Lung Tuberculosis Research Articles

ANALISIS KETAHANAN HIDUP PADA PENDERITA TUBERKULOSIS PARU-PARU MENGGUNAKAN METODE REGRESI COX PROPORTIONAL HAZARD

Lung Tuberculosis is a type of infectious disease caused by the Mycobacterium Tuberculosis bacteria that attacks the lungs. The source of transmission of this disease is a patient with pulmonary tuberculosis. Indonesia has the third highest number of tuberculosis sufferers after India and China. To find out the factors that affect the patient's long survival time, survival analysis can be used. This study uses the Cox Proportional Hazard Regression method because this method can be used to determine the magnitude of the relationship between the dependent and independent variables. The research data was obtained from data on Lung Tuberculosis patients at the Kajen II Public Health Center from January-December 2021. The dependent variable was the length of time they were treated until they experienced an incident (death). The independent variables consisted of age, gender, and history of taking medication (regular or irregular). Based on the results of the analysis, all independent variables had an effect on the dependent variable. The results obtained are that the age category of children is the most at risk of dying, the female sex is the most at risk, and patients with a history of taking irregular medication are the most at risk of dying.

EP.14C.01 Coexisting Pulmonary Tuberculosis and Primary Lung Cancer: Prevalence of Diagnostic, Treatment and Outcome

EP.14C.01 Coexisting Pulmonary Tuberculosis and Primary Lung Cancer: Prevalence of Diagnostic, Treatment and Outcome

Chronic Pulmonary Aspergillosis with Tracheobronchial Involvement

Introduction: Aspergillosis is a fungal infection commonly found in human lungs and takes several forms. Chronic pulmonary aspergillosis (CPA) commonly affects individuals with underlying disease, most usually lung tuberculosis (TB). Aspergillosis can cause the formation of a fungus ball in the lung cavity and can also manifest in the tracheobronchial area, although this is rarely seen in immunocompetent patients. Case: A 23-year-old woman came with persistent cough, hemoptysis, and shortness of breath for 4 months. The patient also had a significant weight loss and a history of lung TB 3 years ago. She had completed her lung TB medication. Physical examination showed increased respiratory rate and rhonchi on the left lung. GeneXpert showed no Mycobacterium tuberculosis (MTB) detected. The chest X-ray showed a cavity on the left superior lobe of the lung. Bronchoscopy showed multiple plaques along the trachea, carina, and left main bronchus. A chest computed tomography (CT) scan with contrast enhancement was performed, and a fungus ball was found inside the cavity in the left upper lobe of the lung. The patient was given intravenous fluconazole as therapy and continued with oral fluconazole when discharged. A second bronchoscopy was performed, and improvement was shown. Conclusion: Early detection and treatment should be applied to CPA patients since some studies showed poor prognosis and low five-year survival rates.

A STUDY ON PIRFENIDONE VERSUS NINTEDANIB IN PATIENTS WITH IDIOPATHIC PULMONARY FIBROSIS IN A TERTIARY CARE HOSPITAL: A CROSS SECTIONAL STUDY

