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Tuberculosis (TB) is caused by infection with the bacterial pathogen Mycobacterium tuberculosis (M.tb) in the respiratory tract. There was an estimated 10.6 million people newly diagnosed with TB, and there were approximately 1.3 million deaths caused by TB in 2022. Although the global prevalence of TB has remained high for decades and is an annual leading cause of death attributed to infectious diseases, only one vaccine, Bacillus Calmette-Guérin (BCG), has been approved so far to prevent/attenuate TB disease. Correlates of protection or immunological mechanisms that are needed to control M.tb remain unknown. The protective role of antibodies after BCG vaccination has also remained largely unclear; however, recent studies have provided evidence for their involvement in protection against disease, as biomarkers for the state of infection, and as potential predictors of outcomes. Interestingly, the antibodies generated post-vaccination with BCG are linked to the activation of innate immune cascades, providing further evidence that antibody effector functions are critical for protection against respiratory pathogens such as M.tb. In this review, we aim to provide current knowledge of antibody application in TB diagnosis, prevention, and treatment. Particularly, this review will focus on 1) The role of antibodies in preventing M.tb infections through preventing Mtb adherence to epithelium, antibody-mediated phagocytosis, and antibody-mediated cellular cytotoxicity; 2) The M.tb-directed antibody response generated after vaccination and how humoral profiles with different glycosylation patterns of these antibodies are linked with protection against the disease state; and 3) How antibody-mediated immunity against M.tb can be further explored as early diagnosis biomarkers and different detection methods to combat the global M.tb burden. Broadening the paradigm of differentiated antibody profiling and antibody-based detection during TB disease progression offers new directions for diagnosis, treatment, and preventative strategies. This approach involves linking the aforementioned humoral responses with the disease state, progression, and clearance.

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Introduction: Current immunologic methods cannot distinguish Mycobacterium tuberculosis (Mtb) infection statuses, especially to discriminate active tuberculosis (ATB) from latent tuberculosis infection (LTBI). This study explored the potential of latency-associated antigens (Rv1733cSLP and Rv2028c) and multifactorial cytokine detection to distinguish tuberculosis infection states. Methods: ATB patients (20), LTBI healthcare workers (25), fever patients (11), and healthy controls (10) were enrolled. Cytokine levels (IFN-γ, TNF-α, IL-2, IL-6, IP-10, IL-1Ra, CXCL-1, and MCP-1) were measured using Luminex with/without MTB-specific virulence factor and latency-associated antigens stimulation. Results: Without antigen stimulation, IL-6, IP-10, MCP-1, and IL-1Ra were higher in the ATB group than in the LTBI group (p<0.05), but no significant differences between the ATB group and the fever group. Stimulated with the four antigens, respectively, the cytokines, including IP-10Esat-6, IP-10CFP-10, IFN-γRv1733cSLP, IFN-γRv2028c, IL-6Esat-6, IL-6Rv1733cSLP, IL-6Rv2028c, IL-2Rv1733cSLP, IL-2 Rv2028c, IL-1RaEsat-6, IL-1RaCFP-10, IL-1RaRv2028c, CXCL-1Esat-6, CXCL-1CFP-10, CXCL-1Rv1733cSLP, CXCL-1Rv2028c, MCP-1Esat-6 and MCP-1CFP-10, demonstrated accurate discrimination between ATB and LTBI (p<0.05). Additive concentrations demonstrated significant secretion differences of IFN-γ, IP-10 and IL-2, primarily by virulence factors in ATB and latency-associated antigens in LTBI. Latency-associated antigens synergized with virulence factors, enhancing TH1-type cytokine diagnostic efficacy for discriminating ATB from LTBI, the AUC for TNF-α increased from 0.696 to 0.820 (p=0.038), IFN-γ increased from 0.806 to 0.962 (p=0.025), and IL-2 increased from 0.565 to 0.868 (p=0.007). Model selected by forward likelihood method indicated combined detection of IFN-γCFP-10, IFN-γRv1733cSLP, IP-10Rv1733cSLP, and CXCL-1Rv1733cSLP achieved ATB diagnosis (AUC=0.996) and ATB-LTBI differentiation (AUC=0.992). Combined detection of IFN-γCFP-10 and IFN-γRv1733cSLP achieved tuberculosis infection diagnosis (AUC=0.943). Conclusion: Latency-associated antigens enhance multiple cytokine discriminatory ability, particularly TH1-type cytokines, for differentiating Mtb infection statuses.

