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Based on previous studies, we found that Bacillus Calmette-Guerin(BCG) vaccination may have a role in preventing SARS-CoV-2 infection. Thus, we conducted this meta-analysis to investigate this protective effect. We searched in Embase, PubMed, Web of Science, Cochrane Library, BioRxiv, and MedRxiv databases for studies that evaluated the relationship between BCG vaccination and SARS-CoV-2 infection or COVID-19 disease. The quality of all included studies was assessed through the Risk of Bias in Non-randomized Studies - of Interventions and the Agency for Healthcare Research and Quality. Review Manager (Version 5.3) was used for conducting all data analyses. A total of 8 studies were ultimately included in our meta-analysis. Our primary analysis found significantly lower SARS-CoV-2 infection rate in the BCG vaccination group compared to the control group, with a odds ratio (OR) of 0.61, (95% confidence interval (CI) 0.39 to 0.95, P = 0.03; I2 = 31%, and P = 0.21 for heterogeneity). Our study indicated that BCG vaccination can protect against SARS-CoV-2 infection. However, there is insufficient evidence that BCG vaccination can reduce the severity of COVID-19.

Background Tuberculosis (TB) is a serious infectious disease caused by Mycobacterium tuberculosis (MTB). An estimated 1.7 billion people worldwide are infected with Mycobacterium tuberculosis (LTBI) during the incubation period without any obvious symptoms. Because of MTB’s high infection and mortality rates, there is an urgent need to develop a fast, portable, and sensitive diagnostic technology for its detection. Methods We included research from PubMed, Cochrane Library, Web of Science, and Embase and extracted the data. MetaDisc and STATA were used to build forest plots, Deek’s funnel plot, Fagan plot, and bivariate boxplot for analysis. Results Forty-six articles were analyzed, the results of which are as follows: sensitivity and specificity were 0.92 (0.91–0.93) and 0.95 (0.94–0.95) respectively. The NLR and PLR were 0.04 (95% CI 0.03–0.07) and 25.32 (95% CI 12.38–51.78) respectively. DOR was 639.60 (243.04–1683.18). The area under the SROC curve (AUC) was 0.99. Conclusions MPT64 exhibits good diagnostic efficiency for MTB. There is no obvious heterogeneity between the three commercial kits.

Objective To evaluate the accuracy of the reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in community or primary-care settings. Method We systematically searched the Web of Science, Embase, PubMed, and Cochrane Library databases. We conducted quality evaluation using ReviewManager software (version 5.0). We then used MetaDisc software (version 1.4) and Stata software (version 12.0) to build forest plots, along with a Deeks funnel plot and a bivariate boxplot for analysis. Result Overall, the sensitivity, specificity, and diagnostic odds ratio were 0.79, 0.97, and 328.18, respectively. The sensitivity for the subgroup with RNA extraction appeared to be higher, at 0.88 (0.86–0.90), compared to the subgroup without RNA extraction, at 0.50 (0.45–0.55), with no significant difference in specificity. Conclusion RT-LAMP assay exhibited high specificity regarding current SARS-CoV-2 infection. However, its overall sensitivity was relatively moderate. Extracting RNA was found to be beneficial in improving sensitivity.

Background In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people’s health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein–protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in. Results In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients. Conclusions In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.

BackgroundXpert Bladder Cancer is a detection method developed in recent years, designed with the functions of integrating sample automatically, nucleic acid amplification, and target sequence detection. It is a urine assay targeting five mRNAs (CRH, IGF2, UPK1B, ANXA10, and ABL1). The purpose of this article is to review the accuracy of Xpert Bladder Cancer in the follow-up diagnosis of bladder cancer and evaluate the role of Xpert Bladder Cancer in detecting the recurrence of non-muscle-invasive bladder cancer in the round.MethodsIn the database of Embase, PubMed, Web of Science, and Cochrane Library, the articles published up to October 13, 2020, were searched and screened based on the exclusion and inclusion criteria, and data were extracted from the included studies. The sensitivity, specificity, negative likelihood ratio, positive likelihood ratio summary of receiver operating characteristic curves, and diagnostic odds ratio were combined by the Meta-DiSc 1.4 software. The Stata 12.0 software was used to obtain the assessment of publication bias.ResultsA total of 8 articles involving eight fourfold tables were finally identified. The pooled sensitivity and specificity of Xpert Bladder Cancer in the diagnosis of bladder cancer were 0.71 and 0.81, respectively. The positive likelihood ratio and negative likelihood ratio were 3.74 and 0.34, respectively. The area under the curve was 0.8407. The diagnostic odds ratio was 11.99. Deeks’ funnel plot asymmetry test manifested no publication bias.ConclusionsIn summary, Xpert Bladder Cancer presents high accuracy and specificity in monitoring bladder cancer compared with cystoscopy. More researches are still required to further confirm this conclusion.

