ArticleFrontiers in immunology2026
Integrated machine learning and transcriptomics reveal immune infiltration-related orthologous transcription genes in cerebral ischemic injury.
Article in Frontiers in immunology, 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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Abstract
Background: Ischemic brain injury is a major contributor to global mortality and disability. Despite extensive pathological characterization, systematic integration of rodent transcriptomic data remains limited. This study investigates orthologous transcription factors (TFs) in cerebral ischemia models and their roles in regulating neuroinflammation to develop novel diagnostic and/or predictive biomarkers. Methods: We employed an integrated bioinformatics approach to analyze RNA-seq data from ten public datasets. Robustly up- and down-regulated differentially expressed genes (DEGs) were first identified from integrated rat and mouse datasets, followed by functional enrichment analysis. Orthologous TFs co-expressed in both species were screened from these robust DEGs and functionally characterized. Using machine learning, a diagnostic biomarker panel comprising five TFs ( Results: Robust DEGs common to rats and mice were primarily enriched in immune cell differentiation, immune responses, and synaptic signaling. Screening identified 51 orthologous TFs similarly enriched in leukocyte differentiation and development pathways. The machine learning-derived biomarker panel ( Conclusion: This study identifies
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