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BACKGROUND: Autophagy is crucial for controlling the manifestation of tuberculosis. This study intends to discover autophagy-related molecular clusters as biomarkers for discriminating between latent tuberculosis (LTBI) and active tuberculosis (ATB) in children through gene expression profile analysis. METHODS: The expression of autophagy modulators was examined in pediatric patients with LTBI and ATB utilizing public datasets from the Gene Expression Omnibus (GEO) collection (GSE39939 and GSE39940). RESULTS: In a training dataset (GSE39939), patients with LTBI and ATB exhibited the expression of autophagy-related genes connected with their active immune responses. Two molecular clusters associated with autophagy were identified. Compared to Cluster 1, Cluster 2 was distinguished through decreased adaptive cellular immune response and enhanced inflammatory activation, according to single-sample gene set enrichment analysis (ssGSEA). Per the study of gene set variation, Cluster 2's differentially expressed genes (DEGs) played a role in synthesizing transfer RNA, DNA repair and recombination, and primary immunodeficiency. The peak variation efficiency, root mean square error, and area under the curve (AUC) (AUC = 0.950) were all lowered in random forest models. Finally, a seven-gene-dependent random forest profile was created utilizing the CD247, MAN1C1, FAM84B, HSZFP36, SLC16A10, DTX3, and SIRT4 genes, which performed well against the validation dataset GSE139940 (AUC = 0.888). The nomogram calibration and decision curves performed well in identifying ATB from LTBI. CONCLUSIONS: In summary, according to the present investigation, autophagy and the immunopathology of TB might be correlated. Furthermore, this investigation established a compelling prediction expression profile for measuring autophagy subtype development risks, which might be employed as possible biomarkers in children to differentiate ATB from LTBI.

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Introduction: There is a global gap between tuberculosis incident cases and the notified cases. Active household contact investigation is one of the strategies to narrow this gap. It has the advantage of giving early diagnosis and preventive treatment to vulnerable and eligible groups. This study assessed the practice of contact investigation and tuberculosis preventive treatment adherence in central Ethiopia. Method: A cross-sectional study covering all registered bacteriologically confirmed pulmonary tuberculosis patients and their close contacts was conducted in central Ethiopia from January 1, 2022, to December 30, 2022. Result: A total of 1372 household contacts were declared by the index cases. From these 79.44 % (1090) contacts received a one-time tuberculosis screening giving a total of four (0.36 %) active TB cases. Among 484 household contacts of drug-resistant tuberculosis index cases, 5.53 % (14) had presumptive tuberculosis and 0.79 % (2) had active tuberculosis. While among 837 household contacts of drug-susceptible tuberculosis index cases presumptive TB cases were 1.91 % (16) and active TB cases were 0.23 % (2). Of the 142 eligible under 15 children 81.69 % (116) had started tuberculosis preventive treatment and 84.48 % (98) completed the treatment. On multivariable logistic regression, the associated factor for tuberculosis preventive treatment non-adherence was age 2-5 years (aOR, 0.02, 95 % CI (0.002-0.20) and age 5-15 years (aOR, 0.04,95 % CI (0.002-0 0.95)) P=<0.05). Conclusion: There was low contact screening practice in the DR-TB index cases as compared to national and global targets. The yield of routine contact investigation was low and it indicates the quality of screening. Tuberculosis preventive treatment initiation and completion rates were also low as compared to those of many other countries and global achievements which need further improvement, especially for completion. Alternative mechanisms should be planned to increase the yield of tuberculosis screening and tuberculosis preventive treatment adherence.