Background Tuberculosis poses a severe threat to human health. At present, compared with the traditional diagnostic methods for tuberculosis pleural effusion, such as Löwenstein–Jensen culture, pleural biopsy, and Ziehl–Neelsen smear microscopy, Xpert MTB/RIF was regarded as an emerging technology for its efficiency. The Xpert MTB/RIF accuracy for tuberculous pleural effusion diagnosis was evaluated in this systematic study. Materials and methods We searched the relevant literature published before January 2021 in PubMed, Cochrane, EMBASE, and Web of Science databases. Utilizing Review Manager 5.3 software, the quality of the included literature was evaluated based on the Quality Assessment of Diagnostic Accuracy Studies criteria. Sensitivity, specificity, and the summary receiver operating characteristic curves were plotted and analyzed with Metadisc 1.40 software. We used Stata 12.0 software to evaluate the publication bias of this study. Results Eighteen articles were identified in total. The sensitivity of Xpert MTB/RIF in the pleural effusion was 0.24, and specificity was 1.00, respectively. The area under the summary receiver operating characteristic curve was 0.9737, which indicated that the overall accuracy of the Xpert MTB/RIF was high. In addition, based on the Deeks funnel plot, no publication bias of the study was found. Conclusion Xpert MTB/RIF is a rapid method with high specificity but relatively low sensitivity for detecting Mycobacterium tuberculosis in pleural effusion. Its less sensitivity made it difficult to be used clinically, but the high specificity suggests that it can be used as a specific diagnostic method for tuberculous pleural effusion., SROC curve was plotted, and the following parameters were obtained: AUC of 0.9737 and Q of 0.9260 (SE = 0.0512). The SROC turn was near the top left corner, and the AUC was close to 1, which suggested that Xpert MTB/RIF had a comparatively overall high diagnostic accuracy for pleural effusion.

Cutaneous Leishmaniasis (CL) is the most common clinical form of leishmaniasis. Despite its low mortality, CL deserves further attention because its pathogenesis is currently no well-known or well-researched.We downloaded the gene expression datasets of GSE55664 and GSE63931 with respect to leishmaniasis from the Gene Expression Synthesis (GEO) database. Additionally, the differentially expressed genes (DEGs) in the infection and control groups were identified by packages of R software. The Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) pathway were utilized for the biological functional analysis. Subsequently, we identified the top ten hub genes from protein-protein interaction (PPI) networks based on STRING and Cytoscape software. The hub genes were validated in GraphPad Prism 8.0 using the GSE162760 dataset. Further, CIBERSORT was used to evaluate the immune cell infiltration proportions between the CL infection samples and the control samples based on the GSE43880 and GSE55664 datasets.The enrichment analysis revealed that DEGs were significantly involved in cell-mediated immune responses, such as leukocyte cell-cell adhesion and T-cell activation. STAT1, CCR7, CCR2, and CXCL10 were identified as hub genes with statistical significance. These hub genes showed close correlations with various immune cells, such as M1 cells and CD4-activated memory T-cells.In our research, we used bioinformatics analysis to identify some molecular biomarkers and significant pathways in CL infection. These hub genes may provide new options for future diagnosis and treatment.

