Exosomal ncRNAs profiling of mycobacterial infection identified miRNA-185-5p as a novel biomarker for tuberculosis.

BACKGROUND: There are ever increasing researches implying that noncoded RNAs (ncRNAs) specifically circular RNAs (circRNAs) and microRNAs (miRNAs) in exosomes play vital roles in respiratory disease. However, the detailed mechanisms persist to be unclear in mycobacterial infection. METHODS: In order to detect circRNAs and miRNAs expression pattern and potential biological function in tuberculosis, we performed immense parallel sequencing for exosomal ncRNAs from THP-1-derived macrophages infected by Mycobacterium tuberculosis H37Ra, Mycobacterium bovis BCG and control Streptococcus pneumonia, respectively and uninfected normal cells. Besides, THP-1-derived macrophages were used to verify the validation of differential miRNAs, and monocytes from PBMCs and clinical plasma samples were used to further validate differentially expressed miR-185-5p. RESULTS: Many exosomal circRNAs and miRNAs associated with tuberculosis infection were recognized. Extensive enrichment analyses were performed to illustrate the major effects of altered ncRNAs expression. Moreover, the miRNA-mRNA and circRNA-miRNA networks were created and expected to reveal their interrelationship. Further, significant differentially expressed miRNAs based on Exo-BCG, Exo-Ra and Exo-Control, were evaluated, and the potential target mRNAs and function were analyzed. Eventually, miR-185-5p was collected as a promising potential biomarker for tuberculosis. CONCLUSION: Our findings provide a new vision for exploring biological functions of ncRNAs in mycobacterial infection and screening novel potential biomarkers. To sum up, exosomal ncRNAs might represent useful functional biomarkers in tuberculosis pathogenesis and diagnosis.

A novel autophagy-related lncRNA survival model for lung adenocarcinoma.

Long non-coding RNA (lncRNA) is an important regulatory factor in the development of lung adenocarcinoma, which is related to the control of autophagy. LncRNA can also be used as a biomarker of prognosis in patients with lung adenocarcinoma. Therefore, it is important to determine the prognostic value of autophagy-related lncRNA in lung adenocarcinoma. In this study, autophagy-related mRNAs-lncRNAs were screened from lung adenocarcinoma and a co-expression network of autophagy-related mRNAs-lncRNAs was constructed by using The Cancer Genome Atlas (TCGA). The univariate and multivariate Cox proportional hazard analyses were used to evaluate the prognostic value of the autophagy-related lncRNAs and finally obtained a survival model composed of 11 autophagy-related lncRNAs. Through Kaplan-Meier analysis, univariate and multivariate Cox regression analysis and time-dependent receiver operating characteristic (ROC) curve analysis, it was further verified that the survival model was a new independent prognostic factor for patients with lung adenocarcinoma. In addition, based on the survival model, gene set enrichment analysis (GSEA) was used to illustrate the function of genes in low-risk and high-risk groups. These 11 lncRNAs were GAS6-AS1, AC106047.1, AC010980.2, AL034397.3, NKILA, AL606489.1, HLA-DQB1-AS1, LINC01116, LINC01806, FAM83A-AS1 and AC090559.1. The hazard ratio (HR) of the risk score was 1.256 (1.196-1.320) (P < .001) in univariate Cox regression analysis and 1.215 (1.149-1.286) (P < .001) in multivariate Cox regression analysis. And the AUC value of the risk score was 0.809. The 11 autophagy-related lncRNA survival models had important predictive value for the prognosis of lung adenocarcinoma and may become clinical autophagy-related therapeutic targets.

IRF1 as a potential biomarker in Mycobacterium tuberculosis infection.

Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456, GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell-cell adhesion and regulation of T-cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine-cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein-protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up-regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834. Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up-regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.

Integrated single-cell transcriptome and T cell receptor profiling reveals defects of T cell exhaustion in pulmonary tuberculosis.

