ArticleJournal of orthopaedic surgery and research2018
Bioinformatics analysis of differentially expressed genes in rotator cuff tear patients using microarray data.
Article in Journal of orthopaedic surgery and research, 2018. 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
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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
5 citing papers in PubMed, 15 citations in OpenAlex.
- Transcriptional time course after rotator cuff repair in 6 month old female rabbits.Frontiers in physiology · 2023Article
- Extended adverse effects of cyclophosphamide on mouse ovarian function.BMC pharmacology & toxicology · 2021Article
- Transcriptional Time Course After Rotator Cuff Tear.Frontiers in physiology · 2021Article
- Genetic Aspects in Shoulder Disorders.Revista brasileira de ortopedia · 2020Article
- Identify differential gene expressions in fatty infiltration process in rotator cuff.Journal of orthopaedic surgery and research · 2019Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundRotator cuff tear (RCT) is a common shoulder disorder in the elderly. Muscle atrophy, denervation and fatty infiltration exert secondary injuries on torn rotator cuff muscles. It has been reported that satellite cells (SCs) play roles in pathogenic process and regenerative capacity of human RCT via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) of SCs that regulated between the torn supraspinatus (SSP) samples and intact subscapularis (SSC) samples, identify their functions and molecular pathways.
methodsThe gene expression profile GSE93661 was downloaded and bioinformatics analysis was made.
resultsFive hundred fifty one DEGs totally were identified. Among them, 272 DEGs were overexpressed, and the remaining 279 DEGs were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene-gene interaction network analysis such as GNG13, GCG, NOTCH1, BCL2, NMUR2, PMCH, FFAR1, AVPR2, GNA14, and KALRN, that may contribute to the understanding of the molecular mechanisms of secondary injuries in RCT. We also discovered that GNG13/calcium signaling pathway is highly correlated with the denervation atrophy pathological process of RCT.
conclusionThese genes and pathways provide a new perspective for revealing the underlying pathological mechanisms and therapy strategy of RCT.
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Registered trials
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