Background GeneXpert enterovirus Assay is a PCR-based assay for Enterovirus meningitis diagnosis. However, there is currently no research about the performance of GeneXpert enterovirus assay in the diagnosis of enterovirus meningitis. Thus, a systematic review and meta-analysis is significant on the topic. Methods Embase, Cochrane Library, Web of Science, and PubMed were systematically reviewed with retrieval types. Some criteria were used to filter the studies. Only studies published in English, that made a comparison between GeneXpert enterovirus assay and RT-PCR, and could be formulated in a 2*2 table, were included. The quality of the included studies was evaluated by QUADAS-2. The effect of the GeneXpert enterovirus assay was assessed by the Sensitivity, Specificity, Positive Likelihood Ratio, Negative Likelihood Ratio, Diagnosis Odds Ratio, and summary receiver operating characteristic (SROC) curve. Publication bias and heterogeneity were evaluated by the Deeks' funnel test and Bivariate Box plot respectively. Results 7 studies were recruited in the analysis. The Pooled Sensitivity was 0.96 [95% CI (0.94–0.97)], Pooled Specificity was 0.99 [95% CI (0.98–0.99)], Positive Likelihood Ratio was 130.46 [95% CI (35.79–475.58)], Negative Likelihood Ratio was 0.04 [95% CI (0.02–0.10)], and Diagnostic Odds Ratio was 3648.23 (95% CI [963.99–13,806.72)]. In SROC Curve, Area Under Curve (AUC) was 0.9980, and Q*= 0.9849. In Deeks' funnel test, the P-value was 0.807 (P > 0.05), indicating no publication bias. The Bivariate Box plot indicated no evident heterogeneity. Conclusions The GeneXpert enterovirus assay demonstrated high diagnostic accuracy in diagnosing enterovirus meningitis.

Introduction Staphylococcus aureus is a gram-positive bacterium that causes serious infection. With the increasing resistance of bacteria to current antibiotics, it is necessary to learn more about the molecular mechanism and cellular pathways involved in the Staphylococcus aureus infection. Methods We downloaded the GSE33341 dataset from the GEO database and applied the weighted gene co-expression network analysis (WGCNA), from which we obtained some critical modules. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were applied to illustrate the biological functions of genes in these modules. We constructed the protein-protein interaction (PPI) network by Cytoscape and selected five candidate hub genes. Five potential hub genes were validated in GSE30119 by GraphPad Prism 8.0. The diagnostic values of these genes were calculated and present in the ROC curve based on the GSE13670 dataset. Their gene functions were analyzed by Gene Set Enrichment Analysis (GSEA). Results A co-expression network was built with 5000 genes divided into 11 modules. The genes in green and turquoise modules demonstrated a high correlation. According to the KEGG and GO analyses, genes in the green module were closely related to ubiquitination and autophagy. Subsequently, we picked out the top five hub genes in the green module. And UBB was determined as the hub gene in the GSE30119 dataset. The expression level of UBB, ASB, and MKRN1 could significantly differentiate between Staphylococcus aureus infection and healthy controls based on the ROC curve. The GSEA analysis indicated that lower expression levels of UBB were associated with the P53 signal pathway. Conclusions We identified some hub genes and significant signal enrichment pathways in Staphylococcus aureus infection via bioinformatics analysis, which may facilitate the development of potential clinical therapeutic strategies.

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., Author summary Dengue fever is a mosquito borne viral disease caused by a single stranded RNA virus with four serotypes. DENV infection can cause various diseases, such as breakbone fever, haemorrhagic fever, and shock syndrome. As one of the most viral diseases leading to incidence rate and mortality in animal arthropods, Dengue fever has become an increasingly serious global health threat. However, the pathogenesis of dengue fever has not been fully elucidated. In this study, we used bioinformatics analysis to identify potential biomarkers associated with dengue fever and elucidate their underlying mechanisms. Finally, we predicted that IFI44L and IFI6 might be potential biomarkers of DENV infection. This finding provides a promising target for the treatment of dengue fever to a certain extent. In addition, the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein–protein interaction (PPI) network were implemented to analyze the key differentially expressed genes after DENV infection, and the related mechanisms were illuminated by this study.