Tuberculosis-affected lungs with chronic inflammation harbor abundant immunosuppressive immune cells but the nature of such inflammation is unclear. Dysfunction in T cell exhaustion, while implicated in chronic inflammatory diseases, remains unexplored in tuberculosis. Given that immunotherapy targeting exhaustion checkpoints exacerbates tuberculosis, we speculate that T cell exhaustion is dysfunctional in tuberculosis. Using integrated single-cell RNA sequencing and T cell receptor profiling we reported defects in exhaustion responses within inflamed tuberculosis-affected lungs. Tuberculosis lungs demonstrated significantly reduced levels of exhausted CD8+ T cells and exhibited diminished expression of exhaustion-related transcripts among clonally expanded CD4+ and CD8+ T cells. Additionally, clonal expansion of CD4+ and CD8+ T cells bearing T cell receptors specific for CMV was observed. Expanded CD8+ T cells expressed the cytolytic marker GZMK. Hence, inflamed tuberculosis-affected lungs displayed dysfunction in T cell exhaustion. Our findings likely hold implications for understanding the reactivation of tuberculosis observed in patients undergoing immunotherapy targeting the exhaustion checkpoint.

A genome-wide analysis of multidrug-resistant and extensively drug-resistant strains of Mycobacterium tuberculosis Beijing genotype.

The Beijing genotype of Mycobacterium tuberculosis (MTB) is one of the most successful MTB lineages that has disseminated in the world. In China, the rate of multidrug-resistant (MDR) tuberculosis is significantly higher than the global average rate, and the Beijing genotype strains take the largest share of MDR strains. To study the genetic basis of the epidemiological findings that Beijing genotype has often been associated with tuberculosis outbreaks and drug resistance, we determined the genome sequences of four clinical isolates: two extensively drug resistant (XDR1219, XDR1221) and two multidrug resistant (WX1, WX3), using whole-genome sequencing. A large number of individual and shared SNPs of the four Beijing strains were identified. Our isolates harbored almost all classic drug resistance-associated mutations. The mutations responsible for drug resistance in the two XDR strains were consistent with the clinical quantitative drug resistance levels. COG analysis revealed that Beijing strains have significantly higher abundances of the mutations responsible for cell wall/membrane/envelope biogenesis (COG M), secondary metabolites biosynthesis, transport and catabolism (COG Q), lipid transport and metabolism (COG I) and defense mechanisms (COG V). The shared mutated genes of the four studied Beijing strains were significantly overrepresented in three DNA repair pathways. Our analyses promote the understanding of the genome polymorphism of the Beijing family strains and provide the molecular genetic basis for their wide dissemination capacity and drug resistance.

Collective and Individual Assessment of the Risk of Death from COVID-19 for the Elderly, 2020-2022.

Introduction: Coronavirus disease 2019 (COVID-19) has had profound disruptions worldwide. For a population or individual, it is critical to assess the risk of death for making preventative decisions. Methods: In this study, clinical data from approximately 100 million cases were statistically analyzed. A software and an online assessment tool were developed in Python to evaluate the risk of mortality. Results: Our analysis revealed that 76.51% of COVID-19-related fatalities occurred among individuals aged over 65 years, with frailty-associated deaths accounting for more than 80% of these cases. Furthermore, over 80% of the reported deaths involved unvaccinated individuals. A notable overlap was observed between aging and frailty-associated deaths, both of which were connected to underlying health conditions. For those with at least two comorbidities, the proportion of frailty and the proportion of COVID-19-related death were both close to 75 percent. Subsequently, we established a formula to calculate the number of deaths, which was validated using data from twenty countries and regions. Using this formula, we developed and verified an intelligent software designed to predict the death risk for a given population. To facilitate rapid risk screening on an individual level, we also introduced a six-question online assessment tool. Conclusions: This study examined the impact of underlying diseases, frailty, age, and vaccination history on COVID-19-related mortality, resulting in a sophisticated software and a user-friendly online scale to assess mortality risk. These tools offer valuable assistance in informed decision-making.

Identification of unique transcriptomic signatures and key genes through RNA sequencing and integrated WGCNA and PPI network analysis in HIV infected lung cancer.

With the widespread use of highly active antiretroviral therapy (HARRT), the survival time of AIDS patients has been greatly extended. However, the incidence of lung cancer in HIV-infected patients is increasing and has become a major problem threatening the survival of AIDS patients. The aim of this study is to use Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene analysis to find possible key genes involved in HIV-infected lung cancer. In this study, using lung tissue samples from five pairs of HIV-infected lung cancer patients, second-generation sequencing was performed and transcriptomic data were obtained. A total of 132 HIV-infected lung cancer-related genes were screened out by WGCNA and differential gene expression analysis methods. Based on gene annotation analysis, these genes were mainly enriched in mitosis-related functions and pathways. In addition, in protein-protein interaction (PPI) analysis, a total of 39 hub genes were identified. Among them, five genes (ASPM, CDCA8, CENPF, CEP55, and PLK1) were present in both three hub gene lists (intersection gene, DEGs, and WCGNA module) suggesting that these five genes may become key genes involved in HIV-infected lung cancer.

