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cs.AI, q-bio.NC updates on arXiv.org
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AnyECG: Evolved ECG Foundation Model for Holistic Health Profiling
arXiv:2601.10748v1 Announce Type: cross Abstract: Background: Artificial intelligence enabled electrocardiography (AI-ECG) has demonstrated the ability to detect diverse pathologies, but most existing models focus on single disease identification, neglecting comorbidities and future risk prediction. Although ECGFounder expanded cardiac disease coverage, a holistic health profiling model remains needed. Methods: We constructed a large multicenter dataset comprising 13.3 million ECGs from 2.98
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Nature Medicine
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An eyecare foundation model for clinical assistance: a randomized controlled trial
Nature Medicine, Published online: 28 August 2025; doi:10.1038/s41591-025-03900-7Trained and validated on multimodal data from 14.5 million images from multicountry datasets, a foundation model is shown to increase diagnostic and referral accuracy of clinicians when used as an assistant in a trial involving 16 ophthalmologists and 668 patients.
An eyecare foundation model for clinical assistance: a randomized controlled trial
Nature Medicine, Published online: 28 August 2025; doi:10.1038/s41591-025-03900-7
Trained and validated on multimodal data from 14.5 million images from multicountry datasets, a foundation model is shown to increase diagnostic and referral accuracy of clinicians when used as an assistant in a trial involving 16 ophthalmologists and 668 patients.-
Most Recent Articles: Clinical Epigenetics
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Clinical performance evaluation of a plasma dual-target methylation test for the detection of primary liver cancer: a multicenter study
Primary liver cancer (PLC) is a global health concern. The plasma dual-target methylation (PDTM) test, which interrogates the methylation status of GNB4 and Riplet, exhibits a commendable ability to discriminate ...
Clinical performance evaluation of a plasma dual-target methylation test for the detection of primary liver cancer: a multicenter study
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Integrative single-cell and multi-omics analyses reveal ferroptosis-associated gene expression and immune microenvironment heterogeneity in gastric cancer
Discov Oncol. 2025 Jan 17;16(1):57. doi: 10.1007/s12672-025-01798-8.ABSTRACTGastric cancer (GC), a prevalent malignancy worldwide, encompasses a multitude of biological processes in its progression. Recently, ferroptosis, a novel mode of cell demise, has become a focal point in cancer research. The microenvironment of gastric cancer is composed of diverse cell populations, yet the specific gene expression profiles and their association with ferroptosis are not well understood. Our study employed
Integrative single-cell and multi-omics analyses reveal ferroptosis-associated gene expression and immune microenvironment heterogeneity in gastric cancer
Discov Oncol. 2025 Jan 17;16(1):57. doi: 10.1007/s12672-025-01798-8.
ABSTRACT
Gastric cancer (GC), a prevalent malignancy worldwide, encompasses a multitude of biological processes in its progression. Recently, ferroptosis, a novel mode of cell demise, has become a focal point in cancer research. The microenvironment of gastric cancer is composed of diverse cell populations, yet the specific gene expression profiles and their association with ferroptosis are not well understood. Our study employed single-cell RNA sequencing to thoroughly investigate the transcriptomic profiles and identify differential gene expression in gastric cancer, offering fresh insights into the cellular diversity and underlying molecular mechanisms of this disease. We discovered a set of significantly differentially expressed genes in GC, which may serve as valuable leads for future functional investigations. Subsequent analyses, including gene set intersection and functional enrichment, pinpointed genes implicated in ferroptosis and conducted comprehensive Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to elucidate their biological roles. In the gene selection and model validation section, critical genes were identified using machine learning algorithms, constructing a model with high predictive accuracy. Besides, distorted immune landscapes were further identified in RBL using ssGSEA analysis such that the complex association of gene expression features and its interaction networks as well as infiltration by various types of immune cells can be more clearly understood. Correlation analysis with different immune cell subtypes showed CTSB as an important regulator in the distributions of cancer infiltrating cells. Single-cell RNA sequencing analysis was utilized to map the cellular composition and gene expression profiles of cells in the gastric cancer microenvironment, which provide critical information for elucidating cellular heterogeneity as well as tumor microenvironment regulation in GC. Moreover, the distribution of FTH1, ZFP36 and CIRBP at different expression levels show new research prospects for functional information of these promoters in tumor microenvironment. In summary, the present study augments our knowledge of molecular mechanisms underlying gastric tumorigenesisa and provide scientific basis for identifing new targets and biomarkers in therapeutic diagnosis.
PMID:39831925 | PMC:PMC11747029 | DOI:10.1007/s12672-025-01798-8
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Cell Death Discovery nature.com science feeds
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OTUB1/NDUFS2 axis promotes pancreatic tumorigenesis through protecting against mitochondrial cell death
Cell Death Discovery, Published online: 23 April 2024; doi:10.1038/s41420-024-01948-xOTUB1/NDUFS2 axis promotes pancreatic tumorigenesis through protecting against mitochondrial cell death
OTUB1/NDUFS2 axis promotes pancreatic tumorigenesis through protecting against mitochondrial cell death
Cell Death Discovery, Published online: 23 April 2024; doi:10.1038/s41420-024-01948-x
OTUB1/NDUFS2 axis promotes pancreatic tumorigenesis through protecting against mitochondrial cell death