Search Results (684)

Background: Tuberculosis (TB) is a leading cause of death among people living with HIV (PLHIV). While body mass index (BMI) affects TB risk, its association with latent tuberculosis infection (LTBI) in PLHIV is unclear. High-transmission settings, such as prisons, may further increase LTBI risk, yet this relationship has not been studied across both prison and community populations of PLHIV. Methods: We conducted a dual cross-sectional study of PLHIV in Jiangsu Province, China, recruiting participants from a prison hospital in 2021 and community healthcare facilities from July to November 2023. BMI was calculated from measured height and weight. LTBI was identified by a positive ESAT6-CFP10 (EC) skin test or the QuantiFERON-TB Gold In-Tube (QFT-GIT) assay. Logistic regression and generalized additive models (GAMs) assessed the association between BMI and LTBI, adjusting for demographic, clinical, and behavioral confounders. Results: A total of 1799 PLHIV were included in the analysis, of whom 343 (19.07%) were recruited from prison settings and 1456 (80.93%) from community-based screening. The overall prevalence of LTBI was 13.79% (n = 248). Obesity (BMI ≥ 28 kg/m²) was linked to a significantly lower risk of LTBI (adjusted OR = 0.47, 95% CI: 0.23–0.95, p = 0.036), particularly when identified by EC testing (adjusted OR = 0.13, 95% CI: 0.03–0.54, p = 0.005). The BMI–LTBI association followed a nonlinear “U-shaped” pattern, with the lowest prevalence in individuals who were obese. Among those with CD4+ T cell counts < 500 cells/μL, the inverse association between obesity and LTBI was even more marked (adjusted OR = 0.20, 95% CI: 0.05–0.83, p = 0.027). Conclusion: In summary, obesity is significantly associated with a lower risk of LTBI among PLHIV, with an approximate 54% risk reduction. This inverse relationship was most pronounced when using the EC skin test. Full article

Background and Objectives: Active pulmonary tuberculosis (aPTB) in the Older Adults (≥75 years) is frequently under-recognized in non-pulmonology settings due to atypical symptoms and multiple comorbidities. This study aimed to develop and validate a TRIPOD-compliant clinical prediction model for early identification of atypical aPTB in this vulnerable population. Materials and Methods: We retrospectively analyzed 5651 patients aged ≥75 years with culture-confirmed aPTB and World Health Organization (WHO) symptom scores < 5. Patients were stratified into Group a (Ga, Patients with aPTB not initially suspected by non-pulmonologists (atypical presentation, WHO/CDC 7-point score < 5, n = 1155) and Group b (Gb, Patients without aPTB within the first 24 h (non-TB comparators), n = 4496). Multivariate logistic regression identified independent predictors of delayed diagnosis. A weighted scoring system was derived from β-coefficients and validated in independent derivation (2000–2020) and temporal validation (2021–2023) cohorts. Model discrimination, calibration, and decision curve analysis (DCA) were assessed following TRIPOD standards. Results: Five independent predictors—age > 85 years (OR = 6.31, 95% CI = 5.31–8.72), hypoalbuminemia (OR = 4.10, 95% CI = 3.92–7.26), cardiovascular disease (OR = 3.32, 95% CI = 1.23–5.27), diabetes mellitus (OR = 2.03, 95% CI = 1.32–4.07), and predominant lower-lung field involvement (OR = 1.25,95% CI = 1.03–2.44)—were incorporated into the scoring model. Using a cutoff ≥ 7, the model achieved excellent performance across all cohorts (AUC 0.95–0.96; sensitivity 91–94%; specificity 97–99%). Calibration plots and DCA confirmed strong agreement and high net clinical benefit. Nearly 70% of atypical cases had symptom scores ≤ 1, lacking typical signs such as fever or cough. Conclusions: Oldest-old (>85 years) emerged as the strongest independent predictor of atypical TB, surpassing conventional frailty indicators such as sarcopenia or osteoporosis. The proposed score provides a simple, accurate, and validated tool for early detection of aPTB in non-pulmonology settings. Its integration into electronic medical records may reduce diagnostic delays and improve outcomes in this high-risk, late-elderly population. Full article

