Identification of Key Biomarkers in Hepatocellular Carcinoma Induced by Non-alcoholic steatohepatitis or Metabolic Syndrome via Integrated Bioinformatics Analysis.

The burden of hepatocellular carcinoma (HCC) is steadily growing because obesity, type 2 diabetes, and nonalcoholic fatty liver disease (NAFLD) are replacing viral- and alcohol-related liver disease as major pathogenic promoters. The current study attempted to identify the key genes and pathways in the non-alcoholic steatohepatitis (NASH) induced development of HCC using integrated bioinformatics analyses. Two gene expression profiling datasets, GSE102079 and GSE164760 were downloaded. Differentially expressed genes (DEGs) from HCC and healthy control samples were screened. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource. Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Expression and survival analysis of hub genes, methylation and genetic mutation analysis were explored with GEPIA2, UALCAN, GSCA, and TIMER2.0 databases. We identified 158 overlapping genes from the 2 datasets. Up-regulated genes were mainly related to the proliferation, adhesion and metastasis of tumors, while down-regulated genes were mainly related to oxidative stress and energy metabolism. CDKN2A, SPP1, CYP2C9 and CYP4A11 were associated with prognostic performance and were considered the potential crucial genes, which SPP1, CYP2C9 and CYP4A11 were identified as the DNA methylation-driven genes. In different mutation statuses of HCC, gene expression of CDKN2A, SPP1, CYP2C9 and CYP4A11 showed significant differences. CDKN2A and SPP1 were identified as risk genes, while CYP2C9 and CYP4A11 were identified as protective genes, which may affect the transformation of NASH into HCC.

[Studies on detection of E. coli O157:H7 by ATP bioluminescence].

In the present paper, a quantitative linear model betweena series of concentrations of E. coliO157 : H7 and counts by BPCL ultra weak luminescence analyzer was built up. And the influences of four different buffers with the same pH (pH = 7.4), Tris-HCl, PBS, KH2PO4-NaOH and Na2 HPO4-C6H8O7, and five different chemical substances with the same mass concentration (10 g x L), NaCl, KCl, NaOH, MgCl2 and NaH2PO4 on ATP bioluminescence were compared. The results showed that Tris-HCl was a suitable buffer for dilution, since it could distinguish well between different concentrations and had the lowest background signals. And MgCl2 could intensify luminescence distinctly, while the other four chemical substances decreased luminescence, of which NaOH decreased luminescence most obviously. Moreover, ATP bioluminescence was correlated well with conventional culture methods (r = 0.96), and the detection limit was 10(3) cells x mL(-1).