ArticleSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2026
[Integrating Bioinformatics and Machine Learning Algorithms to Screen Inflammatory Biomarkers for Atrial Fibrillation and Experimental Validation].
Article in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
Objective: To identify potential biomarkers of atrial fibrillation (AF) using bioinformatics, machine learning (ML) and experimental methods. Methods: AF transcriptomic data were obtained from the GEO and MSigDB databases to screen for differentially expressed genes (DEGs) and inflammation-related gene sets (IRGs). The overlap between DEGs and IRGs was used to identify the DE-IRGs set. Two machine learning algorithms were used to filter AF-related DE-IRGs. Twelve male SD rats were randomly divided into a control group and an AF group. Rats received acetylcholine (66 μg/mL) and calcium chloride (10 mg/kg) via tail vein injection for five consecutive weeks to establish the AF model. Morphological characteristics of atrial myocytes were assessed with HE staining, while RT-qPCR and immunohistochemistry (IHC) were used to measure changes in mRNA and protein levels. Results: In the training set, 119 DEGs were identified, with IRGs showing the highest correlation with two co-expression modules ( Conclusion: The characteristic genes
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