Distribution of common and rare drug resistance patterns in Mycobacterium tuberculosis clinical isolates revealed by GenoType MTBDRplus and MTBDRsl assay.

Background: Tuberculosis (TB) remains a significant global health emergency caused by Mycobacterium tuberculosis (Mtb). The epidemiology, transmission, genotypes, mutational patterns, and clinical consequences of TB have been extensively studied worldwide, however, there is a lack of information regarding the epidemiology and mutational patterns of Mtb in Pakistan, specifically concerning the prevalence of multi-drug resistant TB (MDR-TB). Methods: This study aimed to investigate the incidence of Mtb and associated mutational patterns using the line probe assay (LPA). Previous studies have reported a high frequency of mutations in the rpoB, inhA, and katG genes, which are associated with resistance to rifampicin (RIF) and isoniazid (INH). Therefore, the current study utilized LPA to detect mutations in the rpoB, katG, and inhA genes to identify multi-drug resistant Mtb. Results: LPA analysis of a large pool of Mtb isolates, including samples from 241 sputum-positive patients, revealed that 34.85% of isolates were identified as MDR-TB, consistent with reports from various regions worldwide. The most prevalent mutations observed were rpoB S531L and inhA promoter C15T, which were associated with resistance to RIF and INH, respectively. Conclusions: This study highlights the effectiveness of GenoType MTBDRplus and MTBDRsl assays as valuable tools for TB management. These assays enable rapid detection of resistance to RIF, INH, and fluoroquinolones (FQs) in Mtb clinical isolates, surpassing the limitations of solid and liquid media-based methods. The findings contribute to our understanding of MDR-TB epidemiology and provide insights into the genetic profiles of Mtb in Pakistan, which are essential for effective TB control strategies.

A Rare Case of Multidrug-Resistant Tuberculosis Affecting the Pleura.

The majority of cases with tuberculous pleuritis have negative acid-fast bacilli (AFB) on smear microscopy, making the diagnosis difficult. This case report is based on the successful diagnosis and management of an extra-pulmonary (EP) multidrug-resistant tuberculosis (MDR-TB) patient with a history of lymphoma. Initial tests revealed a right-sided pleural effusion and thickening of the pleura. The closed pleural biopsy, pleural fluid histopathology, culture, and drug sensitivity testing (DST) report revealed Mycobacterium tuberculosis with isoniazid and rifampicin resistance. Based on the DST report, the patient was labeled as a case of MDR-TB and successfully managed with an individualized drug-resistant TB (DR-TB) regimen. With initial negative microscopy and GeneXpert MTB/RIF (Sunnyvale, CA: Cepheid Inc.) reports, this case demonstrated that DR-TB could exist even in the absence of risk factors. Furthermore, it also unveils the importance of line probe assays (LPAs) and culture in identifying MDR-TB. Lymphocytic/exudative pleural effusions and pleural biopsy specimens should be subjected early on to investigations like Xpert/MTB RIF, cultures, and genotypic DST to timely diagnose and treat DR-TB.

Prediction of Multidrug-Resistant Tuberculosis Using Machine Learning Algorithms in SWAT, Pakistan.

In this paper, we have focused on machine learning (ML) feature selection (FS) algorithms for identifying and diagnosing multidrug-resistant (MDR) tuberculosis (TB). MDR-TB is a universal public health problem, and its early detection has been one of the burning issues. The present study has been conducted in the Malakand Division of Khyber Pakhtunkhwa, Pakistan, to further add to the knowledge on the disease and to deal with the issues of identification and early detection of MDR-TB by ML algorithms. These models also identify the most important factors causing MDR-TB infection whose study gives additional insights into the matter. ML algorithms such as random forest, k-nearest neighbors, support vector machine, logistic regression, leaset absolute shrinkage and selection operator (LASSO), artificial neural networks (ANNs), and decision trees are applied to analyse the case-control dataset. This study reveals that close contacts of MDR-TB patients, smoking, depression, previous TB history, improper treatment, and interruption in first-line TB treatment have a great impact on the status of MDR. Accordingly, weight loss, chest pain, hemoptysis, and fatigue are important symptoms. Based on accuracy, sensitivity, and specificity, SVM and RF are the suggested models to be used for patients' classifications.

Combined treatment of sinapic acid and ellagic acid attenuates hyperglycemia in streptozotocin-induced diabetic rats.

In the present study, we aimed to investigate the effect of individual and combined treatment of sinapic acid (SA) and ellagic acid (EA) in streptozotocin (STZ)-induced diabetic rats. Rats were divided into eight groups (n = 7): Normal Control, Diabetic Control, Diabetic + Sinapic Acid, Diabetic + Ellagic Acid, Diabetic + Sinapic Acid + Ellagic Acid, Sinapic Acid, Ellagic Acid and Sinapic Acid + Ellagic Acid. Diabetic groups were injected with a single dose of 50 mg/kg STZ intraperitoneally. Rats received 20 mg/kg/day SA and 50 mg/kg/day EA intragastrically for 28 days. The numerical density of immunopositive ß-cells and volume density of pancreatic islets were calculated. Additionally, glucose and insulin levels in serum, MDA, GSH, and CAT levels of pancreatic tissue were measured. While serum glucose levels increased, serum insulin levels decreased in STZ-induced diabetic rats. But these changes in glucose and insulin were restored by individual and combined treatments of SA and EA. Also, individual and combined treatments of SA and EA increased insulin expression of ß-cells in STZ-induced diabetic rats. Moreover, these compounds improved deteriorating oxidative stress parameters in STZ-induced diabetic rats. Our study indicates that SA and EA, especially their combined treatments, can be used as an antihyperglycemic agent in diabetes.

The prevalence of atrial fibrillation among acute medical admissions in Kuwait.

OBJECTIVE: To establish the prevalence of atrial fibrillation (AF) among acute medical admissions to the Adan Hospital, Kuwait, and to evaluate the clinical features of the patients. SUBJECTS AND METHODS: Of 2,833 acute medical admissions to the Adan Hospital from January 1 to May 31, 2003, 120 patients with AF were included in the study. The patients were divided into paroxysmal or persistent (PPAF), and chronic atrial fibrillation (CAF). The prevalence of stroke and clinical features of the CAF patients with and without strokes were studied. All the patients with AF underwent echocardiography to evaluate left ventricular ejection fraction (LVEF) and left atrial dimension (LAD). RESULTS: The prevalence of AF in the study period was 4.24%, of which 68.3% had CAF and 31.7% had PPAF. The prevalence of heart failure, ischemic heart disease, systemic hypertension, and diabetes mellitus was 27.5, 55.8, 65.8, and 53.3%, respectively. Patients with CAF were older and had a higher prevalence of heart failure compared to PPAF patients. Of the patients with CAF, 26.8% had at least one episode of stroke. The CAF patients had lower LVEF and larger LAD than PPAF patients. Stroke patients with CAF had lower LVEF and larger LAD as compared to those without stroke. CONCLUSION: Atrial fibrillation is a common admission diagnosis in our hospital. Patients with AF commonly suffer from heart failure, hypertension, diabetes mellitus, and ischemic heart disease. There was a high prevalence of stroke among CAF patients.