Background: Latent tuberculosis infection (LTBI) is the principal reservoir for active tuberculosis, with >85% of cases attributable to reactivation. Bacillus Calmette-Guérin fails to block this transition, leaving a critical gap in prevention. Methods: An immunoinformatics/reverse-vaccinology pipeline was applied to seven dormancy-related antigens retrieved from Mycobrowser. T-cell epitopes were predicted with NetMHCI/IIpan-4.1 and B-cell epitopes with ABCpred; antigenicity, allergenicity, and toxicity were evaluated with VaxiJen, AllerTOP, and ToxinPred. Secondary/tertiary structures were modeled with PSIPRED and AlphaFold-3; docking to Toll-like receptors (TLR) 2/4 and 100 ns molecular dynamics simulations assessed complex stability. Immune responses were simulated with C-ImmSim, and the mRNA sequence was human-codon-optimized using ExpOptimizer. Results: The resulting construct, RP14914P, encodes 14 cytotoxic T lymphocyte, 9 helper T lymphocyte, and 14 B-cell epitopes within an 866-aa, 90.4 kDa polypeptide. Antigenicity score = 0.7797, immunogenicity score = 8.58629. and no toxicity or allergenicity was predicted. Physicochemical analysis: instability index = 28.65, and solubility = 0.513. Estimated population coverage is 82.35% and 99.67% for Human Leukocyte Antigen (HLA)-I and HLA-II globally. Docking energies: −1477.8 kcal/mol (TLR2) and −1480.1 kcal/mol (TLR4). Molecular dynamics trajectories confirm stable binding. Immune simulation predicts potent activation of Natural Killer cells, macrophages, and dendritic cells, Th1 polarization, high interferon-γ/interleukin-2 secretion, and durable memory. Conclusions: In silico analyses predict that RP14914P exhibits favorable immunogenicity, safety, and broad population coverage, suggesting its potential as a promising mRNA vaccine candidate to prevent LTBI reactivation. However, these computational predictions require thorough experimental validation to confirm the vaccine’s immunogenicity and protective efficacy.
This study reports successful synthesis and application of a multifunctional magnetic nanocomposite, comprising MWCNTs, MnO₂, and mealworm skin-extracted chitin, as a splendid sorbent for preconcentration and determination of narcotic drugs papaverine, noscapine, codeine, and morphine in complex biological matrices, using d-μ-SPE (dispersive micro-solid-phase extraction). Characterization via FT-IR, FE-SEM, XRD, EDS, TGA, VSM, and BET analyses confirmed the nanocomposite's structural integrity, high surface area (107.68 m²/g), mesoporosity, and superparamagnetic behaviour, which altogether enhance adsorption capacity and facilitate facile and rapid magnetic separation. Adsorption studies demonstrated adherence to Langmuir and pseudo-second-order models, indicative of monolayer adsorption on homogeneous active sites. Statistical optimization using Central Composite Design allowed precise modulation of parameters influencing adsorption and desorption phases, improving extraction recoveries and method reproducibility. Optimal conditions for maximum analyte recovery within short extraction and desorption times included a sample pH around neutrality (7.3), adsorbent dosage of 5.8 mg, and the usage of a 50:50 ethanol-acetonitrile solvent mixture for desorption. With LODs as low as 0.10 ng/mL, broad linear dynamic ranges, and relative standard deviations under 4.8%, the method exhibited remarkable analytical performance. Application to real samples, including plasma, breast milk, urine, and saliva, yielded recoveries between 93.36% and 102.85%, which vouchsafed robustness and minimal matrix interference. Overall, exploiting a novel magnetic nanocomposite, the new environmentally-compatible, rapid, and sensitive UA-D-μ-SPE method offers a powerful tool for trace-level detection of narcotic drugs, leading to enhanced capabilities in forensic and clinical toxicology.
