Results 151 to 160 of about 303,207 (215)

Integrated Single‐Cell and Spatial Analysis Reveals a Metabolic‐Immune Axis Driving Aortic Dissection

open access: yesAdvanced Science, EarlyView.
Single‐cell and spatial profiling of 110 human thoracic aortic samples reveals a stromal–immune circuit driving aortic dissection. An elastin‐rich fibroblast subset is depleted with age and markedly reduced in disease, weakening aortic wall integrity.
Jing Tao   +25 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

CK2α Deficiency Drives Myocardial Fibrosis via Desmin‐Induced Mitochondrial Dysfunction

open access: yesAdvanced Science, EarlyView.
CK2α preserves mitochondrial homeostasis by phosphorylating Desmin to recruit Cryab, ensuring proper filament assembly. CK2α deficiency disrupts this interaction, causing mitochondrial dysfunction, metabolic shifts, bioenergetic failure, and oxidative stress—ultimately establishing a pro‐fibrotic environment that drives cardiac fibrosis.
Canjie Ma   +12 more
wiley   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen   +6 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

When complexity does not pay: benchmarking deep learning and ensemble methods for biomarker discovery. [PDF]

open access: yesBrief Bioinform
Njume CM   +9 more
europepmc   +1 more source

Master Regulator SMC1A, Stabilized by N6‐Methyladenosine Reader IGF2BP1, Promotes HCC Progression Through Facilitating Enhancer–Promoter Interaction of Nestin

open access: yesAdvanced Science, EarlyView.
IGF2BP1‐mediated m6A stabilization sustains SMC1A expression, enabling cohesin‐associated chromatin regulation of Nestin in hepatocellular carcinoma. This work reveals an epitranscriptomic‐chromatin‐cytoskeletal regulatory axis linked to malignant phenotypes and identifies SMC1A as a biologically relevant vulnerability in HCC.
Zhenxiang Peng   +7 more
wiley   +1 more source

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