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic condition with a poor prognosis and have an average life expectancy of 3-4 years. Two antifibrotic treatments have been approved to treat IPF: nintedanib and pirfenidone. These medications lower the decline in lung function and lower the risk of acute respiratory deterioration, which is linked with a high morbidity and death.Individual clinical trials have not been powered to demonstrate mortality decreases, however analysis of pooled data from clinical trials and observational research imply that anti-fibrotic drugs increase life expectancy. This study describes the utility of anti-fibrotic drugs and compare their efficacy. Methods and Materials: This 6 month cross-sectional study conducted at Santhiram Medical College and General Hospital in Nandyal.In patients with IPF , Clinical, functional and radiological data were gathered at baseline and during the follow-up, as per our Center procedure.This study compares and evaluates the efficacy of nintedanib and pirfenidone. A total of 40 patients over the age of 18 with IPF diagnosis were included. Patients under 18 years , those with known fibrosing lung diseases, bronchial asthma, COPD, HIV, Tuberculosis, or other organ failures were excluded. Results: At baseline, IPF patients treated with Pirfenidone had Forced vital capacity(FVC) and Forced expiratory volume at 1 second(FEV1) predicted percentages of 63.57 ± 8.34% and 72.31 ± 4.91%, respectively. In IPF patients treated with Nintedanib, at baseline(time 0), FVC and FEV1 percentages were 60.15±8.82% and 72.31±4.91% respectively. There were no significant variations in FVC and FEV1 percentages at time 0 between patients treated with the two medications (p=0.23,p=0.7,respectively). At 3-month follow-up, patients treated with Pirfenidone had predicted FVC and FEV1 values of 65.73 ± 7.84% and 72.94 ± 4.45%, respectively, whereas patients treated with Nintedanib had predicted valuesof 65.75 ± 7.67% and 72.42 ± 4.45%. At 6-month follow-up, patients on Pirfenidone had predicted FVC and FEV1 values of 66.9 ± 8.72% and 73.5 ± 4.50%, respectively. Nintedanib treatment resulted in 67.7±8.46% and 72.94±4.51% outcomes. Conclusion: our study shown that pirfenidone and nintedanib are equally effective at reducing FVC decline over a 6-month time frame.While nintedanib was slightly more beneficial in lowering FVC decline during the 6-month period. Both drugs were well tolerated, while nintedanib showing good tolerance in the majority of IPF patients.

Corrigendum: EGFR Mutation and FHIT Methylation: Inverse Relationship in Patients with Lung Adenocarcinoma and Tuberculosis

Correction The funding in the original publication (https://www.doi.org/10.26689/par.v8i2.6444) is incorrect. The original funding was: The Ethnic Minority Science and Technology Program of Xinjiang Autonomous Region (201523122) The correct funding should be as follows: This project was supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region (2020D01A107)

Primary Pre-Extensively Drug-Resistant (Pre-XDR) Tuberculosis with Meningoencephalitis in Nineteen Years Old Young Woman : A Case Report

Introduction. Mycobacterium tuberculosis (MTB) is continually evolving in order to resist treatment. This has resulted in drug-resistant tuberculosis, which has a greater rate of therapy failure and mortality, as well as the necessity for other ways of disease transmission prevention. Pre-extensively drug-resistant tuberculosis (Pre-XDR TB) is caused by MTB strains that are resistant to isoniazid, rifampicin, and any fluoroquinolone medicines. Case Report. A 19-year-old HIV-negative immunocompetent female presented to our emergency department with dyspnea and severe headache. She also complained of a cough, a low-grade temperature, and weight loss. She has no relevant medical history and has never been exposed to tuberculosis. A chest X-ray revealed infiltrates with cavities and fibrosis in both lungs, while a brain CT suggested meningoencephalitis. We performed a sputum drug sensitivity test and discovered that this patient was resistant to rifampin, isoniazid, levofloxacin, and moxifloxacin. She was later diagnosed with Pre-XDR TB and was given a tailored lengthier regimen that included Bedaquiline, Cycloserin, Linezolide, Clofazimine, and Etambutol. Her symptoms improved significantly as a result of this program. Discussion. Primary pre-XDR TB in an immunocompetent patient is uncommon, and our case is even more unusual due to meningoencephalitis involvement. The treatment of pre-XDR TB requires a personalized regimen that is tailored to the patient's clinical status and comorbidities. The possibility of transmission via a positive contact was raised in this patient, prompting us to conduct a more thorough contact inquiry to prevent future spread. Conclusion. In our region, there is a risk of'silent' drug resistant tuberculosis. Early detection and treatment of such patients are critical to preventing uncontrollable pan-resistant TB. Successful management with cautious contact investigation will minimize the mortality rate and spread rate of drug-resistant TB. Keywords. Drug-Resistant Lung Tuberculosis, Drug-Resistant Meningoencephalitis Tuberculosis

Fine mapping-based multi-omics analysis interprets the gut-lung axis function of SGLT2 inhibitors.

