Results 171 to 180 of about 18,072,840 (248)

CausalCellInfer: Prioritizing Cell‐Type‐Specific Disease Associations From Genetically Predicted Transcriptomes in Biobank Cohorts

open access: yesAdvanced Science, EarlyView.
Bulk and genotype‐imputed transcriptomes obscure the cellular drivers of complex disease. CausalCellInfer resolves them by integrating invariant marker selection, deep learning deconvolution, and regularized matrix completion. Applied to ∼500 000 UK Biobank participants across 29 traits, it uncovers hallmark cell‐type proportion shifts, including ...
Liangying Yin   +6 more
wiley   +1 more source

Structural Variants in the Human Genome Associated With Gut Microbiome and Blood Metabolic Traits With Potential Causal Links

open access: yesAdvanced Science, EarlyView.
Based on a multi‐omics cohort of 2002 individuals comprising high‐depth whole‐genome and metagenomic sequencing data, blood metabolites, and detailed questionnaires, we identified 138 859 high‐confidence SVs, uncovering 36 significant SV–microbiome associations and 48 SV–blood metabolite associations.
Qun Zhou   +13 more
wiley   +1 more source

Improved Skills for Predicting Sub‐Seasonal to Seasonal Global Sea Surface Temperature

open access: yesAdvanced Science, EarlyView.
Addressing the critical Sub‐seasonal to Seasonal predictability gap, this study presents CAS‐Canglong, a novel deep learning framework. By leveraging 3D Swin‐Transformers to capture long‐range ocean interactions, the model demonstrates superior skill over traditional GCMs.
Longhao Wang   +6 more
wiley   +1 more source

Astrocytic Ketogenesis Protects Central Nervous System Injury via CPT1A Stabilization and Epigenetic Regulation

open access: yesAdvanced Science, EarlyView.
A distinct astrocyte subpopulation, enriched at the lesion border, drives CNS repair through enhanced ketone body metabolism. This process promotes neuronal survival and axonal sparing via CPT1A stabilization and H3K9bhb‐dependent epigenetic reprogramming, positioning astrocytic ketogenesis as a promising therapeutic target for tissue regeneration ...
Dishui Pan   +14 more
wiley   +1 more source

An Explainable Multimodal Deep‐Learning Model Using Histopathological Image and Clinical Information for Prognosis Prediction in Colorectal Cancer: A Multi‐Center Cohort Study

open access: yesAdvanced Science, EarlyView.
This study develops a multimodal deep‐learning model that integrates clinical variables and histopathological images to predict survival outcomes in colorectal cancer. The multimodal model effectively stratifies patients into low‐ and high‐risk groups, demonstrating superior accuracy and generalizability across multiple independent cohorts.
Zhihan Jiang   +12 more
wiley   +1 more source

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