Objective:To investigate the value of programmed death-1（PD-1） expression on the T lymphocytes for the prognosis of septic patients.Methods:From September 2017 to May 2019, septic patients were included in Department of Intensive Care Unit at 6 hospitals. The PD-1 expression on T cells were measured by flow cytometry. Logistic regression was conducted to analyze independent risk factors related to death within 28 days，and receiver operating characteristic curve(ROC) was conducted to evaluate the prognostic value of PD-1 expression on T cells in septic patients.Results:A total of 64 septic patients were enrolled to this study，including 32 survivors and 32 deaths. The PD-1 expression on T cells in the death group was significantly higher than that in the surviving group ( P<0.05). Correlation analysis showed that the percentages of PD-1 +/CD3 +T cells and PD-1 +/CD8 +T cells were positively correlated with procalciton in ( r=0.313, P =0.015； r=0.375, P=0.003), logistic regression analysis showed that the percentages of PD-1 +/CD3 +，PD-1 +/CD4 +，PD-1 +/CD8 +T cells were independent risk factors for the death of sepsis patients. The percentage of PD-1 +/CD3 +T cell was 3.63%, with AUC 0.842, sensitivity to predict the mortality 96.43% and specificity 59.38%, ( P<0.000 1). The percentage of PD-1 +/CD4 +T cell was 4.65%, with AUC 0.847, sensitivity 96.43%, specificity 62.50%，( P<0.000 1). The percentage of PD-1 +/CD8 +T cell was 3.91%, with AUC 0.771, sensitivity 64.29%, specificity 81.25%，( P=0.000 3). Conclusions:The T cell PD-1 expression is an independent risk factor to predict the 28-day mortality in septic patients. Combining the proportions of PD-1 +/CD3 +, PD-1 +/CD4 +and PD-1 +/CD8 +T cells may further enhance the predictive value for death.

Objective:To identify the Key genes in the development of sepsis through weighted gene co-expression network analysis (WGCNA).Methods:The gene expression dataset GSE154918 was downloaded from the public database Gene Expression Omnibus (GEO) database, which containes data from 105 microarrays of 40 control cases, 12 cases of asymptomatic infection, 39 cases of sepsis, and 14 cases of follow-up sepsis. The R software was used to screen out differentially expressed genes (DEG) in sepsis, and the distributed access view integrated database (DAVID), search tool for retrieval of interacting neighbouring genes (STRING) and visualization software Cytoscape were used to perform gene function and pathway enrichment analysis, Protein-protein interaction (PPI) network analysis and key gene analysis to screen out the key genes in the development of sepsis.Results:Forty-six candidate genes were obtained by WGCNA and combined with DEG expression analysis, and these 46 genes were analyzed by gene ontology (GO) and Kyoto City Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to obtain gene functions and involved signaling pathways. The PPI network was further constructed using the STRING database, and 5 key genes were selected by the PPI network visualization software Cytoscape, including the mast cell expressed membrane protein 1 gene (MCEMP1), the S100 calcium-binding protein A12 gene (S100A12), the adipokine resistance factor gene (RETN), the c-type lectin structural domain family 4 member gene (CLEC4D), and peroxisome proliferator-activated receptor gene (PPARG), and differential expression analysis of each of these 5 genes showed that the expression levels of the above 5 genes were significantly upregulated in sepsis patients compared with healthy controls.Conclusion:In this study, 5 key genes related to sepsis were screened by constructing WGCNA method, which may be potential candidate targets related to sepsis diagnosis and treatment.

Sepsis is a common disease in critical patients, which may lead to myocardial damage, thereby aggravating the severity of the patients' condition, and causing adverse prognosis. How to detect sepsis with myocardial injury as early as possible, and use corresponding treatment measures on time are essential. Cardiac troponin I (cTnI), brain natriuretic peptide (BNP), myoglobin (Mb), MB isoenzyme of creatine kinase (CK-MB) and other traditional cardiac markers are easily affected by the complications of other critical diseases, thus the diagnostic value of those markers for myocardial injury of sepsis is reduced. In recent years, there have been some studies on heart-type fatty acid binding protein (H-FABP), microRNA (miRNA), soluble triggering receptor expressed on myeloid cell-1 (sTREM-1), high mobility group protein B1 (HMGB1), neutrophil gelatinase-associated lipocalin (NGAL), histone and other new biomarkers of myocardial injury in septic patients. This article reviewed the value of these unconventional cardiac markers in the diagnosis of sepsis-induced myocardial injury, with the hope to provide some help for clinic.

Sepsis is a common disease in critical patients, which may lead to myocardial damage, thereby aggravating the severity of the patients' condition, and causing adverse prognosis. How to detect sepsis with myocardial injury as early as possible, and use corresponding treatment measures on time are essential. Cardiac troponin I (cTnI), brain natriuretic peptide (BNP), myoglobin (Mb), MB isoenzyme of creatine kinase (CK-MB) and other traditional cardiac markers are easily affected by the complications of other critical diseases, thus the diagnostic value of those markers for myocardial injury of sepsis is reduced. In recent years, there have been some studies on heart-type fatty acid binding protein (H-FABP), microRNA (miRNA), soluble triggering receptor expressed on myeloid cell-1 (sTREM-1), high mobility group protein B1 (HMGB1), neutrophil gelatinase-associated lipocalin (NGAL), histone and other new biomarkers of myocardial injury in septic patients. This article reviewed the value of these unconventional cardiac markers in the diagnosis of sepsis-induced myocardial injury, with the hope to provide some help for clinic.
Biomarkers ; Creatine Kinase, MB Form ; Humans ; Myocardial Infarction ; Myoglobin ; Natriuretic Peptide, Brain ; Sepsis ; Troponin I