Background: Infection prevention and control (IPC) in hospitals relies heavily on infection control nurses (ICNs) who manage complex consultations to prevent and control infections. This study evaluated large language models (LLMs) as artificial intelligence (AI) tools to support ICNs in IPC decision-making processes. Our goal is to enhance the efficiency of IPC practices while maintaining the highest standards of safety and accuracy. Methods: A cross-sectional benchmarking study at Queen Mary Hospital, Hong Kong assessed three LLMs—GPT-4.1, DeepSeek V3, and Gemini 2.5 Pro Exp—using 30 clinical infection control scenarios. Each model generated clarifying questions to understand the scenarios before providing IPC recommendations through two prompting methods: an open-ended inquiry and a structured template. Sixteen experts, including senior and junior ICNs and physicians, rated these responses on coherence, conciseness, usefulness and relevance, evidence quality, and actionability (1–10 scale). Quantitative and qualitative analyses assessed AI performance, reliability, and clinical applicability. Results: GPT-4.1 and DeepSeek V3 scored significantly higher on the composite quality scale, with adjusted means (95% CI) of 36.77 (33.98–39.57) and 36.25 (33.45–39.04), respectively, compared with Gemini 2.5 Pro Exp at 33.19 (30.39–35.99) (p < 0.001). GPT-4.1 led in evidence quality, usefulness, and relevance. Gemini 2.5 Pro Exp failed to generate responses in 50% of scenarios under structured prompt conditions. Structured prompting yielded significant improvements, primarily by enhancing evidence quality (p < 0.001). Evaluator background influenced scoring, with doctors rating outputs higher than nurses (38.83 vs. 32.06, p < 0.001). However, a qualitative review revealed critical deficiencies across all models, for example, tuberculosis treatment solely based on a positive acid-fast bacilli (AFB) smear without considering nontuberculous mycobacteria in DeepSeek V3 and providing an impractical and noncommittal response regarding the de-escalation of precautions for Candida auris in Gemini 2.5 Pro Exp. These errors highlight potential safety risks and limited real-world applicability, despite generally positive scores. Conclusions: While GPT-4.1 and DeepSeek V3 deliver useful IPC advice, they are not yet reliable for autonomous use. Critical errors in clinical judgment and practical applicability highlight that LLMs cannot replace the expertise of ICNs. These technologies should serve as adjunct tools to support, rather than automate, clinical decision-making. Full article

Drug-resistant tuberculosis represents a challenge with high potential for spread. This ecological study aimed to describe the prevalence and incidence of drug-resistant tuberculosis and analyze its spatial, temporal, and spatiotemporal patterns in Paraná, Brazil, 2012–2023, and forecast trends through 2030. National surveillance data were analyzed using descriptive statistics, Mann–Kendall trend tests, Global and Local Moran’s I, Kulldorff’s spatial scan statistic, and Seasonal AutoRegressive Integrated Moving Average modeling. A total of 576 cases were identified, corresponding to an incidence of 5.08 per 100,000 inhabitants, with an increasing trend (p < 0.001). After peaking in 2019, incidence declined during the pandemic and rose in 2023. Isoniazid monoresistance was the most frequent profile. Prevalence was higher among males, young adults (15–34 years), and Asian and Black individuals. Spatial distribution showed expansion over time, with early circulation in the West. The North and Northwest exhibited an initial high incidence. Spatial and spatiotemporal analyses identified persistent high-risk clusters in these regions (p < 0.05). Forecasting suggests that, if current conditions persist, the incidence may continue to rise through 2030. The findings highlight the need for surveillance to ensure treatment adherence and interrupt transmission of resistant bacilli, supporting progress toward the global goal of tuberculosis elimination. Full article

