Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0920646 (renal ischemia)
 2,515 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The cell type-, organ-, and species-specific expression of the pattern-recognition receptors (PRRs) are well described but little is known about the respective expression profiles of their negative regulators. We therefore determined the mRNA expression levels of A20, CYLD, DUBA, ST2, CD180, SIGIRR, TANK, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, SHP1, SHP2, TOLLIP, IRF4, SIKE, NLRX1, ERBIN, CENTB1, and Clec4a2 in human and mouse solid organs. Humans and mice displayed significant differences between their respective mRNA expression patterns of these factors. Additionally, we characterized their expression profiles in mononuclear blood cells upon bacterial endotoxin, which showed a consistent induction of A20, SOCS3, IRAK-M, and Clec4a2 in human and murine cells. Furthermore, we studied the expression pattern in transient kidney ischemia-reperfusion injury versus post-ischemic atrophy and fibrosis in mice. A20, CD180, ST2, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, IRF4, CENTB1, and Clec4a2 were all induced, albeit at different times of injury and repair. Progressive fibrosis was associated with a persistent induction of these factors. Thus, the organ- and species-specific expression patterns need to be considered in the design and interpretation of studies related to PRR-mediated innate immunity, which seems to be involved in tissue injury, tissue regeneration and in progressive tissue scarring.
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PMID:Pattern-recognition receptor signaling regulator mRNA expression in humans and mice, and in transient inflammation or progressive fibrosis. 2400 23

BACKGROUND This study aimed to identify hub genes and pathways in a rat model of renal ischemia-reperfusion injury (IRI) using bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset and integration of gene expression profiles. MATERIAL AND METHODS GEO software and the GEO2R calculation method were used to analyze two mRNA profiles, including GSE 39548 and GSE 108195. The co-expression of differentially expressed genes (DEGs) were identified and searched in the DAVID and STRING databases for pathway and protein-protein interaction (PPI) analysis. Cytoscape was used to draw the PPI network. DEGs were also analyzed using the Molecular Complex Detection (MCODE) algorithm. Cytoscape and cytoHubba were used to analyze the hub genes and visualize the molecular interaction networks. Rats (n=20) included the IRI model group (n=10) and a control group (n=10). Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to measure and compare the expression of the identified genes in rat renal tissue in the IRI model and the control group. RESULTS Ten hub genes were identified, STAT3, CD44, ITGAM, CCL2, TIMP1, MYC, THBS1, IGF1, SOCS3, and CD14. Apart from IGF1, qRT-PCR showed that expression of these genes was significantly increased in renal tissue in the rat model of IRI. The HIF-1alpha signaling pathway was involved in IRI in the rat model, which was supported by MCODE analysis. CONCLUSIONS In a rat model of renal IRI, bioinformatics analysis of the GEO dataset and integration of gene expression profiles identified involvement of HIF-1alpha signaling and the STAT3 hub gene.
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PMID:Identification of Hub Genes and Pathways in a Rat Model of Renal Ischemia-Reperfusion Injury Using Bioinformatics Analysis of the Gene Expression Omnibus (GEO) Dataset and Integration of Gene Expression Profiles. 3169 60