Marra A, Morganti S, Pareja F, et al. Artificial intelligence entering the pathology arena in oncology: current applications and future perspectives. Annals of oncology : official journal of the European Society for Medical Oncology. 2025;36(7):712-725. doi:10.1016/j.annonc.2025.03.006
Publications
Hernández-Cacho A, GarcÃa-Gavilán JF, Atzeni A, et al. Multi-omics approach identifies gut microbiota variations associated with depression. NPJ biofilms and microbiomes. 2025;11(1):68. doi:10.1038/s41522-025-00707-9
Mvundura M, Ngwira LG, Shrestha KB, et al. Cost-effectiveness of wastewater-based environmental surveillance for SARS-CoV-2 in Blantyre, Malawi and Kathmandu, Nepal: A model-based study. PLOS global public health. 2025;5(4):e0004439. doi:10.1371/journal.pgph.0004439
Atzeni A, Hernández-Cacho A, Khoury N, et al. The link between ultra-processed food consumption, fecal microbiota, and metabolomic profiles in older mediterranean adults at high cardiovascular risk. Nutrition journal. 2025;24(1):62. doi:10.1186/s12937-025-01125-5
Myserlis EP, Georgakis MK, Parodi L, et al. A Beneficial Role for Gluteofemoral Adipose Tissue in Cerebrovascular Disease: Causal Pathway and Mediation Analysis. Neurology. 2025;104(9):e213573. doi:10.1212/WNL.0000000000213573
Wu K, Li Y, Yi Y, et al. The detection, function, and therapeutic potential of RNA 2’-O-methylation. The innovation life. 2025;3(1). doi:10.59717/j.xinn-life.2024.100112
Schaffer L V, Hu M, Qian G, et al. Multimodal cell maps as a foundation for structural and functional genomics. Nature. 2025;642(8066):222-231. doi:10.1038/s41586-025-08878-3
Mathew V, Khan RR, Jowell AR, et al. Genetic Risk and First-Trimester Cardiovascular Health Predict Hypertensive Disorders of Pregnancy in Nulliparous Women. Journal of the American College of Cardiology. 2025;85(14):1488-1500. doi:10.1016/j.jacc.2025.02.015
Pagidipati N, Heidenfelder B, Kwee LC, et al. Returning Individual-Level Urgent or Emergent Research Results to Participants: The Project Baseline Health Study Experience. American journal of medicine open. 2025;13:100092. doi:10.1016/j.ajmo.2025.100092
Radhakrishnan A, Belkin M, Drusvyatskiy D. Linear Recursive Feature Machines provably recover low-rank matrices. Proceedings of the National Academy of Sciences of the United States of America. 2025;122(13):e2411325122. doi:10.1073/pnas.2411325122