Background/Objectives: Tuberculosis (TB) remains a global health challenge due to long treatment durations, poor adherence, and growing drug resistance. Inhalable co-amorphous systems (COAMS) offer a promising strategy for targeted pulmonary delivery of fixed-dose combinations, improving efficacy and reducing systemic side effects. Methods: Our in-house-developed machine learning (ML) tool identified two promising API-API combinations for TB therapy, rifampicin (RIF)–moxifloxacin (MOX) and RIF–ethambutol (ETH). Physiologically based pharmacokinetic (PBPK) modeling was used to estimate therapeutic lung doses of RIF, ETH, and MOX following oral administration. Predicted lung doses were translated into molar ratios, and COAMS of RIF-ETH and RIF-MOX at both model-predicted (1:1) and PBPK-informed ratios were prepared by spray drying and co-milling, followed by comprehensive physicochemical and aerodynamic characterization. Results: RIF-MOX COAMS could be prepared in all molar ratios tested, whereas RIF-ETH failed to result in COAMS for therapeutically relevant molar ratios. Spray drying and ball milling successfully produced stable RIF-MOX formulations, with spray drying showing superior behavior in terms of morphology (narrow particle size distribution; lower Sauter mean diameter), aerosolization performance (fine particle fraction above 74% for RIF and MOX), and dissolution. Conclusions: This study demonstrated that PBPK modeling and ML are useful tools to develop COAMS for pulmonary delivery of active pharmaceutical ingredients (APIs) routinely applied through the oral route. It was also observed that COAMS may be less effective when the therapeutic lung dose ratio significantly deviates from the predicted 1:1 molar ratio. This suggests the need for alternative delivery strategies in such cases. Full article

Background/Objectives: The diagnosis of Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacterial (NTM) infections is accomplished by three main diagnostics methods: smear microscopy, culture, and molecular testing. Diagnostic algorithms used by laboratories can significantly impact clinical and infection control management. Current Canadian Tuberculosis Standards recommend the use of nucleic acid amplification testing (NAAT) for smear-positive patients and smear-negative patients upon request. An alternative algorithm is to utilize NAAT in the Panel approach on all samples, pulmonary and extrapulmonary, to potentially reduce time to diagnosis and treatment. This alternative approach was implemented in November 2019 at the Newfoundland and Labrador Public Health and Microbiology Laboratory (NL PHML) using a laboratory-developed multiplex real-time PCR (LDT m-qPCR) assay targeting Mycobacterium spp. (Myco spp.) and MTBC, performed in parallel with smear and culture. Methods: To investigate the impact of this alternate testing approach, we conducted an observational retrospective analysis of laboratory diagnostic and treatment data, recognizing that temporal changes in epidemiology, clinical practice, and laboratory workflow may also have influenced outcomes. To complete this, study data from three years before and four years after implementation were gathered. Results: The sensitivity/specificity of the smear, m-LDT qPCR-MTBC, m-LDT qPCR-Myco spp., and culture assays in this study were 18.1%/100%, 96.7%/99.8%, 47.6%/99.0%, and 96.8%/100%, respectively. The gold standard utilized for these calculations was clinical diagnosis for active MTBC disease and culture for NTM infections, recognizing that the use of clinical diagnosis may introduce subjectivity. The Panel approach reduced the time to diagnosis of tuberculosis MTBC by 29 days (p < 0.0001) for NL PHML, and when modelled for a laboratory with rapid culture identification, diagnosis was reduced by 14 days (p = 0.003). Among non-empirically treated tuberculosis patients, the time to treatment was decreased by 25.5 days (p < 0.001). For NTM infections, rapid diagnostics only affected one patient’s treatment. This finding agrees with clinical management guidelines, which do not routinely utilize rapid diagnostics for the diagnosis of disease or treatment decisions. The cost implications of additional NAAT testing were calculated to be an increase of CAD 23.62 per sample. Conclusions: Our findings support the adoption of a molecular assay for MTBC as an initial diagnostic tool to decrease time to diagnosis and time to treatment, depending on local epidemiology and irrespective of smear status. Utilizing a molecular assay for genus level identification of NTM had minimal impact on clinical management suggesting its limited diagnostic utility in a broad population setting. Full article