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Background: The population with latent tuberculosis infection (LTBI) represents a potential pool of patients with active tuberculosis (ATB). T-SPOT.TB is an important test tool for screening LTBI. Owing to the large population of LTBI patients in China, it is necessary to identify a high-risk group for LTBI and enlarge tuberculosis preventive treatment (TPT) to reduce the incidence of ATB. Methods: Hospitalized patients with positive T-SPOT.TB results were recruited from January 2013 to December 2016. Patients with ATB were excluded. Basic information was collected and the development of ATBs was examined during follow-up. The life-table method was used to calculate cumulative incidence rates. Potential risk factors were analyzed through Cox regression analysis. Results: A total of 1680 patients with LTBI were recruited in the follow-up cohort, and 377 (22.44%) patients dropped out. With a median follow-up time of 81 months [interquartile range (IQR):61-93], 19 of 1303 patients with LTBI developed ATB. The 1-year incidence of ATB was 614 per 100,000 individuals [95%confidence interval (95% CI):584-644]. Over 5-year period, the cumulative incidence of ATB was 1496 per 100,000 [95% CI:1430-1570], and the incidence density was 240 per 100,000 person-years[95% CI:144-375]. In the Cox regression model, exposure of pulmonary tuberculosis (PTB) [adjusted hazard ratio (aHR)=10.557, 95% CI:2.273-49.031], maximum daily dosage of glucocorticoids (GCs)≥ 50 mg/d (aHR=2.948, 95% CI:1.122-7.748), leflunomide (LEF) treatment (aHR=8.572, 95% CI:2.222 -33.070), anemia (aHR=2.565, 95% CI:1.015-6.479) and T-SPOT.TB level≥300SFCs/106 PBMCs (aHR=4.195, 95% CI:1.365-12.892) were independent risk factors for ATB development in LTBI patients. Conclusion: The incidence of ATB is significantly higher in hospitalized patients with LTBI than in the general population. The exposure history of PTB, maximum daily dosage of GCs≥ 50 mg/day, LEF treatment, anemia, and T-SPOT.TB level≥300SFCs/106PBMCs, were the risk factors of tuberculosis reactivation. Hospitalized LTBI patients with the above factors may need TPT.

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Despite the fact that some cases of tuberculosis (TB) are undiagnosed and untreated, it remains a serious global public health issue. In the diagnosis, treatment, and control of latent and active TB, there may be a lack of effectiveness. An understanding of metabolic pathways can be fundamental to treat latent TB infection and active TB disease. Rather than targeting Mycobacterium tuberculosis, the control strategies aim to strengthen host responses to infection and reduce chronic inflammation by effectively enhancing host resistance to infection. The pathogenesis and progression of TB are linked to several metabolites and metabolic pathways, and they are potential targets for host-directed therapies. Additionally, metabolic pathways can contribute to the progression of lung cancer in patients with latent or active TB. A comprehensive metabolic pathway analysis is conducted to highlight lung cancer development in latent and active TB. The current study aimed to emphasize the association between metabolic pathways of tumor development in patients with latent and active TB. Health control programs around the world are compromised by TB and lung cancer due to their special epidemiological and clinical characteristics. Therefore, presenting the importance of lung cancer progression through metabolic pathways occurring upon TB infection can open new doors to improving control of TB infection and active TB disease while stressing that further evaluations are required to uncover this correlation.

