Objective To identify genes of lipopolysaccharide (LPS) -induced acute lung injury (ALI) in mice base on bioinformatics and machine learning. Methods The acute lung injury dataset (GSE2411, GSE111241 and GSE18341) were download from the Gene Expression Database (GEO). Differential gene expression analysis was conducted. Gene ontology (GO) analysis, KEGG pathway analysis, GSEA enrichment analysis and protein-protein interaction analysis (PPI) network analysis were performed. LASSO-COX regression analysis and Support Vector Machine Expression Elimination (SVM-RFE) was utilized to identify key biomarkers. Receiver operator characteristic curve was used to evaluate the diagnostic ability. Validation was performed in GSE18341. Finally, CIBERSORT was used to analyze the composition of immune cells, and immunocorrelation analysis of biomarkers was performed. Results A total of 29 intersection DEGs were obtained after the intersection of GSE2411 and GSE111241 differentially expressed genes. Enrichment analysis showed that differential genes were mainly involved in interleukin-17, cytokine - cytokine receptor interaction, tumor necrosis factor and NOD-like receptor signaling pathways. Machine learning combined with PPI identified Gpx2 and Ifi44 were key biomarkers. Gpx2 is a marker of ferroptosis and Ifi44 is an type I interferon-induced protein, both of which are involved in immune regulation. Immunocorrelation analysis showed that Gpx2 and Ifi44 were highly correlated with Neutrophils, TH17 and M1 macrophage cells. Conclusion Gpx2 and Ifi44 have potential immunomodulatory abilities, and may be potential biomarkers for predicting and treating ALI in mince.
Objective To investigate the clinical characteristics of patients with sever H1N1 influenza in Xinjiang region, and analyze risk factors related to patients’prognosis. Methods 63 patients with severe H1N1 influenza from September 2009 to December 2009, who came from five general hospitals and contagious disease hospitals were retrospectively studied. Data of baseline characteristics, treatment, and outcomes were collected. Results Among the 63 cases of severe H1N1 influenza patients, 46 patients survived, in which 30 cases were complicated with pneumonia( 63. 8% ) , 10 cases with MODS ( 43. 48% ) ;26 were male,20 were female; the median age was ( 28. 48 ±19. 59) years old.17 patients died, in which 11 were male, 6 were female; the median age was ( 39. 47 ±21. 23) years old. There were no significantdifferences in white blood cells, neutrophils, granulocytes, lymphocytes, Hb, platelets, CK-MB, HB, DH, UN,APTT, INR, K+ , Na+ , Cl - , PaO2 , SaO2 between the survival patients and the died patients ( P gt; 0. 05) .However there were significant differences in AST, ALT, CK, LDH, AL, CR, and pH ( P lt; 0. 05) .Conclusions Most of the patients with sever H1N1 influenza are young. The typical clinical manifestations are fever, cough, and expectoration. The patients usually are complicated with pneumonia. The patients complicated with MODS have a higher risk of death. Early administration of effective antiviral agents, low dose corticosteroids, and reasonable mechanical ventilation may improve the prognosis.