Lung epithelial cells interact with immune cells and bacteria to shape the microenvironment in tuberculosis

The lung epithelium has long been overlooked as a key player in tuberculosis disease. In addition to acting as a direct barrier to Mycobacterium tuberculosis (Mtb), epithelial cells (EC) of the airways and alveoli act as first responders during Mtb infections; they directly sense and respond to Mtb by producing mediators such as cytokines, chemokines and antimicrobials. Interactions of EC with innate and adaptive immune cells further shape the immune response against Mtb. These three essential components, epithelium, immune cells and Mtb, are rarely studied in conjunction, owing in part to difficulties in coculturing them. Recent advances in cell culture technologies offer the opportunity to model the lung microenvironment more closely. Herein, we discuss the interplay between lung EC, immune cells and Mtb and argue that modelling these interactions is of key importance to unravel early events during Mtb infection.

SISTEM INFORMASI GEOGRAFIS SEBARAN PENYAKIT TUBERKULOSIS DI KECAMATAN PANINGGARAN KABUPATEN PEKALONGAN BERBASIS ANDROID

Tuberculosis is an infectious disease that can infect one person to another caused by the bacterium Mycobacterium tuberculosis. This disease is not only transmitted to people of productive age (15-45), but teenagers or children under 15 years can also be infected with the bacteria. Every year new cases are found in Indonesia, such as in the work area of the Paninggaran Health Center, Paninggaran District. Public Health Centers and Hospitals are health facilities for the community that have the facilities and infrastructure to determine how large the coverage of health figures for the community is. From this analysis, it can be found the obstacles that must be faced, namely how to provide information to the public about the spread of Tuberculosis in Paninggaran District. This is what underlies this research to create an Android-based Geographic Information System application for the distribution of tuberculosis in Paninggaran District with menus that are useful for the wider community and easy to use. The method used in this research is the Waterfall Method. The final result of this study is a "Geographical Information System for the Distribution of Tuberculosis in Paninggaran District" in the form of an android application for the community and a website for admins, namely Paninggaran Health Center officers, so that it can facilitate the distribution of information about Tuberculosis to the community and related health services, this application can also displays a map of the distribution of Tuberculosis disease, the location of where Tuberculosis patients live, the number of Tuberculosis case data and educational news about Tuberculosis disease.

Stability Analysis of SEIL Tuberculosis Epidemic Model with Logistic Growth in Susceptible Compartment

This article discusses modifications to the SEIL model that involve logistical growth. This model is used to describe the dynamics of the spread of tuberculosis disease in the population. The existence of the model's equilibrium points and its local stability depends on the basic reproduction number. If the basic reproduction number is less than unity, then there is one equilibrium point that is locally asymptotically stable. The equilibrium point is a disease-free equilibrium point. If the basic reproduction number ranges from one to three, then there are two equilibrium points. The two equilibrium points are disease-free equilibrium and endemic equilibrium points. Furthermore, for this case, the endemic equilibrium point is locally asymptotically stable.

Pulmonary tuberculosis diagnosis, differentiation and disease management: A review of radiomics applications

Pulmonary tuberculosis is a worldwide epidemic that can only be fought effectively with early and accurate diagnosis and proper disease management. The means of diagnosis and disease management should be easily accessible, cost effective and be readily available in the high tuberculosis burdened countries where it is most needed. Fortunately, the fast development of computer science in recent years has ensured that medical images can accurately be quantified. Radiomics is one such tool that can be used to quantify medical images. This review article focuses on the literature currently available on the application of radiomics explicitly for the purpose of diagnosis, differentiation from other pulmonary diseases and disease management of pulmonary tuberculosis. Despite using a formal search strategy, only five articles could be found on the application of radiomics to pulmonary tuberculosis. In all five articles reviewed, radiomic feature extraction was successfully used to quantify digital medical images for the purpose of comparing, or differentiating, pulmonary tuberculosis from other pulmonary diseases. This demonstrates that the use of radiomics for the purpose of tuberculosis disease management and diagnosis remains a valuable data mining opportunity not yet realised.

Previous tuberculosis disease as a risk factor for chronic obstructive pulmonary disease: a cross-sectional analysis of multicountry, population-based studies

BackgroundRisk factors for COPD in high-income settings are well understood; however, less attention has been paid to contributors of COPD in low-income and middle-income countries (LMICs) such as pulmonary tuberculosis. We sought to study the association between previous tuberculosis disease and COPD by using pooled population-based cross-sectional data in 13 geographically diverse, low-resource settings.MethodsWe pooled six cohorts in 13 different LMIC settings, 6 countries and 3 continents to study the relationship between self-reported previous tuberculosis disease and lung function outcomes including COPD (defined as a postbronchodilator forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) below the lower limit of normal). Multivariable regressions with random effects were used to examine the association between previous tuberculosis disease and lung function outcomes.ResultsWe analysed data for 12 396 participants (median age 54.0 years, 51.5% male); 332 (2.7%) of the participants had previous tuberculosis disease. Overall prevalence of COPD was 8.8% (range 1.7%–15.5% across sites). COPD was four times more common among those with previous tuberculosis disease (25.7% vs 8.3% without previous tuberculosis disease, p<0.001). The adjusted odds of having COPD was 3.78 times higher (95% CI 2.87 to 4.98) for participants with previous tuberculosis disease than those without a history of tuberculosis disease. The attributable fraction of COPD due to previous tuberculosis disease in the study sample was 6.9% (95% CI 4.8% to 9.6%). Participants with previous tuberculosis disease also had lower prebronchodilator Z-scores for FEV1 (−0.70, 95% CI −0.84 to −0.55), FVC (−0.44, 95% CI −0.59 to −0.29) and the FEV1:FVC ratio (−0.63, 95% CI −0.76 to −0.51) when compared with those without previous tuberculosis disease.ConclusionsPrevious tuberculosis disease is a significant and under-recognised risk factor for COPD and poor lung function in LMICs. Better tuberculosis control will also likely reduce the global burden of COPD.

3D Atom based QSAR model of DprE1 inhibitors as Anti-tubercular Agents

Tuberculosis disease is world’s biggest threat to health with a high mortality rate. There has been a steady surge in the frequency of MDR-TB and XDR-TB. Hence, it is imperative to encourage the research and development of novel drugs to counteract the infection. Decaprenylphosphoryl-ß-D-ribose-2'α-epimerase 1 (DprE1) is a valuable enzyme which is responsible for the stability and virulence of the infection causing bacteria (Mycobacterium tuberculosis) thereby making it a perfect target for drugs anti TB activity. This study represent atom based 3D QSAR model consisting the derivatives of DprE1 inhibitors and provides guidance and insight to develop and identify new novel molecule which have good therapeutic efficiency as Anti TB drugs.