \n \n \n\n\n \n Moro, G.; Ragazzi, L.; Valgimigli, L.; and Molfetta, L.\n\n\n \n\n\n\n In Pedreira O.; and Estivill-Castro V., editor(s), Lect. Notes Comput. Sci., volume 14289 LNCS, pages 64–78, 2023. Springer Science and Business Media Deutschland GmbH\n Journal Abbreviation: Lect. Notes Comput. Sci.\n\n\n\n
\n\n\n\n \n \n $\"Retrieve-and-Rank$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@inproceedings{moro_retrieve-and-rank_2023,\n\ttitle = {Retrieve-and-{Rank} {End}-to-{End} {Summarization} of {Biomedical} {Studies}},\n\tvolume = {14289 LNCS},\n\tisbn = {03029743 (ISSN); 978-303146993-0 (ISBN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177229188&doi=10.1007%2f978-3-031-46994-7_6&partnerID=40&md5=7b199e38061fcf4c394b7ad6598d29a1},\n\tdoi = {10.1007/978-3-031-46994-7_6},\n\tabstract = {An arduous biomedical task involves condensing evidence derived from multiple interrelated studies, given a context as input, to generate reviews or provide answers autonomously. We named this task context-aware multi-document summarization (CA-MDS). Existing state-of-the-art (SOTA) solutions require truncation of the input due to the high memory demands, resulting in the loss of meaningful content. To address this issue effectively, we propose a novel approach called Ramses, which employs a retrieve-and-rank technique for end-to-end summarization. The model acquires the ability to (i) index each document by modeling its semantic features, (ii) retrieve the most relevant ones, and (iii) generate a summary via token probability marginalization. To facilitate the evaluation, we introduce a new dataset, FAQsumC19, which includes the synthesizing of multiple supporting papers to answer questions related to Covid-19. Our experimental findings demonstrate that Ramses achieves notably superior ROUGE scores compared to state-of-the-art methodologies, including the establishment of a new SOTA for the generation of systematic literature reviews using Ms2. Quality observation through human evaluation indicates that our model produces more informative responses than previous leading approaches. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},\n\tlanguage = {English},\n\tbooktitle = {Lect. {Notes} {Comput}. {Sci}.},\n\tpublisher = {Springer Science and Business Media Deutschland GmbH},\n\tauthor = {Moro, G. and Ragazzi, L. and Valgimigli, L. and Molfetta, L.},\n\teditor = {{Pedreira O.} and {Estivill-Castro V.}},\n\tyear = {2023},\n\tnote = {Journal Abbreviation: Lect. Notes Comput. Sci.},\n\tkeywords = {Biomedical Multi-Document Summarization, Biomedical multi-document summarization, Context-Aware, End to end, End-to-End Neural Retriever, End-to-end neural retriever, Marginalization, Multi documents summarization, Natural language processing systems, Neural Semantic Representation, Neural semantic representation, Quality control, SP1, Semantic features, Semantic representation, Semantics, State of the art, WP4},\n\tpages = {64--78},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution.\n \n \n \n \n\n\n \n Notario, E.; Visci, G.; Fosso, B.; Gissi, C.; Tanaskovic, N.; Rescigno, M.; Marzano, M.; and Pesole, G.\n\n\n \n\n\n\n Genes, 14(8). 2023.\n Number: 8\n\n\n\n
\n\n\n\n \n \n $\"Amplicon-Based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{notario_amplicon-based_2023,\n\ttitle = {Amplicon-{Based} {Microbiome} {Profiling}: {From} {Second}- to {Third}-{Generation} {Sequencing} for {Higher} {Taxonomic} {Resolution}},\n\tvolume = {14},\n\tissn = {20734425 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168829592&doi=10.3390%2fgenes14081567&partnerID=40&md5=f2f3a050930b53163fb07711631b8390},\n\tdoi = {10.3390/genes14081567},\n\tabstract = {The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary. © 2023 by the authors.},\n\tlanguage = {English},\n\tnumber = {8},\n\tjournal = {Genes},\n\tpublisher = {Multidisciplinary Digital Publishing Institute (MDPI)},\n\tauthor = {Notario, E. and Visci, G. and Fosso, B. and Gissi, C. and Tanaskovic, N. and Rescigno, M. and Marzano, M. and Pesole, G.},\n\tyear = {2023},\n\tnote = {Number: 8},\n\tkeywords = {16S rRNA amplicon-based sequencing, Acinetobacter baumannii, Article, Ascomycetes, Bacteroidaceae, Bacteroides, Bacteroidetes, Benchmarking, Bifidobacteriaceae, Bifidobacterium, Computational Biology, DNA extraction, Enterococcus faecalis, Escherichia coli, Firmicutes, Lachnospiraceae, Lactobacillus, Microbiota, Neisseria meningitidis, Porphyromonas gingivalis, Propionibacterium acnes, Proteobacteria, Pseudomonas aeruginosa, RNA 16S, RNA, Ribosomal, 16S, Ruminococcaceae, SP3, Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus mutans, Technology, WP4, accuracy, amplicon, area under the curve, bacterium identification, benchmarking, bioinformatics, controlled study, diagnostic test accuracy study, genetics, high throughput sequencing, metagenomics, microbial diversity, microbiome, microflora, mock analysis, multiplex polymerase chain reaction, next-generation sequencing, nonhuman, principal coordinate analysis, pyrosequencing, recall, receiver operating characteristic, taxonomy, technology, third-generation sequencing},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Efficient text-image semantic search: A multi-modal vision-language approach for fashion retrieval.