ArticleMolecular medicine reports2017
Identification of key genes and pathways associated with spinal cord injury.
Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Unraveling the role of MAG, PTEN, and NOTCH1 in axonal regeneration: a network analysis and molecular dynamics study of siRNA/drugs/nanocarriers interactions.Journal of translational medicine · 2025Article
- Apelin alleviated neuroinflammation and promoted endogenous neural stem cell proliferation and differentiation after spinal cord injury in rats.Journal of neuroinflammation · 2022Article
- Bioinformatic analysis of the gene expression profile in muscle atrophy after spinal cord injury.Scientific reports · 2021Article
- A Time-Course Study of the Expression Level of Synaptic Plasticity-Associated Genes in Un-Lesioned Spinal Cord and Brain Areas in a Rat Model of Spinal Cord Injury: A Bioinformatic Approach.International journal of molecular sciences · 2021Article
- Identification of four differentially expressed genes associated with acute and chronic spinal cord injury based on bioinformatics data.Neural regeneration research · 2021Article
- Age and Sex-Related Changes to Gene Expression in the Mouse Spinal Cord.Journal of molecular neuroscience : MN · 2019Article
- Chronic spinal cord changes in a high-fat diet-fed male rat model of thoracic spinal contusion.Physiological genomics · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study was designed to identify key genes or significant signaling pathways associated with spinal cord injury (SCI), and to clarify the underlying molecular mechanisms of SCI. Data from the GSE45550 array were downloaded from the Gene Expression Omnibus database. A total of 6 control samples, 6 samples at 3 days post‑SCI (SCI3d), 6 samples at 8 days post‑SCI (SCI8d) and 6 samples at 14 days post‑SCI (SCI14d) were included. The microarray data was preprocessed by the robust multi‑array average algorithm. The differentially expressed genes (DEGs) were identified using the limma package. The overlapping DEGs among groups were analyzed using the Venny 2.0 online tool. Modules enriched by DEGs were selected by weighted gene co‑expression network analysis. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathways were identified for DEGs using the Database for Annotation, Visualization and Integrated Discovery. A total of 693 genes were obtained by combining the DEGs of the SCI3d, SCI8d and SCI14d groups. The pink module and green module with smaller P‑values obtained from weighted gene co‑expression network analysis module analyses of DEGs demonstrated a higher correlation with SCI. In addition, the peroxisome proliferator‑activated receptor (PPAR) signaling pathway that the cluster of differentiation 36 (CD36) was significantly enriched in, was one of the significant pathways in the pink module. The p53 signaling pathway that Caspase‑3 (Casp3) was significantly enriched in was one of the significant pathways in the green module. In conclusion, the results of the present study demonstrated that the PPAR and p53 signaling pathway may serve important roles in the progression of SCI. In addition, CD36 and Casp3 may be involved in the progression of SCI via the PPAR and p53 signaling pathways, respectively.
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