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Background: Total hip arthroplasty (THA) is a well-established procedure to cure tubercular hip arthritis in patients with healed tuberculosis while its role in active tuberculosis is still debatable. The aim of the study is to investigate the functional outcomes of THA in active tuberculosis with advanced hip arthritis. The reactivation of tuberculosis and complications postoperatively has also been assessed. Materials and methods: The current open-ended prospective cohort study was carried out at a tertiary center from 2018 to 2020. Twenty patients of active tubercular hip arthritis (8 females and 12 males) were taken with a follow-up period ranging from 1 year to 3 years, with a mean of 14 months.Biochemical investigations were done both preoperatively and postoperatively. Preoperative anti-tubercular therapy (ATT) regimen was administered, as per standard norms, to patients for a minimum period of 6 weeks, and postoperatively for 6 months-12 months. Postero-lateral and Hardinge approaches were employed in all cases. Clinical and radiological parameters were assessed and functional outcomes were evaluated using the Harris Hip score (HHS). Results: The mean age of patients was 37.6 ± 11.38 years. Biochemical parameters were also found to improve postoperatively (p < 0.0001). The mean flexion, extension, abduction, external and internal rotation were found to increase postoperatively (p < 0.001). The mean flexion deformity in the preoperative period was 12.35 ± 4.716, whereas none of the patients had flexion deformities post operatively. The mean shortening was 2.12 ± 0.60 and 1 ± 0 at preoperative and postoperative respectively. The Total hip arthroplasty implant was found stable in all patients. The mean Harris score increased subsequently throughout the follow-up interval and differences were statistically significant (p < 0.0001). None of the patients had reactivation of tuberculosis infection postoperatively. Conclusion: Total hip arthroplasty is a reliable option to treat active advanced tubercular hip arthritis and gives good functional outcome with proper preoperative and postoperative ATT regimen.

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Background: Apoptosis is associated with the pathogenesis of Mycobacterium tuberculosis infection. This study aims to identify apoptosis-related genes as biomarkers for differentiating active tuberculosis (ATB) from latent tuberculosis infection (LTBI). Methods: The tuberculosis (TB) datasets (GSE19491, GSE62525, and GSE28623) were downloaded from the Gene Expression Omnibus (GEO) database. The diagnostic biomarkers differentiating ATB from LTBI were identified by combining the data of protein-protein interaction network, differentially expressed gene, Weighted Gene Co-Expression Network Analysis (WGCNA), and receiver operating characteristic (ROC) analyses. Machine learning algorithms were employed to validate the diagnostic ability of the biomarkers. Enrichment analysis for biomarkers was established, and potential drugs were predicted. The association between biomarkers and N6-methyladenosine (m6A) or 5-methylated cytosine (m5C) regulators was evaluated. Results: Six biomarkers including CASP1, TNFSF10, CASP4, CASP5, IFI16, and ATF3 were obtained for differentiating ATB from LTBI. They showed strong diagnostic performances, with area under ROC (AUC) values > 0.7. Enrichment analysis demonstrated that the biomarkers were involved in immune and inflammation responses. Furthermore, 24 drugs, including progesterone and emricasan, were predicted. The correlation analysis revealed that biomarkers were positively correlated with most m6A or m5C regulators. Conclusion: The six ARGs can serve as effective biomarkers differentiating ATB from LTBI and provide insight into the pathogenesis of Mycobacterium tuberculosis infection.

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BACKGROUND: Tuberculosis (TB) infection remains a crucial global health challenge, with active tuberculosis (ATB) representing main infection source. MicroRNA (miRNA) has emerged as a potential diagnostic tool in this context. This study aims to identify candidate miRNAs for ATB diagnosis and explore their possible mechanisms. METHODS: Differentially expressed miRNAs in ATB were summarized in qualitative analysis. The diagnostic values of miRNAs for ATB subtypes were assessed by overall sensitivity, specificity, and area under the curve. Additionally, we conducted enrichment analysis on miRNAs and target genes. RESULTS: Over 100 differentially expressed miRNAs were identified, with miR-29 family being the most extensively studied. The miR-29 family demonstrated sensitivity, specificity, and area under the curve of 80 %, 80 % and 0.86 respectively for active pulmonary TB (PTB). The differentially expressed miR-29-target genes in PTB were enriched in immune-related pathways. CONCLUSIONS: The miR-29 family exhibits good diagnostic value for active PTB and shows association with immune process.

