Identification of the Hub Genes and the Signaling Pathways in Human iPSC-Cardiomyocytes Infected by SARS-CoV-2.

Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) is an enveloped single-stranded RNA virus that can lead to respiratory symptoms and damage many organs such as heart, kidney, intestine, brain and liver. It has not been clearly documented whether myocardial injury is caused by direct infection of cardiomyocytes, lung injury, or other unknown mechanisms. The gene expression profile of GSE150392 was obtained from the Gene Expression Omnibus (GEO) database. The processing of high-throughput sequencing data and the screening of differentially expressed genes (DEGs) were implemented by R software. The R software was employed to analyze the Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The protein-protein interaction (PPI) network of the DEGs was constructed by the STRING website. The Cytoscape software was applied for the visualization of PPI network and the identification of hub genes. The statistical analysis was performed by the GraphPad Prism software to verify the hub genes. A total of 516 up-regulated genes and 191 down-regulated genes were screened out. The top 1 enrichment items of GO in biological process (BP), Cellular Component (CC), and Molecular Function (MF) were type I interferon signaling pathway, sarcomere, and receptor ligand activity, respectively. The top 10 enrichment pathways, including TNF signaling pathway, were identified by KEGG enrichment analysis. A PPI network was established, consisting of 613 nodes and 3,993 edges. The 12 hub genes were confirmed as statistically significant, which was verified by GSE151879 dataset. In conclusion, the hub genes of human iPSC-cardiomyocytes infected with SARS-CoV-2 were identified through bioinformatics analysis, which may be used as biomarkers for further research.

Evaluation of lateral flow immunochromatographic assay for diagnostic accuracy of cryptococcosis.

BACKGROUND: Cryptococcus is a conditional pathogenic fungus causing cryptococcosis, which is one of the most serious fungal diseases faced by humans. Lateral flow immunochromatographic assay (LFA) is successfully applied to the rapid detection of cryptococcal antigens. METHODS: Studies were retrieved systematically from the Embase, PubMed, Web of Science, and Cochrane Library before July 2019. The quality of the studies was assessed by Review Manager 5.0 based on the Quality Assessment of Diagnostic Accuracy Study guidelines. The extracted data from the included studies were analyzed by Meta-DiSc 1.4. Stata 12.0 software was used to detect the publication bias. RESULTS: A total of 15 articles with 31 fourfold tables were adopted by inclusion and exclusion criteria. The merged sensitivity and specificity in serum were 0.98 and 0.98, respectively, and those in the cerebrospinal fluid were 0.99 and 0.99, respectively. CONCLUSIONS: Compared to the urine and other samples, LFA in serum and cerebrospinal fluid is favorable evidence for the diagnosis of cryptococcosis with high specificity and sensitivity.

Diagnostic Accuracy of Xpert Xpress Flu/RSV for the Detection of Influenza and Respiratory Syncytial Viruses.

Xpert Xpress Flu/RSV is a fast and automated real-time nucleic acid amplification tool for detecting influenza virus and respiratory syncytial virus (RSV). The aim of this study was to verify the accuracy of Xpert Xpress Flu/RSV for detecting influenza virus and RSV. PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched up to October 2020. The quality of the original research was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 guidelines. Meta-DiSc 1.4 software was used to analyze the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristic curve. Deek's funnel plot asymmetry test was used to evaluate the publication bias using the Stata 12.0 software. Ten studies with 25 fourfold tables were included in the analysis. The sensitivity of Xpert Xpress Flu/RSV for detecting influenza A, influenza B, and RSV were 0.97, 0.98, and 0.96, respectively, and the specificities were 0.97, 1.00, and 1.00, respectively. Compared with other common clinical real-time reverse transcription-polymerase chain reaction (RT-PCR), Xpert Xpress Flu/RSV is a valuable tool for diagnosing influenza virus and RSV with high sensitivity and specificity.

Identification of potential biomarkers in dengue via integrated bioinformatic analysis.

Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein-protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent.