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Background:Drug-induced liver injury (DILI) is a potentially severe adverse drug reaction especially in susceptible patients. But there are no sensitive or specific parameters to detecting DILI. The specific expression of miR-122 in the liver has been a hotspot in the evaluation of hepatic toxicity due to its high stability and sensitivity.Methods:We performed a systematic literature review through July 31, 2017 to identify studies which evolved DILI patients testing miR-122 without limiting a certain drug. According to the PRISMA statement, a meta-analysis: the diagnostic role of miR-122 in DILI was made. QUADAS-2 quality evaluation table was used to evaluate the quality of the documentary evidence, PRISMA flowchart and quality evaluation table were drawn with RevMan, use Stata to calculate the sensitivity and specificity of miR-122 in diagnosing DILI, ROC curve and Deeks funnel plot were also drawn by STATA.Results:Eleven studies involved 194 DILI patients and 251 controls, all were tested miR-122 (fold change). Sensitivity of miR-122 in diagnosing DILI was [0.85 (95% CI, 0.75–0.91), I2 = 53.46%] and specificity was [0.93 (95% CI, 0.86–0.97), I2 = 65.10%], the area under ROC curve was 0.95 (95% CI, 0.93–0.97). While in acetaminophen (APAP)-induced liver injury, the sensitivity was [0.82 (95%CI, 0.67–0.91), I2 = 65.77%] specificity was [0.96 (95%CI, 0.88–0.99), I2 = 31.46%], AUROC was 0.97 (95% CI, 0.95–0.98).Conclusions:In this systematic review and meta-analysis, we found miR-122 have a high specificity in DILI, and a modest positive diagnostic effects. On the basis of the limited evidence, further research is needed to evaluate the long-term observation and more clinical data to testify miR-122 in diagnosing DILI.

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China.Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels.Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC.Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

Aim: To study the expression pattern of circular RNAs in diabetic peripheral neuropathy. Materials & methods: Transmission electron microscopy was used to observe the ultrastructure of sciatic nerves and dorsal root ganglion (DRGs). circRNAs in DRGs were identified with high-throughput RNA sequencing. Whole-genome mRNAs were detected by a chip scan. Results: The ultrastructure of sciatic nerves and DRGs in diabetes mellitus mice changed significantly. A total of 11,004 circRNAs and 15 differentially expressed circRNAs, as well as 35,368 mRNAs and 133 differentially expressed mRNAs were identified in DRGs between wild type and diabetes mellitus mice. Eleven circRNAs and 14 mRNAs have a significant correlation using strict coexpression analysis. The expression of circRNA.4614 was validated to be upregulated significantly. Conclusion: Our study suggested that circRNAs might be involved in the regulation of mRNA expressions in diabetic peripheral neuropathy.

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