Tuberculosis Situation in Volga Federal District in 2016-2020

The objective of the study: to assess changes in the incidence and prevalence of multiple drug resistant tuberculosis (MDR TB) and TB/HIV coinfection (TB/HIV) in Volga Federal District (VFD) and its regions during 2016-2020.Subjects and Methods. Data from FGSN Forms No. 8, 33, and 61, and analytical reviews of main statistical TB rates in the Russian Federation have been studied. The number of those died is presented as per the Rosstat data.Results. An increase in the incidence and prevalence of MDR TB and TB/HIV coinfection has been detected in certain region of Volga Federal District. Perm Region, the Republic of Bashkortostan, the Republic of Udmurtia, and Orenburg and Samara Regions have the highest prevalence of MDR TB and TB/HIV coinfection. In 2020, the Republic of Bashkortostan was the only region where the incidence and prevalence of MDR TB were growing (164.7% and 47.3%, respectively). The highest incidence and prevalence of TB/HIV coinfection was reported in the Republic of Bashkortostan, Perm Kray, Orenburg Region, the Chuvash and Udmurt Republics. Over the last 5 years, the maximum increase in TB/HIV incidence and prevalence was observed in the Republic of Bashkortostan (38.8% and 41.3%, respectively).

Drug Utilization Evaluation of Colistin: A Retrospective Study

Background: Colistin, is used as the last treatment line for infections concluded from multiple drug-resistant gram-negative microorganisms. Increased consumption of colistin leads to resistance to this antibiotic in many countries. This study investigated the usage pattern of colistin administration in a selected hospital in Iran. Methods: This study was conducted in a selected hospital in Ahvaz. Inclusion criteria were all patients who received colistin during this time according to the health information system. Patients who were received less than three doses of colistin were excluded from the study. Prescription of colistin in all patients was evaluated according to the protocol extracted from the last version of Lexicomp written by Wolters Kluwer. The descriptive and analytical statistics were carried out by the R software. Results: Among 27 patients who received colistin, pneumonia (30%) was the main diagnoses. Colistin administration was based on the microbiological culture data in 70% of cases. Considering the involved microorganism, most cases were Acinetobacter spp., followed by Klebsiella spp. Loading dose was prescribed for seven (26%) patients. In only five (19%) cases, colistin dosing, including loading dose, maintenance dose, and the interval of colistin administration, was appropriate during the study time. Increasing in serum creatinine was seen in two (7.4%) patients. In 29.4% of patients, the combination of colistin and carbapenems was observed. Conclusion: Given the lack of appropriate dose adjustment of colistin that may lead to incidence of resistance and adverse effect, applying of the specialist clinical pharmacist will be suggested.

A Drug-free Strategy to Combat Bacterial Infections with Magnetic Nanoparticles Biosynthesized in the Bacterial Pathogens

The extensive and indiscriminate use of antibiotics in the ongoing COVID-19 pandemic might significantly contribute to the growing number of multiple drug resistant (MDR) bacteria. With the dwindling pipeline of...

Therapy challenges in patients with Mycoplasma genitalium infection of the urogenital tract: clinical observations

Mycoplasma genitalium is a clinically significant intracellular bacterium from the family of genital mycoplasmas; it absolutely dominates in persistent/recurrent nongonococcal urethritis, causes chronic inflammatory diseases of the urogenital organs which dictates the necessity of treating this infection. The study presents observations of 2 patients with chronic recurrent urethritis caused by multiple drug resistant strains of M. genitalium. None of the administered schemes of antibacterial treatment covered in the international protocols on treatment of M. genitalium infection allowed to achieve clinical or microbiological cure in these patients. Practicing doctors require development and improvement of nucleic acid amplification methods with antimicrobial testing for M. genitalium resistance and new antimicrobial drugs with improved chemical and pharmacological characteristics for treatment of patients with intracellular urogenital infections.

