AI must be taught concepts, not just patterns in raw data
Nature, Published online: 04 March 2025; doi:10.1038/d41586-025-00663-6
AI must be taught concepts, not just patterns in raw dataNature, Published online: 04 March 2025; doi:10.1038/d41586-025-00663-6
AI must be taught concepts, not just patterns in raw dataNature, Published online: 04 March 2025; doi:10.1038/d41586-025-00618-x
As the European Unionβs Artificial Intelligence Act takes effect, AI systems that mimic how human teams collaborate can improve trust in high-risk situations, such as clinical medicine.bioRxiv [Preprint]. 2025 Feb 17:2025.02.13.637721. doi: 10.1101/2025.02.13.637721.
ABSTRACT
Cell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here we performed single nucleus multiomics and spatial transcriptomics in up to 32 non-diabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine sub-types. Beta, acinar, and other cell types, and related cellular niches, had altered abundance and gene activity in T1D progression, including distinct pathways altered in AAB+ compared to T1D. We identified epigenomic drivers of gene activity in T1D and AAB+ which, combined with genetic association, revealed causal pathways of T1D risk including antigen presentation in beta cells. Finally, single cell and spatial profiles together revealed widespread changes in cell-cell signaling in T1D including signals affecting beta cell regulation. Overall, these results revealed drivers of T1D progression in the pancreas, which form the basis for therapeutic targets for disease prevention.
PMID:40027657 | PMC:PMC11870426 | DOI:10.1101/2025.02.13.637721
Cell Death Discovery, Published online: 03 March 2025; doi:10.1038/s41420-025-02366-3
Enhancer reprogramming: critical roles in cancer and promising therapeutic strategies