Currently, Sodium-glucose cotransporter 2 (SGLT2) inhibitors demonstrate additional effects beyond glucose control on the gut microbiota and circulating metabolites. The gut microbiota and metabolites have been found to be useful in elucidating potential biological mechanisms of pulmonary diseases. Therefore, our study aims to investigate the effects of gut microbiota and metabolites mediating SGLT2 inhibition in 10 pulmonary diseases through Mendelian randomization (MR) research. We conducted a two-sample, two-step MR study to assess the association between SGLT2 inhibition and 10 pulmonary diseases and to investigate the mediating effects of gut microbiota and metabolite. Gene-fine mapping and annotation of mediators by FUMA and Magma analyses were performed, and causal associations of mapped genes with diseases were assessed by muti-omics MR analyses. Possible side effects of SGLT2 inhibition were assessed by PheWAS analysis. SGLT2 inhibition was linked to a reduced risk of T2DM, Interstitial lung disease (ILD), Pneumoconiosis, Pulmonary tuberculosis, and Asthma(OR=0.457, 0.054, 0.002, 0.280, 0.706). The family Enterobacteriaceae and order Enterobacteriales were associated with SGLT2 inhibition and ILD(95% CI:0.079-0.138). The family Alcaligenaceae and X-12719 were linked to pneumoconiosis (95% CI: 0.042-0.120, 0.050-0.099). The genus Phascolarctobacterium was connected to pulmonary tuberculosis (95% CI: 0.236-0.703).The degree of unsaturation (Fatty Acids), ratio of docosahexaenoic acid to total fatty acids, and 4-androsten-3beta,17beta-diol disulfate 2, were associated with asthma(95% CI: 0.042-0.119, 0.039-0.101, 0.181-0.473). Furthermore, Fuma and Magma analyses identified target genes for the four diseases, and proteomic MR analysis revealed six overlapping target genes in asthma. PheWAS analysis also highlighted potential side effects of SGLT2 inhibition. This comprehensive study strongly supports a multi-omics association between SGLT2 inhibition and reduced risk of interstitial lung disease, tuberculosis, pneumoconiosis, and asthma. Four identified gut microbiota, four metabolites, sixteen metabolic pathways, and six target genes appear to play a potential role in this association. The results of the comprehensive phenome-wide association analysis also identified the full effect of SGLT2 inhibitors.

Frightening symptom hemoptysis: Analysis of etiology, mortality, and treatment outcomes in a large cohort from the chest disease center in Turkiye

Aims: Hemoptysis can indicate serious, potentially life-threatening conditions. The etiology varies by region and can include tuberculosis (TB) in developing countries and malignancies in developed regions. Methods: This retrospective cohort study reviewed medical records of 400 hospitalized hemoptysis patients between June 2012 and March 2016. Data collected included patient demographics, comorbidities, hemoptysis volume, diagnostic tests, treatments, and outcomes. Survival rates and readmissions were tracked for 2-6 years post-discharge. Results: Of the 400 patients, 88 (22%) were female and 312 (78%) were male. The leading causes of hemoptysis were bronchiectasis (14%), sequela of tuberculosis (TB sequelae; 19%), and malignancy (22.8%). The most common causes in male patients were lung cancer (27.2%) and TB sequelae (21.8%). Bronchiectasis accounted for 28.4% of cases in female patients, followed by drug-induced hemoptysis at 14.8%. The in-hospital mortality rate was 1% (n = 4), with severe hemoptysis present in all four patients who died during admission for hemoptysis. The 2–6-year survival rate was 70.8% for women and 56.1% for men (p = 0.005). The factors found to significantly worsen mortality risk were lung malignancy, age >65, diabetes, and chronic obstructive pulmonary disease (COPD). Conclusion: Overall, lung cancer was found to be the leading cause of hemoptysis, with bronchiectasis being the leading cause in female patients and malignancy in male patients. Close monitoring of male patients is crucial due to higher mortality risk. Careful assessment of patients with hemoptysis having comorbidities such as diabetes and COPD is required due to the reduced survival rates associated with these conditions. Early detection and intervention for lung cancer is essential to optimize the prognosis of affected individuals.