Background Nowadays, hand, foot, and mouth disease (HFMD) has a significant negative impact on children's health, especially in the Asia‐Pacific region. Loop‐mediated isothermal amplification assay (LAMP) is a highly efficient and convenient novel tool. However, its diagnostic accuracy for HFMD is still not clear. Therefore, we conducted a meta‐analysis in order to evaluate the potential of LAMP assay for the diagnosis of HFMD, in which the reference standard was polymerase chain reaction (PCR). Methods A protocol was predetermined (CRD42020212882) in PROSPERO. We retrieved seven databases including PubMed for relevant studies published before October 2020. Articles were included if they compared the diagnostic efficiency of LAMP with PCR for HFMD through detecting clinical samples which was more than 15. Statistical analysis was performed by STATA 15.1 software. Risk of bias and applicability were assessed using Quality Assessment of Diagnostic Accuracy Studies. No funding was used for the study. Results A total of 18 retrospective studies including 2495 samples from China were finally included. Reference standards of them included RT‐PCR and non‐RT‐PCR. The merged sensitivity and specificity with 95% confidence interval (95% CI) were 1.00 (0.97–1.00) and 0.97 (0.88–0.99), respectively. The pooled PLR, NLR, and DOR with 95% CI were 11.17 (5.91–21.11), 0.05 (0.03–0.09), and 538.12 (183.17–1580.83), respectively. The AUC of SROC was 1.00 (95% CI: 0.99–1.00). Conclusion In conclusion, our research revealed high sensitivity and specificity of LAMP in diagnosing HFMD. However, more high‐quality research is required to prove this conclusion., Our research revealed high sensitivity and specificity of LAMP in diagnosing HFMD. The AUC of SROC was 1.00 (0.99–1.00), indicating the high diagnostic accuracy of LAMP for HFMD.

Background Currently, Chlamydia trachomatis–specific host defense mechanisms in humans remain poorly defined. To study the characteristics of host cells infected early with Chlamydia trachomatis, we used bioinformatics methods to analyze the RNA transcription profiles of the conjunctiva, fallopian tubes, and endometrium in humans infected with Chlamydia trachomatis. Method The gene expression profiles of GSE20430, GSE20436, GSE26692, and GSE41075 were downloaded from the Gene Expression Synthesis (GEO) database. Then, we obtained the differentially expressed genes (DEGs) through the R 4.0.1 software. STRING was used to construct protein–protein interaction (PPI) networks; then, the Cytoscape 3.7.2 software was used to visualize the PPI and screen hub genes. GraphPad Prism 8.0 software was used to verify the expression of the hub gene. In addition, the gene–miRNA interaction was constructed on the NetworkAnalyst 3.0 platform using the miRTarBase v8.0 database. Results A total of 600 and 135 DEGs were screened out in the conjunctival infection group and the reproductive tract infection group, respectively. After constructing a PPI network and verifying the hub genes, CSF2, CD40, and CSF3 in the reproductive tract infection group proved to have considerable statistical significance. Conclusion In our research, the key genes in the biological process of reproductive tract infection with Chlamydia trachomatis were clarified through bioinformatics analysis. These hub genes may be further used in clinical treatment and clinical diagnosis.

