Land disposal of dredged sediments from an urbanized tropical lagoon: toxicity to soil fauna.

Urban tropical lagoons are commonly impacted by silting, domestic sewage and industrial wastes and the dredging of their sediments is often required to minimize environmental impacts. However, the ecological implications of land disposal of dredged sediments are still poorly investigated in the tropics. Aiming to contribute to filling this gap, an ecotoxicological evaluation was conducted with dredged sediments from Tijuca Lagoon (Rio de Janeiro, Brazil) using different lines of evidence, including soil and sediment characterization, metal determination, and acute and avoidance bioassays with Eisenia andrei. Two different dredged sediment samples, a sandy sediment and another muddy one, were obtained in two distinct and spatially representative sectors of the Tijuca Lagoon. The sediments were mixed with an artificial soil, Ferralsol and Spodosol to obtain doses between 0 (pure soil) and 12%. The sediment dose that caused mortality (LC50) or avoidance responses (EC50) to 50% of the organisms was estimated through PriProbit analysis. Metal concentrations and toxicity levels were higher in the muddy sediment (artificial soil LC50 = 3.84%; Ferralsol LC50 = 4.58%; Spodosol LC50 = 2.85%) compared to the sandy one (artificial soil LC50 = 10.94%; Ferralsol LC50 = 14.36%; Spodosol LC50 = 10.38%), since fine grains tend to adsorb more organic matter and contaminants. Mortality and avoidance responses were the highest in Spodosol due to its extremely sandy texture (98% of sand). Metal concentrations in surviving earthworms were generally low, except sodium whose bioaccumulation was high. Finally, the toxicity is probably linked to marine salts, and the earthworms seem to accumulate water in excess to maintain osmotic equilibrium, increasing their biomass.

Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.

BACKGROUND: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN). METHODS: We performed a retrospective study of all TB cases reported to SINAN between 2015 and 2022; excluding children (< 18 years-old), vulnerable groups or drug-resistant TB. For the score, data before treatment initiation were used. We trained and internally validated three different prediction scoring systems, based on Logistic Regression, Random Forest, and Light Gradient Boosting. Before applying our models we splitted our data into training (~ 80% data) and test (~ 20%) sets, and then compared the model metrics using the test data set. RESULTS: Of the 243,726 cases included, 41,373 experienced LTFU whereas 202,353 were successfully treated. The groups were different with regards to several clinical and sociodemographic characteristics. The directly observed treatment (DOT) was unbalanced between the groups with lower prevalence in those who were LTFU. Three models were developed to predict LTFU using 8 features (prior TB, drug use, age, sex, HIV infection and schooling level) with different score composition approaches. Those prediction scoring systems exhibited an area under the curve (AUC) ranging between 0.71 and 0.72. The Light Gradient Boosting technique resulted in the best prediction performance, weighting specificity and sensitivity. A user-friendly web calculator app was developed ( https://tbprediction.herokuapp.com/ ) to facilitate implementation. CONCLUSIONS: Our nationwide risk score predicts the risk of LTFU during ATT in Brazilian adults prior to treatment commencement utilizing schooling level, sex, age, prior TB status, and substance use (drug, alcohol, and/or tobacco). This is a potential tool to assist in decision-making strategies to guide resource allocation, DOT indications, and improve TB treatment adherence.

Improved Treatment Outcome Following the Use of a Wound Dressings in Cutaneous Leishmaniasis Lesions.