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Latent tuberculosis infection (LTBI) with fibrotic lesions (FL) can progress to active tuberculosis (TB). Most previous studies have used tuberculin skin tests, which have lower specificity than interferon-gamma release assays (IGRAs), for LTBI diagnosis. This study evaluated the incidence of active TB among individuals with LTBI (diagnosed using IGRAs) and FL in Nishinari District, Osaka City. In total, 54 men (mean age: 68.7 years) were enrolled, of whom 10 (18.5%) were homeless, and 36 (66.7%) were welfare recipients. The median observation period was 1,084 days (range: 64-2,907 days). The incidence rate of active TB among individuals with LTBI and FL was 1.18 (95% confidence interval: 0.32-4.29) cases per 100 person-years. Among the 19 participants who had not been treated with anti-TB therapy, one (5.3%) progressed to active TB, and among the 30 participants who had completed anti-TB treatment, one (3.3%) progressed to active TB. The other 5 participants did not have TB. This study revealed the incidence of active TB among individuals with LTBI, diagnosed using IGRAs, and FL in a vulnerable urban population. The higher incidence than that reported in previous studies reinforces the importance of improved LTBI management strategies, including chest radiography screening, and LTBI treatment.

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This guideline aims to provide comprehensive and practical guidance for clinical management of tuberculosis in kidney transplant recipients. First, it summarizes the particularity of tuberculosis in kidney transplant recipients, and highlights the high incidence and diverse clinical manifestations. To better understand the patients' conditions, relevant assessment of tuberculosis is recommended before kidney transplantation. Extensive attention should be paid to the monitoring of tuberculosis after kidney transplantation. Regarding the diagnosis, the guideline explicitly introduces common diagnostic approaches for tuberculosis, and evaluates the applicability in kidney transplant recipients. After the diagnosis is confirmed, it discusses how to balance the treatment and rejection of tuberculosis under the background of immunosuppressants, and focuses upon the potential drug interaction. In terms of prevention, it emphasizes the screening of tuberculosis prior to kidney transplantation. This guideline is designed to deepen the understanding of medical staff for tuberculosis management in kidney transplant recipients, promote more effective clinical practice and improve the quality of life of the recipients.

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Objective To investigate the Meta-analysis of microRNA(miRNA)in distinguishing active tu-berculosis and latent tuberculosis.Methods CNKI,Wanfang Data,VIP,PubMed,Cochrane Library,Web of Science and Embase databases were searched to select the literature on miRNA in discriminating active tuber-culosis and latent tuberculosis from the establishment of the database to April 2023,and screened strictly ac-cording to the inclusion and exclusion criteria.The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2,and data extraction and summary analysis were carried out with Stata16.0 software.Heterogeneity among studies was evaluated by calculating I2,and the sources of heteroge-neity were further explored by Meta-regression and subgroup analysis.Publication bias was assessed using Deeks funnel plot.Results The Meta-analysis encompassed 9 articles,comprising 13 studies.The combined sensitivity of miRNA in differentiating active tuberculosis and latent tuberculosis was found to be 0.79(95％CI:0.69-0.86,I2=86.24％),with a specificity of 0.73(95％CI:0.64-0.81,I2=81.80％).The positive likelihood ratio was 2.96(95％CI:2.22-3.95,12=63.84％),while the negative likelihood ratio was 0.29(95％CI:0.20-0.41,I2=84.04％).Furthermore,the diagnostic odds ratio was 10.33(95％CI:6.43-16.61,I2=99.90％),and the area under the receiver operating characteristic curve was 0.83(95％CI:0.79-0.86).The results of Meta-regression and subgroup analysis showed that sample size may be the source of sensitivity heterogeneity,and dysregulation of miRNA may be the source of specificity heterogeneity.Deeks funnel plot showed no publication bias among included studies.Conclusion miRNA shows good diagnostic a-bility in distinguishing active tuberculosis and latent tuberculosis,which has important significance for impro-ving the development of diagnostic strategies for tuberculosis management.