BackgroundStaphylococcus aureus-induced bacteremia has an impact on human health due to its high mortality rate of 20–30%. To better study the invasion process of staphylococcus aureus, we conducted a study in human endothelial cells to try to find a link between the infection process and bacteremia at the molecular level.MethodsIn this study, the datasets GSE13736, GSE82036 were analyzed using R software to identify differentially expressed genes. Only the infection samples of four different strains had differential gene expression compared to the control samples. Then the GO analysis and KEGG analysis were conducted to construct a protein-protein interaction (PPI) network which shows the interaction and influence relationship between these differential genes. Finally, the central gene of the selected CytoHubba plug-in was verified using GraphPad Prism 8.ResultsThere were 421 differential genes in the Strain 6850, including 64 up-regulated and 357 down-regulated; There were 319 differential genes in the Strain 8325-4, including 14 up-regulated and 305 down-regulated. There were 90 differential genes in the Strain K70058396, including 12 up-regulated and 78 down-regulated. There were 876 differential genes in the Strain K1801/10, accompanied by 261 up-regulated and 615 down-regulated. An analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways associated with immune response and cytokines; Verification of the hub gene can provide a molecular basis for studying the relationship between invasive endothelial infection and bacteremia.ConclusionsWe found specific gene expression patterns in endothelial cells in response to infection with Strain K70058396, and these central genes and their expression products (RSAD2, DDX58, IFITT3, and IFIH1) play a key role in this process of infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of coronavirus disease 2019. Diagnostic methods based on the clustered regularly interspaced short palindromic repeats (CRISPR) have been developed to detect SARS-CoV-2 rapidly. Therefore, a systematic review and meta-analysis were performed to assess the diagnostic accuracy of CRISPR for detecting SARS-CoV-2 infection.Studies published before August 2021 were retrieved from four databases, using the keywords "SARS-CoV-2" and "CRISPR." Data were collected from these publications, and the sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic curve was plotted for analysis with MetaDiSc 1.4. The Stata 15.0 software was used to draw Deeks' funnel plots to evaluate publication bias.We performed a pooled analysis of 38 independent studies shown in 30 publications. The reference standard was reverse transcription-quantitative PCR. The results indicated that the sensitivity of CRISPR-based methods for diagnosis was 0.94 (95% CI 0.93-0.95), the specificity was 0.98 (95% CI 0.97-0.99), the PLR was 34.03 (95% CI 20.81-55.66), the NLR was 0.08 (95% CI 0.06-0.10), and the DOR was 575.74 (95% CI 382.36-866.95). The area under the curve was 0.9894.Studies indicate that a diagnostic method based on CRISPR has high sensitivity and specificity. Therefore, this would be a potential diagnostic tool to improve the accuracy of SARS-CoV-2 detection.

Background. The pathogenesis of invasive aspergillosis (IA) is still unknown, but its progression is rapid and mortality rate remains high. Bronchoalveolar lavage fluid (BALF) galactomannan (GM) analysis has been used to diagnose IA. This study is aimed at making an accurate estimate of the whole accuracy of BALF-GM in diagnosing IA. Methods. After a systematic review of the study, a bivariate meta-analysis was used to summarize the specificity (SPE), the sensitivity (SEN), the positive likelihood ratios (PLR), and the negative likelihood ratios (NLR) of BALF-GM in diagnosing IA. The overall test performance was summarized using a layered summary receiver operating characteristic (SROC) curve. Subgroup analysis was performed to explore the heterogeneity between studies. Results. A total of 65 studies that are in line with the inclusion criteria were included. The summary estimates of BALF-GM analysis are divided into four categories. The first is the proven+probable vs. possible+no IA, with an SPE, 0.87 (95% CI, 0.85-0.98); SEN, 0.81 (95% CI, 0.76-0.84); PLR, 9.78 (5.78-16.56); and NLR, 0.20 (0.14-0.29). The AUC was 0.94. The BALF-GM test for proven+probable vs. no IA showed SPE, 0.88 (95% CI, 0.87-0.90); SEN, 0.82 (95% CI, 0.78-0.85); PLR, 6.56 (4.93-8.75); and NLR, 0.24 (0.17-0.33). The AUC was 0.93. The BALF-GM test for proven+probable+possible vs. no IA showed SPE, 0.82 (95% CI, 0.79-0.95); SEN, 0.59 (95% CI, 0.55-0.63); PLR, 3.60 (2.07-6.25); and NLR, 0.31 (0.15-0.61). The AUC was 0.86. The analyses for others showed SPE, 0.85 (95% CI, 0.83-0.87); SEN, 0.89 (95% CI, 0.86-0.91); PLR, 6.91 (4.67-10.22); and NLR, 0.18 (0.13-0.26). The AUC was 0.94. Conclusions. The findings of this BALF-GM test resulted in some impact on the diagnosis of IA. The BALF-GM assay is considered a method for diagnosing IA with high SEN and SPE. However, the patients’ underlying diseases may affect the accuracy of diagnosis. When the cutoff is greater than 1, the sensitivity will be higher.