Leishmaniasis, caused by Leishmania parasites, is a neglected tropical disease and Cutaneous Leishmaniasis (CL) is the most common form. Despite the associated toxicity and adverse effects, Meglumine antimoniate (MA) remains the first-choice treatment for CL in Brazil, pressing the need for the development of better alternatives. Bacterial NanoCellulose (BNC), a biocompatible nanomaterial, has unique properties regarding wound healing. In a previous study, we showed that use of topical BNC + systemic MA significantly increased the cure rate of CL patients, compared to treatment with MA alone. Herein, we performed a study comparing the combination of a wound dressing (BNC or placebo) plus systemic MA versus systemic MA alone, in CL caused by Leishmania braziliensis. We show that patients treated with the combination treatment (BNC or placebo) + MA showed improved cure rates and decreased need for rescue treatment, although differences compared to controls (systemic MA alone) were not significant. However, the overall time-to-cure was significantly lower in groups treated with the combination treatment (BNC+ systemic MA or placebo + systemic MA) in comparison to controls (MA alone), indicating that the use of a wound dressing improves CL treatment outcome. Assessment of the immune response in peripheral blood showed an overall downmodulation in the inflammatory landscape and a significant decrease in the production of IL-1a (p < 0.05) in patients treated with topical BNC + systemic MA. Our results show that the application of wound dressings to CL lesions can improve chemotherapy outcome in CL caused by L. braziliensis.

Inflammatory profiles in sputum and blood of people with TB with and without HIV coinfection.

Although tuberculosis (TB) remains a major killer among infectious diseases and the leading cause of death for people with HIV, drivers of immunopathology, particularly at the site of infection in the lungs remain incompletely understood. To fill this gap, we compared cytokine profiles in paired plasma and sputum samples collected from adults with pulmonary TB with and without HIV. We found that people with pulmonary TB with HIV had significantly higher markers of inflammation in both plasma and sputum than those without HIV; these differences were present despite a similar extent of radiographic involvement. We also found that the strength and direction of correlations between biomarkers in the blood and lung compartments differed by HIV status and people with HIV had more positive correlations than those without HIV. Future studies can further explore these differences in inflammation by HIV status across the blood and lung compartments and seek to establish how these profiles may be associated with long-term outcomes and lung health after completion of TB treatment.

Divergent Associations of Slow-Wave Sleep versus Rapid Eye Movement Sleep with Plasma Amyloid-Beta.

OBJECTIVE: Recent evidence shows that during slow-wave sleep (SWS), the brain is cleared from potentially toxic metabolites, such as the amyloid-beta protein. Poor sleep or elevated cortisol levels can worsen amyloid-beta clearance, potentially leading to the formation of amyloid plaques, a neuropathological hallmark of Alzheimer disease. Here, we explored how nocturnal neural and endocrine activity affects amyloid-beta fluctuations in the peripheral blood. METHODS: We acquired simultaneous polysomnography and all-night blood sampling in 60 healthy volunteers aged 20-68 years. Nocturnal plasma concentrations of amyloid-beta-40, amyloid-beta-42, cortisol, and growth hormone were assessed every 20 minutes. Amyloid-beta fluctuations were modeled with sleep stages, (non)oscillatory power, and hormones as predictors while controlling for age and participant-specific random effects. RESULTS: Amyloid-beta-40 and amyloid-beta-42 levels correlated positively with growth hormone concentrations, SWS proportion, and slow-wave (0.3-4Hz) oscillatory and high-band (30-48Hz) nonoscillatory power, but negatively with cortisol concentrations and rapid eye movement sleep (REM) proportion measured 40-100 minutes previously (all t values > |3|, p values < 0.003). Older participants showed higher amyloid-beta-40 levels. INTERPRETATION: Slow-wave oscillations are associated with higher plasma amyloid-beta levels, whereas REM sleep is related to decreased amyloid-beta plasma levels, possibly representing changes in central amyloid-beta production or clearance. Strong associations between cortisol, growth hormone, and amyloid-beta presumably reflect the sleep-regulating role of the corresponding releasing hormones. A positive association between age and amyloid-beta-40 may indicate that peripheral clearance becomes less efficient with age. ANN NEUROL 2024.

The role of ESAT-6 in tuberculosis immunopathology.