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Objective@#To analyse the expression of differential mRNA in the plasma exosomes in patients with latent tuberculosis infection (LTBI) and active tuberculosis (ATB) using high-throughput sequencing, so as to provide insights into differential diagnosis of LTBI and ATB.@*Methods@#The plasma samples were collected from the patients treated at The Affiliated Hospital of Hangzhou Normal University, including 16 cases of LTBI and 21 cases of ATB. The exosomes were extracted by Invitrogen extracellular extracts purification kit, and the size and morphology of exosomes were observed by transmission electron microscope (TEM). The exosomes were identified by Western blotting. Total RNA was extracted from plasma exosomes using high-throughput sequencing, differential expression mRNA was identified, and gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Two differential mRNAs with the highest differential expression fold were selected, and five patients with ATB and three patients with LTBI were recruited for verification using real-time quantitative PCR.@*Results@#The sequencing results of plasma exosomes showed that compared with ATB patients, 2 875 differentially expressed mRNAs were detected in exosomes of LTBI patients, of which 1 002 mRNAs were up-regulated and 1 873 mRNAs were down-regulated. The most significant differentially expressed downregulated and upregulated mRNA were M6PR and RGPD5, respectively. GO analysis and KEGG pathway analysis showed that differential mRNAs were enriched in protein serine kinase activity, rRNA binding molecular function, human cytomegalovirus infection, pancreatic cancer, endometrial cancer, insulin signaling pathway and FoxO signaling pathway. The real-time quantitative PCR showed that the expression of differential mRNA was consistent with sequencing. Compared with ATB patients, the relative expression level of M6PR in plasma exosomes in LTBI patients (0.954±0.212) was downregulated compared with that of ATB patients (2.168±0.226), while the relative expression level of RGPD5 (2.126±0.200) was upregulated compared with that of ATB patients (0.588±0.129) (both P<0.05).@*Conclusions@#There is a difference in mRNA expression of plasma exosomes between patients with LTBI and ATB. M6PR and RGPD5 may become markers for distinguishing plasma exosomes between LTBI and ATB.

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Objectives: To study the characteristics of intestinal microbiota at different stages of Mycobacterium tuberculosis infection. Methods: Fecal samples of 19 active tuberculosis (ATB) patients, 21 latent tuberculosis infection (LTBI) individuals, and 20 healthy controls (HC) were collected. Gut microbiota of all the participants were analyzed by 16S rDNA sequencing. Clinical information of ATB patients was also collected and analyzed. Results: Both ATB and LTBI groups showed significant decreases in microbial diversity and decline of Clostridia. For ATB patients, bacteria within phylum Proteobacteria increased. While for LTBI individuals, genera Prevotella and Rosburia enriched. The abundance of Faecalibacterium, Clostridia and Gammaproteobacteria has the potential to diagnose ATB, with the area under the curve (AUC) of 0.808, 0.784 and 0.717. And Prevotella and Rosburia has the potential to diagnose LTBI, with the AUC of 0.689 and 0.689. Notably, in ATB patients, the relative abundance of Blautia was negatively correlated with the proportions of peripheral T cells and CD8+T cells. And serum direct bilirubin was positively correlated with Bacteroidales, while negatively correlated with Clostridiales in ATB patients. Conclusions: The specifically changed bacteria are promising markers for ATB and LTBI diagnosis. Some gut bacteria contribute to anti-MTB immunity through interactions with T cells and bilirubin.

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Objective: To identify host factors associated with false-negative results of interferon-γ release tests in adults with active tuberculosis. Methods: The clinical data of 943 patients with active tuberculosis diagnosed by acid-fast smear staining, Mycobacterium tuberculosis culture, Mycobacterium tuberculosis PCR and pathological examination at West China Hospital of Sichuan University were retrospectively analysed. According to the results of the interferon γ release test (IGRA), the patients were divided into the IGRA- group and IGRA+ group. Logistic regression was used to analyze the sociodemographic data and clinical characteristics of participants in the IGRA- group and IGRA+ group. Results: Among 943 patients with active tuberculosis, 174 (18.5 %) were IGRA negative (false negative), and 769 (81.5 %) were IGRA positive. Multivariate logistic regression analysis identified the following characteristics independently associated with IGRA negativity: age (OR: 1.02; 95 % CI: 1.01 1.03; p = 0.006), anti-tuberculosis treatment >1 month (OR: 1.68; 95 % CI: 1.12 2.52; p = 0.013), HIV infection (OR: 9.48; 95 % CI: 3.23 27.85; p = 0.000), combined with connective tissue diseases (OR: 2.78; 95 % CI: 1.30 5.94; p = 0.008) and low hemoglobin (OR: 0.99; 95 % CI: 0.98 1.00; p = 0.044) was associated with an increased false-negative probability of IGRA. Conclusion: Age, anti-tuberculosis therapy >1 month, coinfection with HIV, coassociated connective tissue disease and decreased hemoglobin were identified as risk factors for false-negative results of IGRA. Our results suggest a careful interpretation of IGRA in adults with these characteristics.

