ArticleFrontiers in molecular neuroscience2025
Exploring hypoxia-related genes in spinal cord injury: a pathway to new therapeutic targets.
Article in Frontiers in molecular neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Deferoxamine mitigates neuronal loss following spinal cord injury via ferroptosis inhibition and Nrf2/HO‑1 pathway activation.International journal of molecular medicine · 2026Article
- Bioinformatics Analysis of Genes Associated with Autophagy and Metabolic Reprogramming in Atrial Fibrillation.Journal of cardiovascular development and disease · 2026Article
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Authors and funding
5 authors.
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Abstract
Introduction: Spinal cord injury (SCI) remains a debilitating condition with limited therapeutic options. Exploring hypoxia-related genes in SCI may reveal potential therapeutic targets and improve our understanding of its pathogenesis. Methods: We developed a diagnostic model using LASSO regression and Random Forest algorithms to investigate hypoxia-related genes in SCI. The model identified critical biomarkers by analyzing differentially expressed genes (DEGs) and hypoxia-related DEGs (HRDEGs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the biological roles of HRDEGs. The model's accuracy was validated using receiver operating characteristic curves, calibration plots, decision curves, and qPCR experiments. Results: The diagnostic model identified Casp6, Pkm, Cxcr4, and Hexa as critical biomarkers among 186 HRDEGs out of 9,732 altered genes in SCI. These biomarkers were significantly associated with SCI pathogenesis. GO and KEGG analyses highlighted their roles in hypoxia responses, particularly through the hypoxia-inducible factor 1 pathway. The model demonstrated high accuracy, with an area under the curve exceeding 0.9. GSEA and GSVA revealed distinct pathways in low- and high-risk SCI groups, suggesting potential clinical stratification strategies. Discussion: This study constructed a diagnostic model that confirmed
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