Tuberculosis (TB) probably returned to being the world’s leading cause of death from a single infectious agent after three years during which it was replaced by COVID-19. Currently, there are two major, closely related challenges in TB treatment: a large number of cases of drug-resistant TB, as well as cases complicated by severe comorbidities. Materials and Methods: Our study included 219 patients with pulmonary multidrug-resistant TB (MDR-TB) who were treated in several clinics in St. Petersburg, Russian Federation. Of these patients, 47.0% had extensively drug-resistant TB (XDR-TB), and 48.4% had severe comorbidities. Univariate and multivariate exploratory analyses were performed to hypothesize factors affecting treatment success. Results: Both extensive drug resistance (XDR-TB) and the presence of comorbidity were significantly associated with a lower probability of successful treatment: OR = 0.56 (CI: 0.32–0.96, p = 0.033) and OR = 0.53 (CI: 0.30–0.91, p = 0.020), respectively. The use of bedaquiline was significantly associated with successful treatment in cases of XDR-TB: OR = 4.15 (CI: 1.32–16.20, p = 0.012). Only an insignificant opposite effect was identified for cases of non-XDR-TB: OR = 0.77 (p = 0.62). Resistance to thioamides was associated with unsuccessful treatment in cases complicated by comorbidity: OR = 0.46 (CI: 0.21–0.99, p = 0.044). Again, an only insignificant opposite effect was identified for cases without comorbidities: OR = 1.11 (p = 0.81). Almost all the patterns described above were replicated in the multivariate model. The following two differences with the univariate results were observed. First, the association between the use of bedaquiline and successful treatment became even more pronounced, and, as before, this was true only for XDR-TB: OR = 6.51 (CI: 1.98–26.04, p = 0.0036) for XDR-TB, and OR = 0.99 (p = 0.98) for non-XDR-TB. Second, the impact of comorbidities on treatment success remained significant only in conjunction with thioamide resistance. In addition, we found that the association between resistance to thioamides and unsuccessful treatment was especially pronounced in cases complicated by heart disease: OR = 0 (CI: 0–0.79, p = 0.0088). Conclusions: We confirmed that both XDR-TB and the presence of comorbidities are serious challenges in the treatment of tuberculosis. We also have reason to hypothesize that, first, bedaquiline can be a much more crucial component of therapy in cases of XDR-TB than in other cases of MDR-TB and, second, thioamides can play a positive role in cases complicated by comorbidities, especially by heart diseases. These findings should be considered as weak hypotheses that require further verification using independent data, as our analysis was exploratory rather than confirmatory. Full article

Tuberculosis (TB) is one of the leading infectious causes of mortality worldwide. Although a significant proportion of the population (up to 36%, depending on the region) is infected with the latent form of TB, only about one in ten of these people will develop an active form of the disease in their lifetime. This is due to a complex interaction between the host’s genetic predisposition and environment. However, the genetic determinants of TB are not well established and have been insufficiently explored in previous genome-wide association studies (GWAS) with sparse and incongruent results. We reviewed recent evidence on host genetic susceptibility to TB, highlighting population-specific characteristics, host–pathogen coevolution, and the limitations of conventional GWAS approaches in terms of clinical and genetic heterogeneity. While rare variants with high penetrance, such as TYK2 P1104A, lead to monogenic susceptibility, most heritable risk results from the cumulative effect of numerous common variants. This cumulative effect may be summarized using polygenic risk scores (PRSs). Although their use has been proven for non-communicable diseases, PRSs are not applied to infectious disease susceptibility. To date, no PRS model for susceptibility to tuberculosis has been consistently validated. The development of PRSs for TB susceptibility is limited by phenotypic heterogeneity, population structure, and co-adaptation between host and pathogen. Another major challenge is to take into account the considerable influence of environmental factors. This difficulty in modeling environmental influences probably explains the current lack of a clinically applicable PRS for TB susceptibility. However, taking these caveats into account, polygenic models could improve risk stratification at the individual level compared to single-variant association and allow for earlier targeted treatment and prophylaxis. Full article