Despite major global efforts to eliminate tuberculosis, which is caused by Mycobacterium tuberculosis (Mtb), this disease remains as a major plague of humanity. Several factors associated with the host and Mtb interaction favor the infection establishment and/or determine disease progression. The Early Secreted Antigenic Target 6 kDa (ESAT-6) is one of the most important and well-studied mycobacterial virulence factors. This molecule has been described to play an important role in the development of tuberculosis-associated pathology by subverting crucial components of the host immune responses. This review highlights the main effector mechanisms by which ESAT-6 modulates the immune system, directly impacting cell fate and disease progression.

Spatio-Temporal Analysis and Clinical-Epidemiological Characterization of Visceral Leishmaniasis in Maranhão, Brazil, from 2009 to 2020.

This study was carried out to identify the spatial distribution and characterize the clinical-epidemiological profile of Visceral Leishmaniasis (VL) in Maranhão state, Brazil, from 2009 to 2020. This descriptive ecological study collected sociodemographic and clinical data of VL cases from the Brazilian Notifiable Diseases Information System database. A spatial autocorrelation analysis (Moran statistics) was performed. From 2009 to 2020, 5699 cases of VL were reported, with incidence of 6.5 cases/100,000 and prevalence of 7.1 cases/100,000. The temporal analysis showed a significant growth in incidence from 2009 to 2018, followed by a significant decrease between 2019 and 2020. The Moran map shows hotspots of high values in the central-west and central-east regions, and hotspots of low values in the northern region of Maranhão. The profile of patients affected by VL comprises males (OR = 1.8; IC95% = 1.72-1.92), aged under 14 years, brown, and with incomplete elementary schooling. The main symptoms reported were fever, fatigue, and edema. The main diagnostic method was laboratory. The mortality rate was 6.8%, and co-infection with HIV was reported by 8.5% of patients. The results of this study indicated the increase in incidence and lethality, as well as the expansion, of leishmaniasis in the state of Maranhão.

Evaluation of the Antiproliferative Potential of Yellow Jaboticaba (Myrciaria glazioviana) Extracts Against Human Cervical Cancer (HeLa cells line) and the Analysis of Their Chemical Composition by HPLC-HRESIMS.

Cervical cancer is a specific type of cancer that affects women around the world, with an incidence of 604 thousand new cases per year and 341 thousand deaths. There is a high demand for new effective antineoplastic drugs with few side effects. In this sense, recent research highlights the potential of compounds of natural origin in treating and preventing different types of cancer. Myrciaria glazioviana is a Brazilian native species belonging to the Myrtaceae family, which has previously described biological activities such as antimicrobial, anti-inflammatory, and antioxidant properties. This study aims to evaluate the anticancer activity of the dichloromethane extract (MGD) and ethyl acetate extract (MGA) of M. glazioviana leaves against human cervical cancer cell line (HeLa), as well as to identify their bioactive compounds. Using HPLC-HRESIMS technique, ten compounds were characterized in both samples: quinic acid, ellagic acid, Tri-O-methyl ellagic acid, two derivatives of Tetra-O-methyl flavellagic acid, quercetrin, Di-O-methyl ellagic acid, and three derivatives of pentamethyl coruleoellagic acid. Through MTT assays using HeLa cells and NIH/3T3 cells, it was observed that MGD and MGA were selective against tumor cells, with IC50 values of 24.31 and 12.62 µg/mL, respectively. The samples induced the tumor cell death by apoptosis, as evidenced by the activation of caspases 3/7, cell shrinkage, and pyknotic nuclei. Both samples were also able to inhibit the migration of HeLa cells after 24 hours of treatment, indicating a potential antimetastatic effect. Therefore, the present research highlights the antiproliferative and antimigratory potential of this species against HeLa cells.

Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare.

The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient's uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the "five rights": the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug-drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.

Exploring Darunavir, Rilpivirine and Etravirine as Potential Therapies for Bladder Cancer: Efficacy and Synergistic Effects.