Permissive lung neutrophils facilitate tuberculosis immunopathogenesis in male phagocyte NADPH oxidase-deficient mice.

NADPH oxidase 2 (NOX2) is an enzyme responsible for generating reactive oxygen species, primarily found in phagocytes. Chronic Granulomatous Disease (CGD), along with bacterial infections such as Mycobacterium tuberculosis (Mtb), is a representative NOX2-deficient X-linked disease characterized by uncontrolled inflammation. However, the precise roles of host-derived factors that induce infection-mediated hyperinflammation in NOX2-deficient condition remain incompletely understood. To address this, we compared Mtb-induced pathogenesis in Nox2-/- and wild type (WT) mice in a sex-dependent manner. Among age- and sex-matched mice subjected to Mtb infection, male Nox2-/- mice exhibited a notable increase in bacterial burden and lung inflammation. This was characterized by significantly elevated pro-inflammatory cytokines such as G-CSF, TNF-α, IL-1α, IL-1β, and IL-6, excessive neutrophil infiltration, and reduced pulmonary lymphocyte levels as tuberculosis (TB) progressed. Notably, lungs of male Nox2-/- mice were predominantly populated with CD11bintLy6GintCXCR2loCD62Llo immature neutrophils which featured mycobacterial permissiveness. By diminishing total lung neutrophils or reducing immature neutrophils, TB immunopathogenesis was notably abrogated in male Nox2-/- mice. Ultimately, we identified G-CSF as the pivotal trigger that exacerbates the generation of immature permissive neutrophils, leading to TB immunopathogenesis in male Nox2-/- mice. In contrast, neutralizing IL-1α and IL-1β, which are previously known factors responsible for TB pathogenesis in Nox2-/- mice, aggravated TB immunopathogenesis. Our study revealed that G-CSF-driven immature and permissive pulmonary neutrophils are the primary cause of TB immunopathogenesis and lung hyperinflammation in male Nox2-/- mice. This highlights the importance of quantitative and qualitative control of pulmonary neutrophils to alleviate TB progression in a phagocyte oxidase-deficient condition.

Prior tuberculosis, radiographic lung abnormalities and prevalent diabetes in rural South Africa

BackgroundGrowing evidence suggests that chronic inflammation caused by tuberculosis (TB) may increase the incidence of diabetes. However, the relationship between post-TB pulmonary abnormalities and diabetes has not been well characterized.MethodsWe analyzed data from a cross-sectional study in KwaZulu-Natal, South Africa, of people 15 years and older who underwent chest X-ray and diabetes screening with hemoglobin A1c testing. The analytic sample was restricted to persons with prior TB, defined by either (1) a self-reported history of TB treatment, (2) radiologist-confirmed prior TB on chest radiography, and (3) a negative sputum culture and GeneXpert. Chest X-rays of all participants were evaluated by the study radiologist to determine the presence of TB lung abnormalities. To assess the relationships between our outcome of interest, prevalent diabetes (HBA1c ≥6.5%), and our exposure of interest, chest X-ray abnormalities, we fitted logistic regression models adjusted for potential clinical and demographic confounders. In secondary analyses, we used the computer-aided detection system CAD4TB, which scores X-rays from 10 to 100 for detection of TB disease, as our exposure interest, and repeated analyses with a comparator group that had no history of TB disease.ResultsIn the analytic cohort of people with prior TB (n = 3,276), approximately two-thirds (64.9%) were women, and the average age was 50.8 years (SD 17.4). The prevalence of diabetes was 10.9%, and 53.0% of people were living with HIV. In univariate analyses, there was no association between diabetes prevalence and radiologist chest X-ray abnormalities (OR 1.23, 95%CI 0.95–1.58). In multivariate analyses, the presence of pulmonary abnormalities was associated with an 29% reduction in the odds of prevalent diabetes (aOR 0.71, 95%CI 0.53–0.97, p = 0.030). A similar inverse relationship was observed for diabetes with each 10-unit increase in the CAD4TB chest X-ray scores among people with prior TB (aOR 0.92, 95%CI 0.87–0.97; p = 0.002), but this relationship was less pronounced in the no TB comparator group (aOR 0.96, 95%CI 0.94–0.99).ConclusionsAmong people with prior TB, pulmonary abnormalities on digital chest X-ray are inversely associated with prevalent diabetes. The severity of radiographic post-TB lung disease does not appear to be a determinant of diabetes in this South African population.