\n \n \n \n \n\n\n \n Moro, G.; Salvatori, S.; and Frisoni, G.\n\n\n \n\n\n\n Neurocomputing, 538. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{moro_efficient_2023,\n\ttitle = {Efficient text-image semantic search: {A} multi-modal vision-language approach for fashion retrieval},\n\tvolume = {538},\n\tissn = {09252312 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152591924&doi=10.1016%2fj.neucom.2023.03.057&partnerID=40&md5=28209e7bb1a9d2ecbd0d886825b44588},\n\tdoi = {10.1016/j.neucom.2023.03.057},\n\tabstract = {In this paper, we address the problem of multi-modal retrieval of fashion products. State-of-the-art (SOTA) works proposed in literature use vision-and-language transformers to assign similarity scores to joint text-image pairs, then used for sorting the results during a retrieval phase. However, this approach is inefficient since it requires coupling a query with every record in the dataset and computing a forward pass for each sample at runtime, precluding scalability to large-scale datasets. We thus propose a solution that overcomes the above limitation by combining transformers and deep metric learning to create a latent space where texts and images are separately embedded, and their spatial proximity translates into semantic similarity. Our architecture does not use convolutional neural networks to process images, allowing us to test different levels of image-processing details and metric learning losses. We vastly improve retrieval accuracy results on the FashionGen benchmark (+18.71\\% and +9.22\\% Rank@1 on Image-to-Text and Text-to-Image, respectively) while being up to 512x faster. Finally, we analyze the speed-up obtainable by different approximate nearest neighbor retrieval strategies—an optimization precluded to current SOTA contributions. We release our solution as a web application available at https://disi-unibo-nlp.github.io/projects/fashion\\_retrieval/. © 2023 Elsevier B.V.},\n\tlanguage = {English},\n\tjournal = {Neurocomputing},\n\tpublisher = {Elsevier B.V.},\n\tauthor = {Moro, G. and Salvatori, S. and Frisoni, G.},\n\tyear = {2023},\n\tkeywords = {Deep learning, Fashion domain, Image enhancement, Image semantics, Large dataset, Metric learning, Multi-modal, Multi-modal retrieval, Nearest neighbor search, SP1, Semantic Web, Semantic search, Semantics, State of the art, Text images, Vision-and-language transformer, Vision-and-language transformers, WP4, article, convolutional neural network, deep learning, human, human experiment, image processing, information retrieval, language, learning, velocity, vision},\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Metric Learning in Histopathological Image Classification: Opening the Black Box.\n \n \n \n \n\n\n \n Amato, D.; Calderaro, S.; Lo Bosco, G.; Rizzo, R.; and Vella, F.\n\n\n \n\n\n\n Sensors, 23(13): 6003. June 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Metric$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@article{amato_metric_2023,\n\ttitle = {Metric {Learning} in {Histopathological} {Image} {Classification}: {Opening} the {Black} {Box}},\n\tvolume = {23},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1424-8220},\n\tshorttitle = {Metric {Learning} in {Histopathological} {Image} {Classification}},\n\turl = {https://www.mdpi.com/1424-8220/23/13/6003},\n\tdoi = {10.3390/s23136003},\n\tabstract = {The application of machine learning techniques to histopathology images enables advances in the field, providing valuable tools that can speed up and facilitate the diagnosis process. The classification of these images is a relevant aid for physicians who have to process a large number of images in long and repetitive tasks. This work proposes the adoption of metric learning that, beyond the task of classifying images, can provide additional information able to support the decision of the classification system. In particular, triplet networks have been employed to create a representation in the embedding space that gathers together images of the same class while tending to separate images with different labels. The obtained representation shows an evident separation of the classes with the possibility of evaluating the similarity and the dissimilarity among input images according to distance criteria. The model has been tested on the BreakHis dataset, a reference and largely used dataset that collects breast cancer images with eight pathology labels and four magnification levels. Our proposed classification model achieves relevant performance on the patient level, with the advantage of providing interpretable information for the obtained results, which represent a specific feature missed by the all the recent methodologies proposed for the same purpose.