This research explores the therapeutic efficacy of Darunavir (DRV), Rilpivirine (RPV), and Etravirine (ETV) against UM-UC-5 bladder cancer cells, addressing the critical need for innovative treatments in bladder cancer research. Through a comprehensive assessment of their individual and combined effects across diverse time intervals, ETV emerges as the most potent drug, with a lowest IC50 of 5.9 µM, closely followed by RPV (lowest IC50 of 9.6 µM), while DRV exhibits the least effectiveness (lowest IC50 of 25.6 µM). Notably, a significant synergistic effect is evident in the ETV and RPV combination, especially at 48 and 72 h for low concentrations. Synergies are also observed with ETV and DRV, albeit to a lesser extent and primarily at 48 h. Conversely, the DRV and RPV combination yields minimal effects, predominantly additive in nature. In summary, this pre-clinical investigation underscores the promising therapeutic potential of ETV and RPV, both as standalone treatments and in combination, hinting at repurposing opportunities in bladder cancer therapy, which could give a new treatment method for this disease that is faster and without as severe side effects as anticancer drugs. These findings represent a substantial stride in advancing personalized medicine within cancer research and will be further scrutinized in forthcoming studies.

The impact of ZIKV infection on gene expression in neural cells over time.

Zika virus (ZIKV) outbreak caused one of the most significant medical emergencies in the Americas due to associated microcephaly in newborns. To evaluate the impact of ZIKV infection on neuronal cells over time, we retrieved gene expression data from several ZIKV-infected samples obtained at different time point post-infection (pi). Differential gene expression analysis was applied at each time point, with more differentially expressed genes (DEG) identified at 72h pi. There were 5 DEGs (PLA2G2F, TMEM71, PKD1L2, UBD, and TNFAIP3 genes) across all timepoints, which clearly distinguished between infected and healthy samples. The highest expression levels of all five genes were identified at 72h pi. Taken together, our results indicate that ZIKV infection greatly impacts human neural cells at early times of infection, with peak perturbation observed at 72h pi. Our analysis revealed that all five DEGs, in samples of ZIKV-infected human neural stem cells, remained highly upregulated across the timepoints evaluated. Moreover, despite the pronounced inflammatory host response observed throughout infection, the impact of ZIKV is variable over time. Finally, the five DEGs identified herein play prominent roles in infection, and could serve to guide future investigations into virus-host interaction, as well as constitute targets for therapeutic drug development.

An integrative multi-omics approach to characterize interactions between tuberculosis and diabetes mellitus.

Tuberculosis-diabetes mellitus (TB-DM) is linked to a distinct inflammatory profile, which can be assessed using multi-omics analyses. Here, a machine learning algorithm was applied to multi-platform data, including cytokines and gene expression in peripheral blood and eicosanoids in urine, in a Brazilian multi-center TB cohort. There were four clinical groups: TB-DM(n = 24), TB only(n = 28), DM(HbA1c ≥ 6.5%) only(n = 11), and a control group of close TB contacts who did not have TB or DM(n = 13). After cross-validation, baseline expression or abundance of MMP-28, LTE-4, 11-dTxB2, PGDM, FBXO6, SECTM1, and LINCO2009 differentiated the four patient groups. A distinct multi-omic-derived, dimensionally reduced, signature was associated with TB, regardless of glycemic status. SECTM1 and FBXO6 mRNA levels were positively correlated with sputum acid-fast bacilli grade in TB-DM. Values of the biomarkers decreased during the course of anti-TB therapy. Our study identified several markers associated with the pathophysiology of TB-DM that could be evaluated in future mechanistic investigations.

Cisplatin Toxicity Causes Neutrophil-Mediated Inflammation in Zebrafish Larvae.