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BACKGROUND: Autophagy is closely involved in the control of mycobacterial infection. OBJECTIVES: Here, a diagnostic model was developed using the levels of autophagy-related genes (ARGs) in the blood to differentiate active tuberculosis (ATB) and latent tuberculosis infection (LTBI). DESIGN: Secondary data analysis of three prospective cohorts. METHODS: The expression of ARGs in patients with ATB and LTBI were analyzed using the GSE37250, GSE19491, and GSE28623 datasets from the GEO database. RESULTS: Twenty-two differentially expressed ARGs were identified in the training dataset GSE37250. Using least absolute shrinkage and selection operator and multivariate logistic regression, three ARGs (FOXO1, CCL2, and ITGA3) were found that were positively associated with adaptive immune-related lymphocytes and negatively associated with myeloid and inflammatory cells. A nomogram was constructed using the three ARGs. The accuracy, consistency, and clinical relevance of the nomogram were evaluated using receiver operating characteristic curves, the C-index, calibration curves, and validation in the datasets GSE19491 and GSE28623. The nomogram showed good predictive performance. CONCLUSION: The nomogram was able to accurately differentiate between ATB and LTBI patients. These findings provide evidence for future study on the pathology of autophagy in tuberculosis infection.

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Purpose: This study aimed to assess the efficacy of chemiluminescence-based urinary lipoarabinomannan (LAM) antigen assay as a diagnostic tool for identifying active tuberculosis. Methods: A retrospective study was conducted on 166 Tuberculosis (TB), 22 Non-Tuberculous Mycobacteria (NTM), 69 Non-TB cases, and 73 healthy controls from Zhangjiagang First Peoples Hospital between July 2022 and November 2022. Clinical and laboratory data were collected, including urine samples for LAM antigen detection, sputum samples and pleural effusion for GeneXpert, TB-DNA, and culture. Results: TB group exhibited a higher LAM positivity rate (P < 0.001). CD4 count and diabetes as independent factors influencing the diagnostic accuracy of LAM. The LAM assay showed a sensitivity of 50.6% and a specificity of 95.65%. Notably, LAM's sensitivity was superior to TB-DNA (50.60% vs. 38.16%, P < 0.05). LAM's PTB detection rate was 51.7%, superior to TB-DNA (P = 0.047). Moreover, in EPTB cases, the LAM detection rate was 42.11%, surpassing Gene Xpert (P = 0.042), as well as exceeding the detection rates of TB-DNA and sputum culture. Conclusion: LAM antigen detection using chemiluminescence has demonstrated outstanding clinical diagnostic value for active TB, especially in the diagnosis of extrapulmonary TB. The convenience of sample collection in this diagnostic approach allows for widespread application in the clinical diagnosis of active tuberculosis, particularly in cases of EPTB and sputum-negative patients.