Evaluation of the IP-10 mRNA release assay for diagnosis of TB in HIV-infected individuals.

HIV-infected individuals are susceptible to Mycobacterium tuberculosis (M.tb) infection and are at high risk of developing active tuberculosis (TB). Interferon-gamma release assays (IGRAs) are auxiliary tools in the diagnosis of TB. However, the performance of IGRAs in HIV-infected individuals is suboptimal, which limits clinical application. Interferon-inducible protein 10 (IP-10) is an alternative biomarker for identifying M.tb infection due to its high expression after stimulation with M.tb antigens. However, whether IP-10 mRNA constitutes a target for the diagnosis of TB in HIV-infected individuals is unknown. Thus, we prospectively enrolled HIV-infected patients with suspected active TB from five hospitals between May 2021 and May 2022, and performed the IGRA test (QFT-GIT) alongside the IP-10 mRNA release assay on peripheral blood. Of the 216 participants, 152 TB patients and 48 non-TB patients with a conclusive diagnosis were included in the final analysis. The number of indeterminate results of IP-10 mRNA release assay (13/200, 6.5%) was significantly lower than that of the QFT-GIT test (42/200, 21.0%) (P = 0.000026). IP-10 mRNA release assay had a sensitivity of 65.3% (95%CI 55.9% - 73.8%) and a specificity of 74.2% (95%CI 55.4% - 88.1%), respectively; while the QFT-GIT test had a sensitivity of 43.2% (95%CI 34.1% - 52.7%) and a specificity of 87.1% (95%CI 70.2% - 96.4%), respectively. The sensitivity of the IP-10 mRNA release assay was significantly higher than that of QFT-GIT test (P = 0.00062), while no significant difference was detected between the specificities of these two tests (P = 0.198). The IP-10 mRNA release assay showed a lower dependence on CD4+ T cells than that of QFT-GIT test. This was evidenced by the fact that the QFT-GIT test had a higher number of indeterminate results and a lower sensitivity when the CD4+ T cells counts were decreased (P < 0.05), while no significant difference in the number of indeterminate results and sensitivity were observed for the IP-10 mRNA release assay among HIV-infected individuals with varied CD4+T cells counts (P > 0.05). Therefore, our study suggested that M.tb specific IP-10 mRNA is a better biomarker for diagnosis of TB in HIV-infected individuals.

Single-cell RNA-sequencing reveals heterogeneity and intercellular crosstalk in human tuberculosis lung.

Lung inflammation indicated by 18F-labeled fluorodeoxyglucose (FDG) in patients with tuberculosis is associated with disease severity and relapse risk upon treatment completion. We revealed the heterogeneity and intercellular crosstalk in lung tissues with 18F-FDG avidity and adjacent uninvolved tissues from 6 tuberculosis patients by single-cell RNA-sequencing. Tuberculous lungs had an influx of regulatory T cells (Treg), exhausted CD8 T cells, immunosuppressive myeloid cells, conventional DC, plasmacytoid DC, and neutrophils. Immune cells in inflamed lungs showed general up-regulation of ATP synthesis and interferon-mediated signaling. Immunosuppressive myeloid and Treg cells strongly displayed transcriptions of genes related to tuberculosis disease progression. Intensive crosstalk between IL4I1-expressing myeloid cells and Treg cells involving chemokines, costimulatory molecules, and immune checkpoints, some of which are specific in 18F-FDG-avid lungs, were found. Our analysis provides insights into the transcriptomic heterogeneity and cellular crosstalk in pulmonary tuberculosis and guides unveiling cellular and molecular targets for tuberculosis therapy.

Asymptomatic Transmissibility Calls for Implementing a Zero-COVID Strategy to End the Current Global Crisis.

The coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented global challenges. A zero-COVID strategy is needed to end the crisis, but there is a lack of biological evidence. In the present study, we collected available data on SARS, MERS, and COVID-19 to perform a comprehensive comparative analysis and visualization. The study results revealed that the fatality rate of COVID-19 is low, whereas its death toll is high compared to SARS and MERS. Moreover, COVID-19 had a higher asymptomatic rate. In particular, COVID-19 exhibited unique asymptomatic transmissibility. Further, we developed a foolproof operating software in Python language to simulate COVID-19 spread in Wuhan, showing that the cumulative cases of existing asymptomatic spread would be over 100 times higher than that of only symptomatic spread. This confirmed the essential role of asymptomatic transmissibility in the uncontrolled global spread of COVID-19, which enables the necessity of implementing the zero-COVID policy. In conclusion, we revealed the triggering role of the asymptomatic transmissibility of COVID-19 in this unprecedented global crisis, which offers support to the zero-COVID strategy against the recurring COVID-19 spread.