},\n\tlanguage = {en},\n\tnumber = {13},\n\turldate = {2024-10-03},\n\tjournal = {Sensors},\n\tauthor = {Amato, Domenico and Calderaro, Salvatore and Lo Bosco, Giosué and Rizzo, Riccardo and Vella, Filippo},\n\tmonth = jun,\n\tyear = {2023},\n\tkeywords = {SP1, WP4},\n\tpages = {6003},\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A stable physisorbed layer of packed capture antibodies for high-performance sensing applications.\n \n \n \n \n\n\n \n Sarcina, L.; Scandurra, C.; Di Franco, C.; Caputo, M.; Catacchio, M.; Bollella, P.; Scamarcio, G.; Macchia, E.; and Torsi, L.\n\n\n \n\n\n\n Journal of Materials Chemistry C, 11(27): 9093–9106. 2023.\n Number: 27\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sarcina_stable_2023,\n\ttitle = {A stable physisorbed layer of packed capture antibodies for high-performance sensing applications},\n\tvolume = {11},\n\tissn = {20507526 (ISSN)},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164128660&doi=10.1039%2fd3tc01123b&partnerID=40&md5=d118f4dd52f242314a4a67993ad5d084},\n\tdoi = {10.1039/d3tc01123b},\n\tabstract = {Antibody physisorption at a solid interface is a very interesting phenomenon that has important effects on applications such as the development of novel biomaterials and the rational design and fabrication of high-performance biosensors. The strategy selected to immobilize biorecognition elements can determine the performance level of a device and one of the simplest approaches is physical adsorption, which is cost-effective, fast, and compatible with printing techniques as well as with green-chemistry processes. Despite its huge advantages, physisorption is very seldom adopted, as there is an ingrained belief that it does not lead to high performance because of its lack of uniformity and long-term stability, which, however, have never been systematically investigated, particularly for bilayers of capture antibodies. Herein, the homogeneity and stability of an antibody layer against SARS-CoV-2-Spike1 (S1) protein physisorbed onto a gold surface have been investigated by means of multi-parametric surface plasmon resonance (MP-SPR). A surface coverage density of capture antibodies as high as (1.50 ± 0.06) × 1012 molecules per cm−2 is measured, corresponding to a thickness of 12 ± 1 nm. This value is compatible with a single monolayer of homogeneously deposited antibodies. The effect of the ionic strength (is) of the antibody solution in controlling physisorption of the protein was thoroughly investigated, demonstrating an enhancement in surface coverage at lower ionic strength. An atomic force microscopy (AFM) investigation shows a globular structure attributed to is-related aggregations of antibodies. The long-term stability over two weeks of the physisorbed proteins was also assessed. High-performance sensing was proven by evaluating figures of merit, such as the limit of detection (2 nM) and the selectivity ratio between a negative control and the sensing experiment (0.04), which is the best reported performance for an SPR S1 protein assay. These figures of merit outmatch those measured with more sophisticated biofunctionalization procedures involving chemical bonding of the capture antibodies to the gold surface. The present study opens up interesting new pathways toward the achievement of a cost-effective and scalable biofunctionalization protocol, which could guarantee the prolonged stability of the biolayer and easy handling of the biosensing system. © 2023 The Royal Society of Chemistry.},\n\tlanguage = {English},\n\tnumber = {27},\n\tjournal = {Journal of Materials Chemistry C},\n\tpublisher = {Royal Society of Chemistry},\n\tauthor = {Sarcina, L. and Scandurra, C. and Di Franco, C. and Caputo, M. and Catacchio, M. and Bollella, P. and Scamarcio, G. and Macchia, E. and Torsi, L.},\n\tyear = {2023},\n\tnote = {Number: 27},\n\tkeywords = {A-stable, Antibodies, Biofunctionalization, Chemical bonds, Cost effective, Cost effectiveness, Gold surfaces, Ionic strength, Long term stability, Performance, Physisorbed, Physisorption, SP3, Sensing applications, Solid interfaces, Stability, Surface coverages, Surface plasmon resonance, WP4},\n\tpages = {9093--9106},\n}\n\n\n\n

