Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis.

BACKGROUND: Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease. MATERIAL AND METHODS: Firstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs (differentially expressed mRNAs). Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR (real-time polymerase chain reaction) verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers. RESULTS: A total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers (such as RAB13, KIF1B, CLEC5A, FCER1A, CACNA2D3, DUSP3, HMGN3, MGST1 and ARHGEF18) for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock. CONCLUSION: Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.

[Antagonism of tert-butylhydroquinone on neurotoxicity and oxidative stress induced by paraquat in PC12].

OBJECTIVE: To investigate the protective effects of the tert-butylhydroquinone (tBHQ) pretreatment on neurotoxicity and oxidative stress induced by paraquat (PQ) in PC12 cells. METHODS: Cytotoxicity of PC12 cells was measured by MTT assay, following the PC12 cells treatment with different concentrations of 100, 300 micromol/L PQ for 24 h and 48 h. PC12 cells were pretreated with or without 40 micromol/L tBHQ for 4 h, PC12 cells were exposed to PQ at the doses of 0, 100, 300 micromol/L for 24 h and 48 h, respectively. The viability of PC12 cells was measured by MTT assay, the apoptosis rates of PC12 cells were detected by flow cytometry (FCM) and the malondialdehyde (MDA) levels of PC12 cells were examine by thiobarbituric acid (TBA) method. RESULTS: When the exposure doses of PQ were 100 and 300 micromol/L for 24 h, the viability of PC12 cells pretreated with tBHQ was significantly higher than that of PC12 cells only exposed to PQ (P < 0.05 or P < 0.01). When the exposure dose of PQ was 100 micromol/L for 48 h, the viability of PC12 cells pretreated with tBHQ was significantly higher than that of PC12 cells only exposed to PQ (P < 0.01). When the exposure doses of PQ were 100 and 300 micromol/L for 24 h, the apoptosis rates and MDA levels of PC12 cells pretreated with tBHQ were significantly lower than those of PC12 cells only exposed to PQ (P < 0.05 or P < 0.01). CONCLUSIONS: tBHQ pretreatment can reduce the cytotoxicity, apoptosis and oxidative stress induced by PQ in PC12 cells.