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BACKGROUND: Tuberculosis is a chronic infectious disease caused by mycobacterium tuberculosis (MTB) and is the ninth leading cause of death worldwide. It is still difficult to distinguish active TB from latent TB,but it is very important for individualized management and treatment to distinguish whether patients are active or latent tuberculosis infection. METHODS: A total of 220 subjects, including active TB patients (ATB, n = 97) and latent TB patients (LTB, n = 113), were recruited in this study .46 features about blood routine indicators and the VCS parameters (volume, conductivity, light scatter) of neutrophils(NE), monocytes(MO), and lymphocytes(LY) were collected and was constructed classification model by four machine learning algorithms(logistic regression(LR), random forest(RF), support vector machine(SVM) and k-nearest neighbor(KNN)). And the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUROC) to estimate of the model's predictive performance for dentifying active and latent tuberculosis infection. RESULTS: After verification,among the four classifications, LR and RF had the best performance (AUROC = 1, AUPRC = 1), followed by SVM (AUROC = 0.967, AUPRC = 0.971), KNN (AUROC = 0.943, AUPRC = 0.959) in the training set. And LR had the best performance (AUROC = 0.977, AUPRC = 0.957), followed by SVM (AUROC = 0.962, AUPRC = 0.949), RF (AUROC = 0.903, AUPRC = 0.922),KNN(AUROC = 0.883, AUPRC = 0.901) in the testing set. CONCLUSIONS: The machine learning algorithm classifier based on leukocyte VCS parameters is of great value in identifying active and latent tuberculosis infection.

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Objective: The clinical manifestations of tuberculosis (TB) range from asymptomatic to disseminated depending on the microbiological and immunological status, making the diagnosis challenging. To improve our understanding of the disease progression mechanism, we aimed to identify the characteristics of subclinical TB and important predictors of symptom development. Methods: From July 2018 to June 2019, we systemically collected data from the National Surveillance System of South Korea on patients with pulmonary TB, and compared the characteristics of subclinical and active symptomatic TB patients. Results: A total of 4,636 patients with pulmonary TB were included, and the prevalence of subclinical TB was 37.1% (1,720/4,636). In subclinical TB patients, the positivity rates of acid-fast bacilli (AFB) smear and culture were 16.2 and 50.2%, respectively. Subclinical TB patients were younger (55.6 ± 19.2 vs. 60.7 ± 19.5, P < 0.001), had a higher body mass index (21.7 ± 3.1 vs. 21.0 ± 3.5, P < 0.001), less under Medicaid support, and had lower rates of chronic lung disease, AFB smear and culture positivity, and bilateral disease. Regarding the characteristic differences of individual TB-related symptoms, age was positively associated with dyspnoea and general weakness but negatively associated with chest pain, haemoptysis, and weight loss. Male patients were more prone to weight loss. Chronic lung disease was related to symptoms including cough/phlegm, dyspnoea, and haemoptysis, while autoimmune diseases were associated with fever and weight loss. Conclusions: The development of TB-related symptoms was associated with microbiological burden and clinical characteristics including underlying comorbidities, which should be evaluated carefully.

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BACKGROUND: The tuberculin-purified protein derivative (PPD) test is commonly used as a screening tool for tuberculosis (TB). However, the traditional judgment standard of the PPD test is influenced by subjective factors, which can lead to less accurate and intuitive test results. OBJECTIVES: To evaluate the accuracy of ultrasonography as a novel auxiliary judgment method for the tuberculin-PPD test and its clinical application. DESIGN: This study was designed as a comparative study following the STROBE guidance. METHODS: From February to May 2022, 208 patients with active tuberculosis infection were enrolled. Manual judgment and ultrasonography were employed in a double-blind-utilized manner, and the PPD examination results were recorded. Kappa statistic was performed to measure the concordance between the two diagnostic methods. Fisher's exact test was used for the analyses of the PPD test results of all 208 active tuberculosis infection patients' PPD results. RESULTS: There was a significant difference between the two methods in the PPD result judgment (p < 0.001), particularly in the positive ratio of the PPD test results, (p < 0.05). Overall, 50 patients were determined as PPD positive based on manual judgment. However, only 24 patients' PPD test results were determined as positive via ultrasonography. The remaining 26 patients should have been classified as strong positive but were misclassified as positive. The misdiagnosis ratio was 52% (26/50). CONCLUSION: Ultrasonography has superior accuracy to traditional manual judgment. Moreover, it does not rely on sophisticated clinical experience or training and can reveal subtle changes of the skin corresponding to each PPD test result providing intuitive results. In conclusion, ultrasonography can be used as an auxiliary interpretive approach for PPD test and has a promising future for clinical application.

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