B cells in perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell signatures identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice.

Because most humans resist Mycobacterium tuberculosis infection, there is a paucity of lung samples to study. To address this gap, we infected Diversity Outbred mice with M. tuberculosis and studied the lungs of mice in different disease states. After a low-dose aerosol infection, progressors succumbed to acute, inflammatory lung disease within 60 days, while controllers maintained asymptomatic infection for at least 60 days, and then developed chronic pulmonary tuberculosis (TB) lasting months to more than 1 year. Here, we identified features of asymptomatic M. tuberculosis infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., Bank1, Cd19, Cd79, Fcmr, Ms4a1, Pax5, and H2-Ob), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic M. tuberculosis infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.

The Coronavirus Disease 2019 Pandemic and Time to Diagnosis for Childhood Pulmonary Diseases: Outcomes of a Tertiary Care Center.

Coronavirus disease 2019 pandemic caused many changes in the social behaviors of individuals and the provision of health systems. Many studies revealed reductions in the number of diagnoses and delays in diagnosis time during the pandemic. This study aimed to evaluate the effect of the pandemic on the time to diagnosis of major diseases of pediatric pulmonology. Newly diagnosed patients with cystic fibrosis (CF), childhood interstitial lung disease (chILD), tuberculosis (TB), and primary ciliary dyskinesia (PCD) were grouped into pandemic (group 1) and 2 consecutive pre-pandemic periods divided into equal intervals (groups 2 and 3). For each disease group, the time to diagnosis was compared between the specified periods. A total number of patients were 171 in this study. In the CF group, there was no statistically difference in time to diagnosis between periods. In the chILD group, there was a statistically significant difference in time to diagnosis (P = .036) between groups (group 1: 2 months, group 2: 4 months and group 3: 10.5 months) that was not originated from pandemic period. In TB group there was no statistically significant difference between groups. In the PCD group, the impact of the pandemic on the time to diagnosis could not be clarified because the time interval to diagnosis (minimum: 2 years, maximum: 16 years) exceeded the studied periods (21 months). In our study, no effect found between the pandemic and age at diagnosis or time to diagnosis in patients with PCD, chILD, CF, and TB at our center.

Implementation Transfer Learning on Convolutional Neural Network for Tubercolosis Classification

Tuberculosis (TB) is an infectious disease that can have serious effects on the lungs and is among the top 10 causes of death worldwide. This disease is caused by the transmission of Mycobacterium tuberculosis bacteria through the air when coughing or sneezing. Without treatment, pulmonary tuberculosis can result in permanent lung damage and can be life-threatening. Accurate and early diagnosis is crucial for effective treatment and control of the disease.The challenge lies in the accurate classification of tuberculosis from lung images, which is essential for timely diagnosis and treatment. Traditional diagnostic methods can be time-consuming and sometimes lack precision. To address this issue, this research aims to achieve high accuracy in classifying tuberculosis using the Convolutional Neural Network (CNN) algorithm through transfer learning methods. By utilizing visual images of tuberculosis-affected and normal lungs, we propose a solution that leverages advanced deep learning techniques to enhance diagnostic accuracy. This approach not only expedites the diagnostic process but also improves the reliability of tuberculosis detection, ultimately contributing to better patient outcomes and more effective disease management. The dataset applied consists of two labels: tuberculosis and normal. This dataset contains 4200 lung images of individuals with tuberculosis and normal lungs. By applying the transfer learning method, Transfer learning is a machine learning method where a pre-trained model is used as the starting point for a new, related task. it was found that the ResNet50 model achieved the highest accuracy at 99%, followed by InceptionV3 at 97%, and lastly, DenseNet121 at 91%.

