ArticleGenes2025
Identification of Differentially Expressed Genes in Spinal Cord Injury.
Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- DHCR24 in cholesterol metabolism and diseases of the nervous system.Lipids in health and disease · 2026Review
- Regional Molecular Diversity in Chronic Spinal Cord Injury.Cellular and molecular neurobiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundSpinal cord injury (SCI) remains a profound medical challenge, with limited therapeutic options available. Studies focusing on individual molecular markers have limitations in addressing the complex disease process.
methodsThis study utilizes RNA-sequencing (RNA-seq) to investigate the differentially expressed genes (DEGs) in spinal cord tissue from a rat SCI model at 1 and 21 days post-injury (dpi). After data processing and analysis, a series of biological pathway enrichment analyses were performed using online tools DAVID and GSEA. Interactions among the enriched genes were studied using Cytoscape software to visualize protein-protein interaction networks.
resultsOur analysis identified 595 DEGs, with 399 genes significantly upregulated and 196 significantly downregulated at both time points.
conclusionsOur findings highlight complex immune and autoimmune responses that contribute to ongoing inflammation and tissue damage post-SCI, underscoring new avenues for therapeutic interventions targeting these molecular processes.
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Registered trials
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