In Mexico, syphilis and tuberculosis are infectious diseases subject to mandatory and immediate epidemiological surveillance, both with special systems that allow nominal follow-up for either variant. Surveillance uses the operational definitions of probable and confirmed cases established in the manual for epidemiological surveillance issued by the General Directorate of Epidemiology of the Ministry of Health. However, both diseases, mainly in the chronic state, present challenges because of their ability to mimic autoimmune disorders. This review explores the phenomenon of clinical and immunological mimicry in secondary and tertiary syphilis, as well as in extrapulmonary tuberculosis, and analyzes its implications for the accuracy of case reporting at the national level. Evidence shows that both infections can present systemic inflammatory features, such as elevated acute phase reactants, positive autoantibodies, and alterations in cerebrospinal fluid that resemble autoimmune profiles. These overlaps can lead to misdiagnosis, inappropriate immunosuppressive treatment and misclassification of confirmed cases within the Mexican surveillance system. Surveillance of these conditions is robust; however, current operational definitions have weaknesses, particularly when atypical or autoimmune conditions are present, as they only focus on cases with the highest prevalence or public health impact. This manuscript proposes the integration of differential diagnostic algorithms and expanded laboratory criteria, including autoimmune markers and molecular tests, into surveillance protocols. Although individual efforts exist in health institutions, in our country, the absence of autoimmune diseases in the national register of obligatory notification stands out, contrasting with surveillance models in other countries, where autoimmune diseases are tracked systematically. To improve diagnostic accuracy and reporting, surveillance systems should incorporate a syndromic and etiological approach, recognizing infectious autoimmune mimicry as a factor in the final recording of confirmed cases to avoid epidemiological silence. Full article

Cell division is critical for the survival, growth, pathogenesis, and antibiotic susceptibility of Mycobacterium tuberculosis (Mtb). However, the regulatory networks governing the transcription of genes involved in cell growth and division in Mtb remain poorly understood. This study aimed to investigate the impact of BlaI overexpression on cell division and growth in Mtb and elucidate the underlying mechanisms. Mycobacterium smegmatis mc²155 was used as the model organism. Recombinant strains overexpressing BlaI were constructed. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), ethidium bromide and Nile red uptake assays, minimum inhibitory concentration (MIC) determination, drug resistance analysis, quantitative real-time PCR (qRT-PCR) assays, and electrophoretic mobility shift assay (EMSA) were employed to assess changes in bacterial morphology, cell wall permeability, antibiotic susceptibility, gene transcription levels, and the interaction between BlaI and its target genes. Overexpression of BlaI disrupted bacterial division in M. smegmatis, leading to growth delay, cell elongation, and formation of multi-septa. It also altered the lipid permeability of the cell wall and enhanced the sensitivity of M. smegmatis to β-lactam antibiotics. BlaI overexpression affected the transcription of cell division-related genes, particularly downregulating ftsQ. Additionally, BlaI negatively regulated the transcription of Rv1303—a gene co-transcribed with ATP synthase-encoding genes—inhibiting ATP synthesis. This impaired the phosphorylation of division complex proteins, ultimately affecting cell division and cell wall synthesis. Overexpression of BlaI in Mtb interferes with bacterial division, slows growth, and alters gene expression. Our findings identify a novel role for BlaI in regulating mycobacterial cell division and β-lactam susceptibility, providing a foundation for future mechanistic studies in M. tuberculosis, with validation required to assess relevance to clinical tuberculosis—though validation in M. tuberculosis and preclinical models is required. Full article