Comparative study on conventional diagnostic methods with GeneXpert and TrueNat Mycobacterium tuberculosis (MTB) assay of tuberculosis disease

Abstract Background: Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, primarily affecting the lungs. While pulmonary TB (PTB) is the most prevalent form, comprising the majority of cases, extrapulmonary TB (EPTB) presents unique diagnostic and therapeutic challenges. TB spreads through the air when individuals with lung TB cough, sneeze, or spit. Aim: We aim to conduct a comprehensive comparative analysis of molecular diagnostic methods versus conventional techniques for detecting PTB. Results: Among 1100 samples analyzed, 384 cases (34.90%) of TB were identified, encompassing both pulmonary and extrapulmonary forms. The highest number of samples was collected from individuals aged 21–40, 41–60, and 61–80 years. In particular, 70 out of 114 pus samples (61.40%) tested positive for EPTB. In contrast, only 5 out of 79 pleural fluid samples (6.33%) and 16 out of 32 lymph node samples (50%) tested positive for EPTB. Conclusion: These findings highlight the critical need for ongoing research and the development of accurate, sensitive, and accessible diagnostic methods to combat TB effectively. PTB was observed to be more prevalent, affecting a larger proportion of individuals, while EPTB accounted for a smaller, though significant, number of cases.

Analysis of Oral Albumin Use and Factors Affecting the Success of its Therapy

Hypoalbuminemia is a risk factor for medical treatment. Albumin has been shown to be a predictor in a number of studies in various settings. Several studies examined albumin as a marker of nutritional status and its association with outcomes (eg, mortality and length of hospital stay). In critical illness, the Acute Physiology and Chronic Health Evaluation (APACHE III) risk score includes serum albumin levels and shows a strong inverse correlation between serum albumin and mortality in critically ill patients. This research was conducted observationally to analyze the use of oral albumin and the factors that influence the success of therapy in the Lung Inpatient Room at Dr Soetomo Regional Hospital for the period 1 January – 31 October 2022. Patients diagnosed with Community Pneumonia, Lung Cancer and Lung Tuberculosis. This research was carried out by collecting secondary data via e-medical records. Data taken were patient demographic data (name, gender, weight, age, length of stay) and albumin data before and after receiving oral albumin. From the research results, the number of samples was 87. The number of samples was 87 patients. Of the 87 patients, 66 male patients (75.86%) were 21 female patients (24.14%), the largest age range was 51 - 60 years, 21 patients (24.14%). The highest body weight ranged from 61-70 kg for 50 patients (57.47%), the longest length of stay ( Length of Stay ) was 10-20 days for 45 patients (51.72%). The most common primary diagnosis was new tuberculosis in 42 patients (48.28%). The highest use of oral albumin was more than 100 capsules, as many as 20 patients (22.99%) with the highest duration of use being 10-19 days, namely 38 patients (43.68%). The statistical results show that there is no significant difference between before receiving oral albumin and after receiving oral albumin with a value of P = 0.541. Factors that influence the success of oral albumin therapy are length of stay with a value of P = 0.001 * Keywords: Oral albumin, pulmonary tuberculosis, lung cancer, pneumonia, length of stay

Advanced Lung Disease Detection and Classification Using Ge-U-Net-ODLwith Gabor Filters and Entropy-Based Feature Selection

