A Pooled Analysis of the PCR for the Detection of Candida Auris.

BACKGROUND: Candida auris is an opportunistic pathogen with multiple drug resistance. Therefore, researchers conducted a meta-analysis to review PCR's ability to diagnose Candida auris to promote the development of accurate Candida auris diagnosis. METHODS: Researchers systematically retrieved relevant articles from PubMed, Cochrane Library, Embase, and Web of Science. Then, researchers extracted the key data required for the study from the selected articles. Meta-DiSc 1.4 was used for the statistical analysis. RevMan 5.3 was employed to assess the quality of the included literature. A funnel plot can appraise whether the included articles have publication bias. RESULTS: Five articles were included in the study. The results suggest that the pooled sensitivity and pooled specificity were 0.94 (95% CI: 0.92 - 0.95) and 0.99 (95% CI: 0.99 - 0.99), respectively. The positive and negative likelyhood ratios were 100.94 (95% CI: 47.51 - 214.47) and 0.07 (95% CI: 0.05 - 0.10), respectively. The diagnostic odds ratio was 1,814.70 (95% CI: 717.30 - 4,591.04), and the area under the SROC curve was 0.9935. Deek's funnel plot indicated that there was no publication bias. CONCLUSIONS: The results of the analysis indicate that PCR can become a valuable technique for the clinical diagnosis of Candida auris due to its excellent performance.

Identification of Key Pathways and Genes in SARS-CoV-2 Infecting Human Intestines by Bioinformatics Analysis.

COVID-19 is a serious infectious disease that has recently swept the world, and research on its causative virus, SARS-CoV-2, remains insufficient. Therefore, this study uses bioinformatics analysis techniques to explore the human digestive tract diseases that may be caused by SARS-CoV-2 infection. The gene expression profile data set, numbered GSE149312, is from the Gene Expression Omnibus (GEO) database and is divided into a 24-h group and a 60-h group. R software is used to analyze and screen out differentially expressed genes (DEGs) and then gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses are performed. In KEGG, the pathway of non-alcoholic fatty liver disease exists in both the 24-h group and 60-h group. STRING is used to establish a protein-protein interaction (PPI) network, and Cytoscape is then used to visualize the PPI and define the top 12 genes of the node as the hub genes. Through verification, nine statistically significant hub genes are identified: AKT1, TIMP1, NOTCH, CCNA2, RRM2, TTK, BUB1B, KIF20A, and PLK1. In conclusion, the results of this study can provide a certain direction and basis for follow-up studies of SARS-CoV-2 infection of the human digestive tract and provide new insights for the prevention and treatment of diseases caused by SARS-CoV-2.