Background: Tuberculous meningitis (TBM) is the most severe form of tuberculosis and is associated with high morbidity and mortality, especially in resource-limited settings. In Mozambique, where both tuberculosis and HIV are highly prevalent, TBM poses significant diagnostic and therapeutic challenges. This study aimed to describe the clinical characteristics and to identify predictors of TBM mortality among persons living with HIV (PLWH) in a rural hospital in Mozambique. Methods: We conducted a retrospective cohort study at Carmelo Hospital of Chokwe (CHC) between 2015 and 2020. We included 372 PLWH diagnosed with TBM (PTBM); data on demographics, clinical presentation, and laboratory findings were extracted from patient records. TBM diagnosis was considered for confirmed cases based on a hospital-adapted algorithm incorporating clinical features, cerebrospinal fluid (CSF) analysis, TB-LAM, and Xpert MTB/RIF testing. Cox proportional hazard models were used to identify independent predictors of mortality, and Kaplan–Meier survival curves with log-rank tests were used to assess survival differences across clinical subgroups. Significance was considered at a p value ≤ 0.05 with an adjusted hazard ratio (AHR) 95% CI in the multivariate analysis. Results: Overall, 372 PTBM contributed to a total of 3720 person-months (PM) of treatment follow-up, corresponding to a mortality incidence of 3.76 deaths per 100 person-months. Factors independently associated with increased mortality included male sex (adjusted hazard ratio [aHR]: 1.80; 95% CI: 1.21–2.68; p = 0.004), BMI < 18.5 kg/m² (aHR: 2.84; 95% CI: 1.46–5.55; p = 0.002), Immunovirological failure to ART (aHR: 2.86; 95% CI: 1.56–5.23; p = 0.001), CSF opening pressure >40 cmH₂O (aHR: 2.67; 95% CI: 1.46–4.86; p = 0.001), and TBM severity grading III (aHR: 4.59; 95% CI: 1.79–11.76; p = 0.001). TBM involving other organs also significantly worsened survival (aHR: 2.03; 95% CI: 1.27–3.25; p = 0.003). Conclusions: TBM mortality in PLWH was driven by ART failure, high CSF pressure, and malnutrition. Male sex and severe neurology also increased risk. Urgent interventions are proposed: optimize ART, manage intracranial pressure, provide nutritional support, and use corticosteroids. An integrated care approach is essential to improving survival in resource-limited settings. Full article

Identification of young children with Mycobacterium tuberculosis (Mtb) infection is critical to curb pediatric morbidity and mortality. The optimal test to identify young children with Mtb infection remains controversial. Using a tuberculosis (TB) household contact (HHC) study design among 130 Ugandan children less than 5 years of age with Mtb exposure, this study was conducted to determine the following: (1) the prevalence of Mtb immune sensitization in young children heavily exposed to TB using both the tuberculin skin test (TST) and QuantiFERON Gold Plus (QFT-Plus) interferon gamma release assay, and to examine the concordance of these two tests; and (2) the diagnostic accuracy of TST and QFT-plus for confirmed and unconfirmed TB in young children. Prevalence of Mtb immune sensitization was determined using TST at both 5 mm and 10 mm thresholds for positivity; manufacturer’s thresholds were utilized to establish QFT-Plus positivity. Concordance analysis between TST and QFT-Plus results was performed, including correlation between QFT-Plus tube TB.1 and tube TB.2. The sensitivity and specificity of TST and QFT-Plus for confirmed and unconfirmed TB was determined, and a logistic regression model was utilized to estimate the odds of TB. A 5 mm TST threshold identified the most children with Mtb sensitization (49.2%) and had moderate agreement with QFT-Plus (Cohen’s Kappa 0.59). The odds of TB were two times higher among children with a positive TST using a 5 mm threshold. Concordance between 10 mm TST threshold and QFT-Plus was substantial (Cohen’s Kappa 0.65), with higher concordance observed among older children (2–5 years). The QFT-Plus tube TB.1 and tube TB.2 results were highly correlated. Positive TST using a 5 mm threshold demonstrated the highest sensitivity for TB (60%), whereas QFT-Plus testing demonstrated the highest specificity (72%). Overall, our findings support that among a population of young, BCG-vaccinated children with heavy household exposure to TB, the TST using a 5 mm threshold identified more children with evidence of Mtb immune sensitization, and children with TB disease, than the QFT-Plus. These findings are highly relevant for children who are TB HHCs in endemic settings, and most at risk for TB following an exposure. We recommend that TST testing continue to be performed to assess for Mtb sensitization in young, TB-exposed children in TB-endemic settings to both prioritize provision of preventive therapy and to aide in diagnosis of pediatric TB. Full article