A Review on Microbial Products and Their Perspective Application as Antimicrobial Agents

Microorganisms including actinomycetes, archaea, bacteria, fungi, yeast, and microalgae are an auspicious source of vital bioactive compounds. In this review, the existing research regarding antimicrobial molecules from microorganisms is summarized. The potential antimicrobial compounds from actinomycetes, particularly Streptomyces spp.; archaea; fungi including endophytic, filamentous, and marine-derived fungi, mushroom; and microalgae are briefly described. Furthermore, this review briefly summarizes bacteriocins, halocins, sulfolobicin, etc., that target multiple-drug resistant pathogens and considers next-generation antibiotics. This review highlights the possibility of using microorganisms as an antimicrobial resource for biotechnological, nutraceutical, and pharmaceutical applications. However, more investigations are required to isolate, separate, purify, and characterize these bioactive compounds and transfer these primary drugs into clinically approved antibiotics.

Structural and mechanistic basis of the high catalytic activity of monooxygenase Tet(X4) on tigecycline

Background Tigecycline is a tetracycline derivative that constitutes one of the last-resort antibiotics used clinically to treat infections caused by both multiple drug-resistant (MDR) Gram-negative and Gram-positive bacteria. Resistance to this drug is often caused by chromosome-encoding mechanisms including over-expression of efflux pumps and ribosome protection. However, a number of variants of the flavin adenine dinucleotide (FAD)-dependent monooxygenase TetX, such as Tet(X4), emerged in recent years as conferring resistance to tigecycline in strains of Enterobacteriaceae, Acinetobacter sp., Pseudomonas sp., and Empedobacter sp. To date, mechanistic details underlying the improvement of catalytic activities of new TetX enzymes are not available. Results In this study, we found that Tet(X4) exhibited higher affinity and catalytic efficiency toward tigecycline when compared to Tet(X2), resulting in the expression of phenotypic tigecycline resistance in E. coli strains bearing the tet(X4) gene. Comparison between the structures of Tet(X4) and Tet(X4)-tigecycline complex and those of Tet(X2) showed that they shared an identical FAD-binding site and that the FAD and tigecycline adopted similar conformation in the catalytic pocket. Although the amino acid changes in Tet(X4) are not pivotal residues for FAD binding and substrate recognition, such substitutions caused the refolding of several alpha helixes and beta sheets in the secondary structure of the substrate-binding domain of Tet(X4), resulting in the formation of a larger number of loops in the structure. These changes in turn render the substrate-binding domain of Tet(X4) more flexible and efficient in capturing substrate molecules, thereby improving catalytic efficiency. Conclusions Our works provide a better understanding of the molecular recognition of tigecycline by the TetX enzymes; these findings can help guide the rational design of the next-generation tetracycline antibiotics that can resist inactivation of the TetX variants.

Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients

The objective of the study: to evaluate the possibility of using machine learning algorithms for prediction of relapses in multiple drug resistant tuberculosis (MDR TB) patients.Subjects and Methods. Сlinical, epidemiological, gender, sex, social, biomedical parameters and chemotherapy parameters were analyzed in 346 cured MDR TB patients. The tools of the scikit-learn library, Version 0.24.2 in the Google Colaboratory interactive cloud environment were used to build forecasting models.Results. Analysis of the characteristics of relapse prediction models in cured MDR TB patients using machine learning algorithms including decision tree, random forest, gradient boosting, and logistic regression using K-block stratified validation revealed high sensitivity (0.74 ± 0.167; 0.91 ± 0.17; 0.91 ± 0.14; 0.91 ± 0.16, respectively) and specificity (0.97 ± 0.03; 0.98 ± 0.02; 0.98 ± 0.02; 0.98 ± 0.02, respectively).Five main predictors of relapse in cured MDR-TB patients were identified: repeated courses of chemotherapy; length of history of tuberculosis; destructive process in the lungs; total duration of treatment less than 22 months; and use of less than five effective anti-TB drugs in the regimen of chemotherapy.