Identification of Key CircRNAs Related to Pulmonary Tuberculosis Based on Bioinformatics Analysis.

Pulmonary tuberculosis (TB) is a chronic infectious disease that is caused by respiratory infections, principally Mycobacterium tuberculosis. Increasingly, studies have shown that circular (circ)RNAs play regulatory roles in different diseases through different mechanisms. However, their roles and potential regulatory mechanisms in pulmonary TB remain unclear. In this study, we analyzed circRNA sequencing data from adjacent normal and diseased tissues from pulmonary TB patients and analyzed the differentially expressed genes. We then constructed machine learning models and used single-factor analysis to identify hub circRNAs. We downloaded the pulmonary TB micro (mi)RNA (GSE29190) and mRNA (GSE83456) gene expression datasets from the Gene Expression Omnibus database and performed differential expression analysis to determine the differentially expressed miRNAs and mRNAs. We also constructed a circRNA-miRNA-mRNA interaction network using Cytoscape. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used to predict the biological functions of the identified RNAs and determine hub genes. Then, the STRING database and cytoHubba were used to construct protein-protein interaction networks. The results showed 125 differentially expressed circRNAs in the adjacent normal and diseased tissues of pulmonary TB patients. Among them, we identified three hub genes associated with the development of pulmonary TB: hsa_circ_0007919 (upregulated), hsa_circ_0002419 (downregulated), and hsa_circ_0005521 (downregulated). Through further screening, we determined 16 mRNAs of potential downstream genes for hsa-miR-409-5p and hsa_circ_0005521 and established an interaction network. This network may have important roles in the occurrence and development of pulmonary TB. We constructed a model with 100% prediction accuracy by machine learning and single-factor analysis. We constructed a protein-protein interaction network among the top 50 hub mRNAs, with FBXW7 scoring the highest and SOCS3 the second highest. These results may provide a new reference for the identification of candidate markers for the early diagnosis and treatment of pulmonary TB.

Comprehensive Genetic Analysis of Tuberculosis and Identification of Candidate Biomarkers.

Purpose: The purpose of this study is to use the data in the GEO database to analyze, screen biomarkers that can diagnose tuberculosis, and verification of candidate biomarkers. Materials and methods: GSE158767 dataset were used to process WGCNA analysis, differential gene analysis, Gene ontology and KEGG analysis, protein-protein network analysis and hub genes analysis. Based on our previous study, the intersect between WGCNA and differential gene analysis could be used as candidate biomarkers. Then, the enzyme-linked immunosorbent assay was used to validate candidate biomarkers, and receiver operating characteristic was used to assess diagnose ability of candidate biomarkers. Results: A total of 412 differential genes were screened. And we obtained 105 overlapping genes between DEGs and WGCNA. GO and KEGG analysis showed that most of the differential genes were significantly enriched in innate immunity. A total of 15 hub genes were screened, and four of them were verified by Enzyme-linked immunosorbent assay. CCL5 performed well in distinguishing the healthy group from the TB group (AUC = 0.723). And CCL19 performed well in distinguishing the TB group from the ORD groups (AUC = 0.811). Conclusion: CCL19, C1Qb, CCL5 and HLA-DMB may play important role in tuberculosis, which indicated four genes may become effective biomarkers and could be conveniently used to facilitate the individual tuberculosis diagnosis in Chinese people.

Rapid GPR183-mediated recruitment of eosinophils to the lung after Mycobacterium tuberculosis infection.

Influx of eosinophils into the lungs is typically associated with type II responses during allergy and fungal and parasitic infections. However, we previously reported that eosinophils accumulate in lung lesions during type I inflammatory responses to Mycobacterium tuberculosis (Mtb) in humans, macaques, and mice, in which they support host resistance. Here we show eosinophils migrate into the lungs of macaques and mice as early as one week after Mtb exposure. In mice this influx is CCR3 independent and instead requires cell-intrinsic expression of the oxysterol receptor GPR183, which is highly expressed on human and macaque eosinophils. Murine eosinophils interact directly with bacilli-laden alveolar macrophages, which upregulate the oxysterol-synthesizing enzyme Ch25h, and eosinophil recruitment is impaired in Ch25h-deficient mice. Our findings show that eosinophils are among the earliest cells from circulation to sense and respond to Mtb infection of alveolar macrophages and reveal a role for GPR183 in the migration of eosinophils into lung tissue.