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\n Antibody physisorption at a solid interface is a very interesting phenomenon that has important effects on applications such as the development of novel biomaterials and the rational design and fabrication of high-performance biosensors. The strategy selected to immobilize biorecognition elements can determine the performance level of a device and one of the simplest approaches is physical adsorption, which is cost-effective, fast, and compatible with printing techniques as well as with green-chemistry processes. Despite its huge advantages, physisorption is very seldom adopted, as there is an ingrained belief that it does not lead to high performance because of its lack of uniformity and long-term stability, which, however, have never been systematically investigated, particularly for bilayers of capture antibodies. Herein, the homogeneity and stability of an antibody layer against SARS-CoV-2-Spike1 (S1) protein physisorbed onto a gold surface have been investigated by means of multi-parametric surface plasmon resonance (MP-SPR). A surface coverage density of capture antibodies as high as (1.50 ± 0.06) × 1012 molecules per cm−2 is measured, corresponding to a thickness of 12 ± 1 nm. This value is compatible with a single monolayer of homogeneously deposited antibodies. The effect of the ionic strength (is) of the antibody solution in controlling physisorption of the protein was thoroughly investigated, demonstrating an enhancement in surface coverage at lower ionic strength. An atomic force microscopy (AFM) investigation shows a globular structure attributed to is-related aggregations of antibodies. The long-term stability over two weeks of the physisorbed proteins was also assessed. High-performance sensing was proven by evaluating figures of merit, such as the limit of detection (2 nM) and the selectivity ratio between a negative control and the sensing experiment (0.04), which is the best reported performance for an SPR S1 protein assay. These figures of merit outmatch those measured with more sophisticated biofunctionalization procedures involving chemical bonding of the capture antibodies to the gold surface. The present study opens up interesting new pathways toward the achievement of a cost-effective and scalable biofunctionalization protocol, which could guarantee the prolonged stability of the biolayer and easy handling of the biosensing system. © 2023 The Royal Society of Chemistry.\n

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\n \n\n \n \n \n \n \n \n Assessing the Use of AutoML for Data-Driven Software Engineering.\n \n \n \n \n\n\n \n Calefato, F.; Quaranta, L.; Lanubile, F.; and Kalinowski, M.\n\n\n \n\n\n\n In 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pages 1–12, New Orleans, LA, USA, 2023. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Assessing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{calefato_assessing_2023,\n\taddress = {New Orleans, LA, USA},\n\ttitle = {Assessing the {Use} of {AutoML} for {Data}-{Driven} {Software} {Engineering}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {978-1-66545-223-6},\n\turl = {https://ieeexplore.ieee.org/document/10304796/},\n\tdoi = {10.1109/ESEM56168.2023.10304796},\n\turldate = {2024-09-10},\n\tbooktitle = {2023 {ACM}/{IEEE} {International} {Symposium} on {Empirical} {Software} {Engineering} and {Measurement} ({ESEM})},\n\tpublisher = {IEEE},\n\tauthor = {Calefato, Fabio and Quaranta, Luigi and Lanubile, Filippo and Kalinowski, Marcos},\n\tyear = {2023},\n\tkeywords = {SP1, WP4},\n\tpages = {1--12},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n System Architecture of TWIN: A New Digital Twin-Based Clinical Decision Support System for Type 1 Diabetes Management in Children.\n \n \n \n \n\n\n \n Cappon, G.; Pellizzari, E.; Cossu, L.; Sparacino, G.; Deodati, A.; Schiaffini, R.; Cianfarani, S.; and Facchinetti, A.\n\n\n \n\n\n\n In 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), pages 1–4, Boston, MA, USA, 2023. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"System$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

@inproceedings{cappon_system_2023,\n\taddress = {Boston, MA, USA},\n\ttitle = {System {Architecture} of {TWIN}: {A} {New} {Digital} {Twin}-{Based} {Clinical} {Decision} {Support} {System} for {Type} 1 {Diabetes} {Management} in {Children}},\n\tcopyright = {https://doi.org/10.15223/policy-029},\n\tisbn = {9798350338416},\n\tshorttitle = {System {Architecture} of {TWIN}},\n\turl = {https://ieeexplore.ieee.org/document/10331272/},\n\tdoi = {10.1109/BSN58485.2023.10331272},\n\turldate = {2024-09-10},\n\tbooktitle = {2023 {IEEE} 19th {International} {Conference} on {Body} {Sensor} {Networks} ({BSN})},\n\tpublisher = {IEEE},\n\tauthor = {Cappon, Giacomo and Pellizzari, Elisa and Cossu, Luca and Sparacino, Giovanni and Deodati, Annalisa and Schiaffini, Riccardo and Cianfarani, Stefano and Facchinetti, Andrea},\n\tyear = {2023},\n\tkeywords = {SP3, WP5},\n\tpages = {1--4},\n}\n\n\n\n

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