No abstract

Introduction. High mortality associated with carbapenemase-producing Gram-negative bacteria (CP-GNB) has evolved into a global health threat. Rapid and accurate detection as well as prompt treatment are of great significance in this case. Xpert Carba-R, a multiple qualitative analysis designed to detect five clinically relevant carbapenem-resistant gene families within one hour, is regarded as reliable, accurate, and easy-to-operate. This study is to present a systematic evaluation of the performance of Xpert Carba-R in detecting carbapenemase genes in GNB suspected for carbapenemase production. Methods. We searched and screened the literature on “Xpert Carba-R” in the database of PubMed, Web of Science, Embase, and Cochrane Library, employing two independent evaluators to collect data, respectively. Then, statistical analysis of the data obtained was performed by the Stata 12.0 software to measure the accuracy of Xpert Carba-R assay in detecting the carbapenemase genes in GNB. Results. We screened a total of 1767 Gram-negative bacillus isolates documented in 9 articles. The precision of the detection of OXA-48 carbapenemase genes was 100%; that of NDM = 100 %; that of VIM = 100 %. When it came to KPC, the precision rate was 100%; that of IMP = 99 %. The overall accuracy of the detection of carbapenemase genes was 100%. Conclusions. Xpert Carba-R assay demonstrates a 100% precision in identifying carbapenemase genes in GNB. It can be seen that Xpert Carba-R method is an effective tool for early clinical detection, which is suitable for the detection of carbapenase gene in GNB.

Background. The World Health Organization approved the use of Xpert MTB/RIF for the detection of Mycobacterium tuberculosis DNA, which has significantly improved the diagnosis of tuberculosis. In this study, our main objective was to evaluate the diagnostic efficacy of Xpert MTB/RIF for lymphoid tuberculosis to determine whether Xpert MTB/RIF could be used as a routine detection method. Materials and Methods. We searched four databases for the relevant literature published from May 2007 to December 2019. The quality of the literature was evaluated with reference to the evaluation criteria. Data that were extracted from the literature on Xpert MTB/RIF diagnosis of lymphatic tuberculosis were used to plot the summary receiver operating characteristic (SROC) curve, after which the software was used to combine and analyze the accuracy of these data. Results. A total of 27 studies were included. The sensitivity of Xpert MTB/RIF for detecting lymphatic tuberculosis was 0.79 (95% CI (0.77, 0.81)), the specificity was 0.88 (95% CI (0.87, 0.90)), and the positive likelihood ratio (PLR) was 7.21 (95% CI (4.93, 10.55)). In addition, the negative likelihood ratio (NLR) was 0.25 (95% CI (0.19, 0.32)) and the diagnostic odds ratio (DOR) was 40.23 (95% CI (24.53, 65.98)). At the same time, we used the extracted data to make the SROC curve, obtaining the following parameters: area under the curve AUC=0.9144, Q=0.8470 (SE=0.0163). Conclusion. Xpert MTB/RIF has high accuracy in detecting lymphatic tuberculosis, and it can be used to quickly and easily diagnose lymphatic tuberculosis at an early stage as a general method.

Background: The Corona Virus Disease 2019 (COVID-19) pandemic poses a serious public health threat to the survival and health of people all over the world. We analyzed related mRNA data and gene expression profiles of human cell lines infected with SARS-CoV-2 obtained from GEO (GSE148729), using bioinformatics tools. Differentially expressed genes (DEGs) of human cells infected with SARS-CoV-2 were identified.Method: The GSE148729 datasets were downloaded from the Gene Expression Omnibus (GEO) database. To explore the Biological significance of DEGs, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEGs was performed. Protein-protein interaction (PPI) networks of the DEGs were constructed by using the STRING database. The hub genes were selected using the Cytoscape Software, and a t-test was performed to validate the hub genes.Result: A total of 1241 DEGs were screened, including 1049 up-regulated genes and 192 down-regulated genes. Besides, 10 hub genes were obtained from the PPI network, among which the expression level of CXCL2, Etv7, and HIST1H2BG was found to be statistically significant.Conclusion: In conclusion, bioinformatics analysis reveals genes and cellular pathways that are significantly altered in SARS-CoV-2 infected cells. This is conducive to further guide the clinical study of SARS-CoV-2 and provides new perspectives for vaccine development.