Cisplatin is an antineoplastic agent used to treat various tumors. In mammals, it can cause nephrotoxicity, tissue damage, and inflammation. The release of inflammatory mediators leads to the recruitment and infiltration of immune cells, particularly neutrophils, at the site of inflammation. Cisplatin is often used as an inducer of acute kidney injury (AKI) in experimental models, including zebrafish (Danio rerio), due to its accumulation in kidney cells. Current protocols in larval zebrafish focus on studying its effect as an AKI inducer but ignore other systematic outcomes. In this study, cisplatin was added directly to the embryonic medium to assess its toxicity and impact on systemic inflammation using locomotor activity analysis, qPCR, microscopy, and flow cytometry. Our data showed that larvae exposed to cisplatin at 7 days post-fertilization (dpf) displayed dose-dependent mortality and morphological changes, leading to a decrease in locomotion speed at 9 dpf. The expression of pro-inflammatory cytokines such as interleukin (il)-12, il6, and il8 increased after 48 h of cisplatin exposure. Furthermore, while a decrease in the number of neutrophils was observed in the glomerular region of the pronephros, there was an increase in neutrophils throughout the entire animal after 48 h of cisplatin exposure. We demonstrate that cisplatin can have systemic effects in zebrafish larvae, including morphological and locomotory defects, increased inflammatory cytokines, and migration of neutrophils from the hematopoietic niche to other parts of the body. Therefore, this protocol can be used to induce systemic inflammation in zebrafish larvae for studying new therapies or mechanisms of action involving neutrophils.

Severe combined immunodeficiency diagnosis and genetic defects.

Severe combined immunodeficiency (SCID) is a rare and life-threatening genetic disorder that severely impairs the immune system's ability to defend the body against infections. Often referred to as the "bubble boy" disease, SCID gained widespread recognition due to the case of David Vetter, a young boy who lived in a sterile plastic bubble to protect him from germs. SCID is typically present at birth, and it results from genetic mutations that affect the development and function of immune cells, particularly T cells and B cells. These immune cells are essential for identifying and fighting off infections caused by viruses, bacteria, and fungi. In SCID patients, the immune system is virtually non-existent, leaving them highly susceptible to recurrent, severe infections. There are several forms of SCID, with varying degrees of severity, but all share common features. Newborns with SCID often exhibit symptoms such as chronic diarrhea, thrush, skin rashes, and persistent infections that do not respond to standard treatments. Without prompt diagnosis and intervention, SCID can lead to life-threatening complications and a high risk of mortality. There are over 20 possible affected genes. Treatment options for SCID primarily involve immune reconstitution, with the most well-known approach being hematopoietic stem cell transplantation (HSCT). Alternatively, gene therapy is also available for some forms of SCID. Once treated successfully, SCID patients can lead relatively normal lives, but they may still require vigilant infection control measures and lifelong medical follow-up to manage potential complications. In conclusion, severe combined immunodeficiency is a rare but life-threatening genetic disorder that severely compromises the immune system's function, rendering affected individuals highly vulnerable to infections. Early diagnosis and appropriate treatment are fundamental. With this respect, newborn screening is progressively and dramatically improving the prognosis of SCID.

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil.

BACKGROUND: Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates. METHODS: We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to evaluate TB-ADR risk. RESULTS: There were 156 TB-ADRs among 102 of the 945 (11%) participants included. Most TB-ADRs were hepatic (n = 82 [53%]), of moderate severity (grade 2; n = 121 [78%]), and occurred in NAT2 slow acetylators (n = 62 [61%]). The main prediction model included CM use, HbA1c, alcohol use, HIV seropositivity, BMI, and age, with robust performance (c-statistic = 0.79 [95% confidence interval {CI}, .74-.83) and fit (optimism-corrected slope and intercept of -0.09 and 0.94, respectively). An alternative model replacing BMI with NAT2 had similar performance. HIV seropositivity (hazard ratio [HR], 2.68 [95% CI, 1.75-4.09]) and CM use (HR, 5.26 [95% CI, 2.63-10.52]) increased TB-ADR risk. CONCLUSIONS: The models, with clinical variables and with NAT2, were highly predictive of TB-ADRs.

