Anti-ITGAM (aa 111-220) polyclonal antibody

Although cocaine exposure has been shown to potentiate neuroinflammation by upregulating glial activation in the brain, the role of mitophagy in this process remains an enigma. In the present study, we sought to examine the role of impaired mitophagy in cocaine-mediated activation of microglia and to determine the ameliorative potential of superoxide dismutase mimetics in this context. Our findings demonstrated that exposure of mouse primary microglial cells (mPMs) to cocaine resulted in decreased mitochondrial membrane potential, that was accompanied by increased expression of mitophagy markers, PINK1 and PRKN. Exposure of microglia to cocaine also resulted in increased expression of DNM1L and OPTN with a concomitant decrease in the rate of mitochondrial oxygen consumption as well as impaired mitochondrial functioning. Additionally, in the presence of cocaine, microglia also exhibited upregulated expression of autophagosome markers, BECN1, MAP1LC3B-II, and SQSTM1. Taken together, these findings suggested diminished mitophagy flux and accumulation of mitophagosomes in the presence of cocaine. These findings were further confirmed by imaging techniques such as transmission electron microscopy and confocal microscopy. Cocaine-mediated activation of microglia was further monitored by assessing the expression of the microglial marker (ITGAM) and the inflammatory cytokine (Tnf, Il1b, and Il6) mRNAs. Pharmacological, as well as gene-silencing approaches aimed at blocking both the autophagy/mitophagy and SIGMAR1 expression, underscored the role of impaired mitophagy in cocaine-mediated activation of microglia. Furthermore, superoxide dismutase mimetics such as TEMPOL and MitoTEMPO were shown to alleviate cocaine-mediated impaired mitophagy as well as microglial activation.

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/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-la 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 pro- files identified involvement of HIF-1 alpha signaling and the STAT3 hub gene.