ArticleMolecular medicine reports2015
Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods.
Article in Molecular medicine reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Spinal Cord Injury Affects Gene Expression of Transmembrane Proteins in Tissue and Release of Extracellular Vesicle in Blood: In Silico andCell journal · 2023Article
- Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis.Molecular medicine reports · 2017Article
- Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to explore the molecular mechanisms underlying the development of thoracic spinal cord injury (SCI). The gene expression profile of GSE20907, which included 12 thoracic non‑injured spinal cord control samples and 12 thoracic transected spinal cord samples at different stages of SCI, was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package in R/Bioconductor. DEG‑associated pathways were analyzed using the Kyoto encyclopedia of genes and genomes database. A protein‑protein interaction (PPI) network was constructed and transcription factors (TFs) were predicted using cytoscape. Compared with the control samples, there were 1,942, 396, 188 and 396 DEGs identified at day 3 (d3), week 1 (wk1), wk2 and month 1 (m1), respectively. Cluster analysis indicated that the DEGs at m1 were similar to those in the control group. Downregulated DEGs were enriched in nervous system disease pathways, such as Parkinson's disease. Upregulated DEGs were enriched in immune response‑associated pathways, such as Fc γ R‑mediated phagocytosis at early stages (d3 and wk1). Upregulated DEGs were enriched in pathways associated with cancer and pyrimidine metabolism at wk2 and m1, respectively. In the PPI network, nodes including RAC2, CD4, STAT3 and JUN were identified. Furthermore, ATF3, JUN and EGR1 were identified as TFs associated with SCI. In conclusion, the results of the present study showed that the number of DEGs decreased in a time‑dependent manner following SCI. OLIG1, ATF3 and JUN may represent SCI regeneration‑associated genes. Immune-associated inflammation was shown to be important in SCI, and SCI exhibits causal associations with other diseases, including cardiovascular disease and cancers. The present study provided novel insight into the molecular mechanisms of SCI regeneration, which may aid in the development of strategies to enhance recovery following SCI.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.