The Xpert® MTB/RIF cycle threshold value predicts M. tuberculosis transmission to close contacts in a Brazilian prospective multicenter cohort.

BACKGROUND: The Xpert® MTB/RIF rapid molecular test provides a quantitative measure of Mycobacterium tuberculosis (Mtb) DNA in the form of cycle threshold (Ct) values. This information can be translated into mycobacterial load and used as a potential risk measure of bacterial spread for tuberculosis cases, which can impact infection control. However, the role of Ct values in assessing Mtb transmission to close contacts has not yet been demonstrated. METHODS: A prospective study was performed to investigate the association between Xpert® MTB/RIF Ct values and Mtb transmission to close contacts of patients with culture-confirmed pulmonary TB in a multi-center Brazilian cohort. We evaluated clinical and laboratory data, such as age, sex, race, smoking habits, drug use, alcohol use, chest radiograph, Xpert® MTB/RIF results among pulmonary tuberculosis cases, and QuantiFERON(QFT)-Plus results at baseline and after six months for close contacts who had a negative result at baseline. RESULTS: A total of 1,055 close contacts of 382 pulmonary tuberculosis cases were included in the study. The median Ct values from pulmonary tuberculosis cases of QFT-Plus positive (at baseline or six months) close contacts were lower compared with those who were QFT-Plus negative. An adjusted logistic regression demonstrated that reduced Ct values from the index cases were independently associated with QFT-Plus conversion from negative to positive (OR: 1.61, 95% CI: 1.12-2.32) after adjusting for clinical characteristics. CONCLUSION: Close contacts of pulmonary TB index cases exhibiting low Xpert MTB/RIF Ct values displayed higher rates of TB infection, reflecting Mtb transmission.

Isoniazid Monoresistance and Antituberculosis Treatment Outcome in Persons With Pulmonary Tuberculosis in Brazil.

Background: The high burden of drug-resistant tuberculosis (TB) is a problem to achieve the goals of the End TB Strategy by 2035. Whether isoniazid monoresistance (Hr) affects anti-TB treatment (ATT) outcomes remains unknown in high-burden countries. Methods: We evaluated determinants of ATT outcome among pulmonary TB cases reported to the National Notifiable Disease Information System (SINAN) between June 2015 and June 2019, according to drug sensitivity testing (DST) results. Binomial logistic regression models were employed to evaluate whether Hr was associated with an unfavorable ATT outcome: death or failure, compared to cure or treatment completion. Results: Among 60 804 TB cases reported in SINAN, 21 197 (34.9%) were included in the study. In this database, the frequency of unfavorable outcomes was significantly higher in those with Hr in contrast to isoniazid-sensitive persons with pulmonary TB (9.1% vs 3.05%; P < .001). Using a binomial logistic regression model, Hr was independently associated with unfavorable outcomes (odds ratio, 3.34 [95% confidence interval, 2.06-5.40]; P < .001). Conclusions: Hr detected prior to ATT was predictive of unfavorable outcomes at the national level in Brazil. Our data reinforce the need for high-TB-burden countries to prioritize DST to detect Hr. Effective treatment regimens for Hr-TB are needed to improve outcomes.

The sound of silent RNA in tuberculosis and the lncRNA role on infection.

Tuberculosis (TB) is one of the leading causes of death worldwide, and Diabetes Mellitus is one of the major comorbidities (TB/DM) associated with the disease. A total of 103 differentially expressed ncRNAs have been identified in the TB and TB/DM comparisons. A machine learning algorithm was employed to identify the most informative lncRNAs: ADM-DT, LINC02009, LINC02471, SOX2-OT, and GK-AS1. These lncRNAs presented substantial accuracy in classifying TB from HC (AUCs >0.85) and TB/DM from HC (AUCs >0.90) in the other three countries. Genes with significant correlations with the five lncRNAs enriched common pathways in Brazil and India for both TB and TB/DM. This suggests that lncRNAs play an important role in the regulation of genes related to the TB immune response.