Complete genome sequence of a novel clinical isolate, the nontuberculous Mycobacterium strain JDM601.

Mycobacteriosis is on the increase. Nontuberculous mycobacteria (NTM) are resistant to most antituberculosis drugs naturally. We determined the complete genome sequence of a novel NTM strain, JDM601, of the Mycobacterium terrae complex, which was isolated from a patient with tuberculosis-like disease and with various antibiotic resistances.

Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis.

Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide-sugar biosynthetic process (biological process), ficolin-1-rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11).

Long non-coding RNAs ENST00000429730.1 and MSTRG.93125.4 are associated with metabolic activity in tuberculosis lesions of sputum-negative tuberculosis patients.

Accurate diagnosis of complete inactivation of tuberculosis lesions is still a challenge with respect to sputum-negative tuberculosis. RNA-sequencing was conducted to uncover potential lncRNA indicators of metabolic activity in tuberculosis lesions. Lung tissues with high metabolic activity and low metabolic activity demonstrated by fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography were collected from five sputum-negative tuberculosis patients for RNA-sequencing. Differentially-expressed mRNAs and lncRNAs were identified. Their correlations were evaluated to construct lncRNA-mRNA co-expression network, in which lncRNAs and mRNAs with high degrees were confirmed by quantitative real-time PCR using samples collected from 11 patients. Prediction efficiencies of lncRNA indicators were assessed by receiver operating characteristic curve analysis. Bioinformatics analysis was performed for potential lncRNAs. 386 mRNAs and 44 lncRNAs were identified to be differentially expressed. Differentially-expressed mRNAs in lncRNA-mRNA co-expression network were significantly associated with fibrillar collagen, platelet-derived growth factor binding, and leukocyte migration involved in inflammatory response. Seven mRNAs (C1QB, CD68, CCL5, CCL19, MMP7, HLA-DMB, and CYBB) and two lncRNAs (ENST00000429730.1 and MSTRG.93125.4) were validated to be significantly up-regulated. The area under the curve of ENST00000429730.1 and MSTRG.93125.4 was 0.750 and 0.813, respectively. Two lncRNAs ENST00000429730.1 and MSTRG.93125.4 might be considered as potential indicators of metabolic activity in tuberculosis lesions for sputum-negative tuberculosis.

[Expression, purification, and characterization Mycobacterium tuberculosis Rv1168c].

OBJECTIVE: To express and purify the Pro-Pro-Glu (PPE) family protein Rv1168c of Mycobacterium tuberculosis in E. coli. and to study the structure of Rv1168c. METHODS: The Rv1168c gene was amplified by PCR from Mycobacterium tuberculosis H37Rv strain genomic DNA and cloned into a prokaryotic expression vector pET32a The resulting recombinant expression plasmid pET32a-Rv1168c was then transformed into the E. coli strain DH5alpha and a high-level expression E. coli BL21(DE3) was established after induction with Isopropyl-beta-D-thiogalactopyranoside (IPTG). SDS-PAGE and mass spectrum analysis determined the relative molecular weight of this recombinant Rv1168c protein. It's secondary and 3D structures were determined by circular dichroism and homologous modeling. RESULTS: The Mycobacterium tuberculosis Rv1168c gene (971bp) and high purified recombinant Rv1168c protein was obtained. The relative molecular weight of recombinant Rv1168c protein was determined to be 51.5 kDa (vector included). Secondary structure of Rv1168c had about 34.4% alpha helix, 33.7%, beta tune, 31.9% random coil at 25 delta C. Homologous modeling shows Rv1168c as (beta/alpha)5 protein. CONCLUSION: This study obtained purified recombinant Rv1168c protein and laid the foundation for exploration of the relationship between the structure and function of Rv1168c in the tuberculosis.

A Rapid and Accurate Detection Approach for Multidrug-Resistant Tuberculosis Based on PCR-ELISA Microplate Hybridization Assay.

