Bioinformatic Analysis of Key Biomarkers and Infiltrating Immune Cells in Nonalcoholic Fatty Liver Disease.

Context: The liver is both the largest metabolic and the largest immune organ and is closely related to the mechanisms of disease development. Clarifying the immune environment of the NAFLD liver to determine its interactions with biomarkers would be beneficial in exploring the mechanisms of disease development. Objective: The study aimed to identify biomarkers and immune cells associated with nonalcoholic fatty liver disease (NAFLD) and to analyze the correlation between key genes and immune cells in NAFLD, to improve the understanding of the mechanisms underlying NAFLD and provide potential therapeutic targets. Design: The research team performed a genetic study. Setting: The study took place at Qingdao, Shandong Province, China. Outcome Measures: The research team: (1) obtained the NAFLD-related datasets GSE63067, GSE48452, and GSE89632 from the Gene Expression Omnibus (GEO) database; (2) analyzed immune-cell infiltrates using single-sample gene set enrichment analysis (ssGSEA) to determine the hub immune cells; (3) selected the differentially expressed genes (DEGs) between the NAFLD and normal samples and screened them to identify the hub genes; (4) evaluated the efficiency of the hub genes using receiver operating characteristic (ROC) curves; and (5) analyzed the correlations between hub genes and immune cells. Results: The research team: (1) found 28 differential immune cells; (2) identified monocytes as the hub immune cells; (3) identified 55 DEGs; (4) comparing the top 10 genes, identified five hub genes: S100 calcium binding proteins A12 (S100A12), S100A9, S100A8, selectin L (SELL), and sex hormone binding globulin (SHBG); (5) for all five, the area under the ROC curve (AUC) was greater than 0.6-training set: AUCSA00A12 = 0.699, AUCSELL = 0.743, AUCS100A9 = 0.735, AUCSHBG = 0.752, and AUCS100A8 = 0.703; and validation set: AUCSA00A12 = 0.852, AUCSELL = 0.905, AUCS100A9 = 0.819, AUCSHBG = 0.830, and AUCS100A8 = 0.822; (6) negatively correlated SHBG with immune cells (P > .05, r=-0.09); and (7) positively correlated S100A12, S100A9, S100A8, and SELL with immune cells-rS100A8 = 0.40, rS100A9 = 0.50, rS100A12 = 0.38, and rSELL = 0.42, respectively. Conclusions: Based on bioinformatic analyses, the progression of NAFLD may involve monocytes through promotion of liver inflammation. The hub genes S100A12, S100A9, S100A8, SELL, and SHBG are potential biomarkers that may be useful as diagnostic tools or therapeutic targets for NAFLD.

Nurse anesthetist training Center on IFNA standards in Mainland China.

AIM: The first training center for nurse anesthetists in Jiangsu Province, China was established. The aim of this study is to understand the status of and effectiveness of a training program based on International Federation of Nurse Anesthetists (IFNA) standards for nurse anesthetists in China. BACKGROUND: China recently issued a clear policy to improve the quality of anesthesia care and to ensure the safety and comfort of patients. As a result, the roles of nurse anesthetists have received more attention, highlighting the importance of the development and implementation of relevant training. INTRODUCTION: IFNA standards were applied to the development of a specialized training program for nurse anesthetists, which is expected to serve as a reference for various medical institutions and to lead to increased uniformity and improvement in the quality and efficiency of care. METHODS: These standards are divided into two indicators: curriculum and core competencies. Through questionnaires, course evaluations, and satisfaction surveys before and after the implementation of the training program, the effectiveness of the training program was analyzed. RESULTS: Theoretical assessment of the program was higher after its completion than before and the core competencies of nurse anesthetists significantly improved. Overall, the curriculum was highly satisfactory and important. DISCUSSION: Curriculum design was based on IFNA standards. Nurse anesthetists who are trained in a systematic way can work better with other professionals in providing anesthesia care. The objectives are to improve anesthesia care, reduce errors, improve physician satisfaction, and allow nurse anesthetists to realize their value. Overall, quality of anesthesia care improved after implementation of IFNA-standard training.

A Meta-Analysis of the Association Between the I148M Variant of Patatin-Like Phospholipase Domain Containing 3 Gene and the Presence of Chronic Hepatitis C.

CONTEXT: The objective of the current study was to evaluate the association between the I148M variant of patatin-like phospholipase domain-containing protein 3 (PNPLA3) and the presence of Chronic Hepatitis C (CHC) across different populations. EVIDENCE ACQUISITION: This study was a meta-analysis of all relevant researches published in the literature from year 2000 to 2015. The odds ratios (ORs) of PNPLA3 allele distributions in CHC patients were analyzed and compared with healthy controls. The meta-analysis Revman 5.2 software was applied for investigating heterogeneity among individual studies and for summarizing all the studies. The meta-analysis was carried out according to the Cochrane Reviewers' Handbook recommendations. A total of 120 clinical trials or reports were retrieved, yet only five trials met the study selection criteria. RESULTS: Five hospital-based case-control studies were included in the final analysis. The overall frequency of PNPLA3 gene polymorphisms was 20.4% (205/1005) in CHC and 10.23% (53/518) in controls. The summary odds ratio for the association of gene polymorphisms of PNPLA3 with the risk for CHC was determined as 2.20 (95% CI: 1.56 -3.11) and was statistically significant (P < 0.05). CONCLUSIONS: The current meta-analysis showed an association between frequency of GG genotype of PNPLA3 and the risk of development of CHC in various populations throughout the world.