ArticleAnnals of translational medicine2021
Identification and analysis of spinal cord injury subtypes using weighted gene co-expression network analysis.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 12 citations in OpenAlex.
- Identification of age-specific biomarkers of spinal cord injury: A bioinformatics analysis of young and aged mice models.Brain and behavior · 2023Article
- Disease- and headache-specific microRNA signatures and their predicted mRNA targets in peripheral blood mononuclear cells in migraineurs: role of inflammatory signalling and oxidative stress.The journal of headache and pain · 2022Article
- Application value of biofluid-based biomarkers for the diagnosis and treatment of spinal cord injury.Neural regeneration research · 2022Article
- Potential value of differentially expressed circular RNAs derived from circulating exosomes in the pathogenesis of rat spinal cord injury.Frontiers in neuroscience · 2022Article
- Bioinformatic analysis of the gene expression profile in muscle atrophy after spinal cord injury.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSpinal cord injury (SCI) has an immediate and devastating impact on the control over various movements and sensations. However, no effective therapies for SCI currently exist.
methodsTo identify and analyze SCI subtypes, we obtained the expression profile data of the 1,057 genes (889 intersection genes) in GSE45550 using weighted gene co-expression network analysis (WGCNA), and 14 co-expression gene modules were identified. Next, we filtered out the network degree top 10 (degree >80) genes, considered the final key SCI genes. A multifactor regulatory network (105 interaction pairs), consisting of messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), and transcription factors (TFs) was constructed. This network was involved in the co-expression of key genes. We selected the top 10 regulatory factors (degree >4) as core regulators in the multifactor regulatory network.
resultsThe results of functional enrichment analysis of the target gene expressing the core regulatory factor [1,059] showed that these target genes were enriched in pathways for human cytomegalovirus infection, chronic myeloid leukemia, and pancreatic cancer. Further, we used the key genes in the co-expression network to categorize the SCI samples in GSE45550. The expression levels of the top 6 genes (
conclusionsThese results may provide a novel therapeutic strategy for the treatment of SCI.
Indexed as
Identifiers
What OpenQuestion holds
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.