Rapid and accurate diagnosis of multidrug-resistant tuberculosis (MDR-TB) is important for timely and appropriate therapy. In this study, a rapid and easy-to-perform molecular test that integrated polymerase chain reaction (PCR) amplification and a specific 96-well microplate hybridization assay, called PCR-ELISA (enzyme-linked immunosorbent assay), were developed for detection of mutations in rpoB, katG, and inhA genes responsible for rifampin (RIF) and isoniazid (INH) resistance and prediction of drug susceptibility in Mycobacterium tuberculosis clinical isolates. We evaluated the utility of this method by using 32 multidrug-resistent (MDR) isolates and 22 susceptible isolates; subsequently, we compared the results with data obtained by conventional drug susceptibility testing and DNA sequencing. The sensitivity and specificity of the PCR-ELISA test were 93.7% and 100% for detecting RIF resistance, and 87.5% and 100% for detecting INH resistance, respectively. These results were comparable to those yielded by commercially available molecular tests such as the GenoType MTBDRplus assay. Based on the aforementioned results, we conclude that the PCR-ELISA microplate hybridization assay is a rapid, inexpensive, convenient, and reliable test that will be useful for rapid diagnosis of MDR-TB, for improved clinical care.

Lung cancer surgery in HIV-infected patients: An analysis of postoperative complications and long-term survival.

BACKGROUND: The purpose of this study was to investigate the risk factors of postoperative complications and reliable prognostic factors of long-term survival in HIV-infected patients with non-small cell lung cancer (NSCLC). METHODS: HIV-infected patients with NSCLC who underwent surgical treatment were retrospectively studied; a single-institutional analysis was conducted from November 2011 to August 2018. Pre- and postoperative clinical data, including age, gender, smoking history, highly active antiretroviral therapy (HAART), CD4+ T cell count, HIV viral load, cancer histology, clinical and pathological stage (p-stage), surgical result, Glasgow Prognostic Score (GPS), the Charlson comorbidity index (CCI), survival time and postoperative complications were collected. RESULTS: A total of 33 HIV-infected patients with NSCLC were enrolled of which 18 (54.7%) had preoperative comorbidities and postoperative complications were observed in 22 (66.7%) patients. Thirty-day mortality was not observed in these patients. Median survival time after surgery was 65 months: the MST of p-stage I patients was 65 months; p-stage II MST was unestimable; p-stage III MST was 21 months. Univariate analyses showed that postoperative complications were associated with HIV viral load (P = 0.002), CCI (P = 0.027), HAART (P = 0.028) and CD4+ T cell count (P = 0.045). However, multiple logistic regression analysis showed no correlation between HAART and postoperative complications. The p-stage was an independent prognostic factor for survival time. CONCLUSIONS: In our single-arm retrospective analysis, the risk factors for postoperative complications in HIV-infected patients with NSCLC were HIV viral load, CCI and CD4+ T cell counts. The p-stage was a predictive factor for long-term survival.

Multi-Fluorescence Real-Time PCR Assay for Detection of RIF and INH Resistance of M. tuberculosis.

BACKGROUND: Failure to early detect multidrug-resistant tuberculosis (MDR-TB) results in treatment failure and poor clinical outcomes, and highlights the need to rapidly detect resistance to rifampicin (RIF) and isoniazid (INH). METHODS: In Multi-Fluorescence quantitative Real-Time PCR (MF-qRT-PCR) assay, 10 probes labeled with four kinds of fluorophores were designed to detect the mutations in regions of rpoB, katG, mabA-inhA, oxyR-ahpC, and rrs. The efficiency of MF-qRT-PCR assay was tested using 261 bacterial isolates and 33 clinical sputum specimens. Among these samples, 227 Mycobacterium tuberculosis isolates were analyzed using drug susceptibility testing (DST), DNA sequencing and MF-qRT-PCR assay. RESULTS: Compared with DST, MF-qRT-PCR sensitivity and specificity for RIF-resistance were 94.6 and 100%, respectively. And the detection sensitivity and specificity for INH-resistance were 85.9 and 95.3%, respectively. Compared with DNA sequencing, the sensitivity and specificity of our assay were 97.2 and 100% for RIF-resistance and 97.9 and 96.4% for INH-resistance. Compared with Phenotypic strain identification, MF-qRT-PCR can distinguish 227 M. tuberculosis complexes (MTC) from 34 Non-tuberculous mycobacteria (NTM) isolates with 100% accuracy rate. CONCLUSIONS: MF-qRT-PCR assay was an efficient, accurate, reliable, and easy-operated method for detection of RIF and INH-resistance, and distinction of MTC and NTM of clinical isolates.