Lung X-ray images play a crucial role in the detection and diagnosis of various lung diseases,including pneumonia, tuberculosis, and lung cancer. These images provide a non-invasive method for visualizing lung structures, allowing radiologists and machine learning models to identify abnormalities such as nodules, masses, or fluid accumulation. With the advancement of deep learning techniques, lung X-ray images are now used in automated systems that can detect and classify diseases with high accuracy. By applying sophisticated algorithms like GE-U-Net-ODL, Gabor filters, and entropy-based feature extraction, these images are analyzed pixel by pixel to enhance feature representation and improve diagnostic precision. This paper presents a novel approach for lung disease detection and classification using the GE-U-Net-ODL model, which integrates advanced preprocessing techniques and deep learning architectures. The study leverages the NIH Chest X-ray dataset and employs a variety of feature extraction and selection methods, including Gabor filters, entropy-based techniques, and multi-scale inputs. A detailed comparative analysis of different model configurations demonstrates that the GE-U-Net-ODL model with Transfer Learning achieves the highest classification accuracy of 95.0%, alongside superior precision (93.5%), recall (94.0%), and F1-score (93.7%). Other configurations, such as those utilizing data augmentation and hybrid filters, also showed notable performance improvements. The research underscores the model's effectiveness in enhancing diagnostic accuracy for lung diseases while balancing training and inference times.

Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs.

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients' chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model's input requirements, we enhanced them through data augmentation techniques for training purposes. We evaluated the model's performance by analyzing the precision, recall, and F1 scores across training, validation, and testing datasets. The results show that the ResNet50 model outperformed VGG16 with accuracy and resilience. It displayed superior ROC AUC values in both validation and test scenarios. Particularly impressive were ResNet50's precision and recall rates, nearing 0.99 for all conditions in the test set. On the hand, VGG16 also performed well during testing-detecting tuberculosis with a precision of 0.99 and a recall of 0.93. Our study highlights the performance of our deep learning method by showcasing the effectiveness of ResNet50 over traditional approaches like VGG16. This progress utilizes methods to enhance classification accuracy by augmenting data and balancing them. This positions our approach as an advancement in using state-of-the-art deep learning applications in imaging. By enhancing the accuracy and reliability of diagnosing ailments such as COVID-19 and tuberculosis, our models have the potential to transform care and treatment strategies, highlighting their role in clinical diagnostics.

The Influence of Body Fat Dynamics on Pulmonary Immune Responses in Murine Tuberculosis: Unraveling Sex-Specific Insights.

The World Health Organization (WHO) highlights a greater susceptibility of males to tuberculosis (TB), a vulnerability attributed to sex-specific variations in body fat and dietary factors. Our study delves into the unexplored terrain of how alterations in body fat influence Mycobacterium tuberculosis (Mtb) burden, lung pathology, immune responses, and gene expression, with a focus on sex-specific dynamics. Utilizing a low-dose Mtb-HN878 clinical strain infection model, we employ transgenic FAT-ATTAC mice with modulable body fat to explore the impact of fat loss (via fat ablation) and fat gain (via a medium-fat diet, MFD). Firstly, our investigation unveils that Mtb infection triggers severe pulmonary pathology in males, marked by shifts in metabolic signaling involving heightened lipid hydrolysis and proinflammatory signaling driven by IL-6 and localized pro-inflammatory CD8+ cells. This stands in stark contrast to females on a control regular diet (RD). Secondly, our findings indicate that both fat loss and fat gain in males lead to significantly elevated (1.6-fold (p ≤ 0.01) and 1.7-fold (p ≤ 0.001), respectively) Mtb burden in the lungs compared to females during Mtb infection (where fat loss and gain did not alter Mtb load in the lungs). This upsurge is associated with impaired lung lipid metabolism and intensified mitochondrial oxidative phosphorylation-regulated activity in lung CD8+ cells during Mtb infection. Additionally, our research brings to light that females exhibit a more robust systemic IFNγ (p ≤ 0.001) response than males during Mtb infection. This heightened response may either prevent active disease or contribute to latency in females during Mtb infection. In summary, our comprehensive analysis of the interplay between body fat changes and sex bias in Mtb infection reveals that alterations in body fat critically impact pulmonary pathology in males. Specifically, these changes significantly reduce the levels of pulmonary CD8+ T-cells and increase the Mtb burden in the lungs compared to females. The reduction in CD8+ cells in males is linked to an increase in mitochondrial oxidative phosphorylation and a decrease in TNFα, which are essential for CD8+ cell activation.