Isoniazid (isonicotinic acid hydrazide, INH) is a key drug used to treat tuberculosis (TB), which continues to be the world’s most lethal infectious disease. Nevertheless, the efficacy of INH has diminished because of the emergence of Mycobacterium tuberculosis (Mtb) strains that are resistant to INH. Our goal in this study was to modify INH to reduce this significant resistance chemically. We synthesized INH-based hydrazones (IP1–IP13) through the reaction of INH with in-house obtained benzaldehydes carrying a piperidine or piperazine ring in refluxing ethanol. Upon confirmation of their proposed structures by various spectral techniques, IP1–IP13 were evaluated for their antimycobacterial capacity against Mtb H37Rv strain and INH-resistant clinical isolates with katG and inhA mutations using the Microplate Alamar Blue Assay (MABA). The compounds were additionally tested for their cytotoxicity. The obtained data indicated that the compounds with moderately increased lipophilicity compared to INH (IP7–IP13) were promising antitubercular drug candidates, exhibiting drug-like properties and negligible cytotoxicity. Out of these, IP11 (N′-(4-(4-cyclohexylpiperazin-1-yl)benzylidene)isonicotinohydrazide) emerged as the most promising derivative, demonstrating the lowest MIC values against all Mtb strains tested. Subsequently, the target molecules were evaluated for their capacity to inhibit enoyl acyl carrier protein reductase (InhA), the main target enzyme of INH. Except for IP11 demonstrating 81% InhA inhibition at a concentration of 50 μM, direct InhA inhibition was shown not to be the primary mechanism responsible for the antitubercular activity of the compounds. The binding mechanism of IP11 to InhA was analyzed through molecular docking and molecular dynamics simulations. Altogether, our research identified a novel approach to modify INH to address the challenges posed by the rising prevalence of drug-resistant Mtb strains. Full article

Attenuated Salmonella strains offer an opportunity for delivering DNA vaccines to antigen-presenting cells. DNA vaccines trigger cellular immune responses, making them suitable for targeting intracellular pathogens, such as Mycobacterium avium subspecies paratuberculosis (MAP). Since whole organism MAP vaccines interfere with tuberculosis diagnosis, innovative vaccine technologies have been introduced to elicit an immune response targeting species-specific antigens. Fibronectin attachment protein (FAP), a MAP surface antigen that is species-specific, can induce cellular immune responses. The present study aims to explore the immunogenic potential of a mammalian expression plasmid encoding the fap-P gene of MAP within a mouse model, utilizing a Salmonella vector for oral immunization using a fluorescent assay and Western blot analysis. The results proved the ability of the constructed plasmid to stimulate the humoral immune response in mice. Moreover, fluorescence microscopy of splenocytes confirmed the successful delivery of the plasmid to the immune system at 24, 48, and 72 h following oral administration. It can be concluded that FAP-P could be considered a candidate for further investigation in the context of MAP vaccine development. Additionally, the use of Salmonella as a delivery system not only improves the efficacy of DNA vaccines but also helps in the preliminary evaluation of the antigens’ immunogenic properties. Full article

We developed a machine-learning model for the International Classification of Diseases, 10th Revision (ICD-10) classification using data from 5108 patients. Nine features, including age, gender, BMI, and vital signs, were extracted to classify the top three ICD-10 categories: intestinal infections, tuberculosis, and other bacterial diseases. Decision trees, random forest, and XGBoost models were tested using the synthetic minority over-sampling technique (SMOTE) and class weights to minimize class imbalance. Five-fold cross-validation was used using the training and testing datasets in a data ratio of 80:20. The random forest model with class weights showed the best performance. Shapley additive explanations (SHAP) analysis highlighted body-mass index (BMI), gender, and pulse as key features. The developed model showed potential for enhancing ICD-10 classification through real-time and personalized medical applications. Full article