Safety of nivolumab monotherapy in five cancer types: pooled analysis of post-marketing surveillance in Japan

BackgroundNivolumab has been approved for treating ≥ 10 cancer types. However, there is limited information on the incidence of rare, but potentially serious, treatment-related adverse events (TRAEs), as well as notable TRAEs in patients with certain medical disorders or older patients in Japan.MethodsWe performed pooled analyses of data from published post-marketing surveillance in Japan of nivolumab monotherapy for patients with malignant melanoma, non-small cell lung cancer, renal cell carcinoma, head and neck cancer, and gastric cancer to determine the frequencies of 20 categories of TRAEs of special interest overall and in patient groups with higher perceived safety risks (history of autoimmune disease, interstitial lung disease, tuberculosis, or hepatitis B/C; patients vaccinated during nivolumab treatment; and older patients [≥ 75 years]).ResultsThe overall population comprised 7421 patients treated with nivolumab. TRAEs were reported in 49.1% of patients, with grade ≥ 3 TRAEs in 16.7%. Endocrine disorders (14.4%), hepatobiliary disorders (10.9%), and interstitial lung disease (7.0%) were the three most common categories (any grade). The incidences of rare TRAEs with high risk of becoming serious, which occurred in < 1% of patients, were consistent with those in previous reports. The frequencies of TRAEs were not markedly increased in the specified patient groups relative to the overall population.ConclusionTo our knowledge, this is the largest study examining the safety of nivolumab-treated patients in real-world clinical practice including rare but potentially serious TRAEs. We found no new signals in the safety of nivolumab among the patient groups relative to the overall population, and no additional safety measures are required in these groups.Trial registration UMIN000048892 (overall analysis), JapicCTI-163272 (melanoma), Japic-163271 (non-small cell lung cancer), JapicCTI-184071 (head and neck cancer), JapicCTI-184070 (gastric cancer), and JapicCTI-184069 (renal cell cancer).

Clinical course of respiratory tuberculosis relapses in the Kazakh population depending on HLA-DRB1 gene alleles.

The study aimed to ascertain the prevalence and frequency of relapses of respiratory tuberculosis (TB) and examine the characteristics of its clinical progression in members of the Kazakh population based on the alleles of the HLA-DRB1 gene. Methods of clinical and genetic research, statistical processing and analysis of the obtained data were used to achieve this goal. The research led to an analysis of the statistical processing of clinical and genetic investigations that found out how often TB in the respiratory tract is found and how different HLA-DRB1 gene alleles affect the disease's progression. To find out how exposure to certain HLA-DRB1 gene alleles affects the chance of relapse, the number of times they were found was compared between people who had relapsed and people who had just been diagnosed with TB. The impact of these alleles on the progression of the disease was assessed based on their frequency of detection of different clinical forms of TB (infiltrative, fibro-cavernous, generalised, disseminated), unilateral and bilateral lung damage, lung tissue deterioration, and the presence of bacterial secretions. The highest detection rate for all comparisons had gene alleles HLA-DRB1*01 (9.5%), *08 (4.2%), *15 (3.9%), *09 (1.6%), *12 (1.3%), *13 (0.9%), *11 (0.2%). The study found that Kazakhs with the HLA-DRB1*01, *08, and 15 gene alleles are more likely to develop recurrent respiratory TB. The study's practical value lies in its potential to utilise its findings for the prompt identification and eradication of genetic variables contributing to the recurrence of TB.