Breast cancer (BRCA) remains one of the most prevalent malignancies worldwide, characterized by marked molecular heterogeneity and diverse clinical outcomes. Necroptosis and ferroptosis, two regulated forms of programmed cell death (PCD), play pivotal roles in tumor progression and immune regulation; however, their combined influence on BRCA pathogenesis remains inadequately understood. To elucidate these interactions, transcriptomic datasets (GSE254218, GSE220608) were integrated to identify differentially expressed genes (DEGs) using edgeR (|log2FC|> 1, FDR < 0.05). From 805 DEGs, intersection with 614 necroptosis-related genes (NRGs) and 259 ferroptosis-related genes (FRGs) yielded 37 candidate cell death-related genes (CDRGs). CytoHubba analysis prioritized 25 hub genes, and UALCAN expression profiling identified six significantly stage-associated genes CASP1, TLR3, PYCARD, KRT5, MAP1B, and MMP13 (p < 1E − 12). Functional enrichment (GO/KEGG) and protein–protein interaction (PPI) analyses linked these genes to immune activation, inflammatory signaling, and PCD-associated pathways. Integrated survival and immune infiltration analyses (CIBERSORT, TIMER 2.0) highlighted CASP1, TLR3, PYCARD, and CD274 as key prognostic biomarkers modulating the BRCA tumor microenvironment. To evaluate genetic and structural perturbations affecting these targets, deleterious nonsynonymous SNPs (nsSNPs) were filtered using SIFT, PolyPhen-2, CADD, REVEL, MetaLR, and Mutation Assessor. Structural characterization identified nine high-impact nsSNPs (ΔΔG < − 1.7 kcal/mol), particularly in TLR3 (L104N, L381P, L77P) and CD274 (W57S, C155S, G159D, Y112N), indicating potential disruption of receptor stability, immune checkpoint interactions, and inflammasome regulation. This integrative multi-omics and structural pharmacogenomics framework reveals a robust four-gene signature (CASP1, TLR3, PYCARD, CD274) that links necroptosis, ferroptosis, and immune modulation in BRCA, providing promising avenues for precision oncology and therapeutic target development. Integrative transcriptomic analysis of BRCA samples identified four key biomarkers—CASP1, TLR3, PYCARD, and CD274—linking necroptosis, ferroptosis, and immune regulation. DEGs identified from GEO dataset (Illumina sequencing) were overlapped with necroptosis- and ferroptosis-related genes to yield candidate CDRGs, followed by PPI, enrichment, survival, and immune infiltration analyses. Drug–gene interaction mapping using the CTD database prioritized clinically relevant compounds, highlighting FDA-approved agents (e.g., Cisplatin, Arsenic Trioxide, Valproic Acid, Aripiprazole) as potential therapeutic modulators. Subsequent nsSNP prioritization and structural modeling using SIFT, PolyPhen-2, CADD, REVEL, NetSurfP-2.0, Project HOPE, and DUET revealed nine deleterious mutations affecting protein stability and immune signaling. Drug–gene interaction mapping identified clinically actionable compounds targeting these biomarkers. This workflow demonstrates the translational potential of these biomarkers as both prognostic indicators and drug targets for precision oncology in BRCA.
Background Kazakhstan has lacked validated tools to comprehensively assess physicians’ perceptions, usability, and perceived effectiveness of telemedicine services. International frameworks such as the Telehealth Usability Questionnaire (TUQ) and the Model for Assessment of Telemedicine (MAST) have not previously been adapted to the national clinical and organizational context. Objective This study aims to develop and validate TUQ-MAST-KZ, a Kazakhstan-adapted questionnaire integrating components of the TUQ and MAST models to assess physicians’ perceptions, usability, and effectiveness of telemedicine services. Methods A multiphase study was conducted, including literature review, questionnaire development, linguistic and cultural adaptation, expert content validity assessment, and pilot testing. An online survey (Google Forms) was administered to 156 physicians representing different regions and levels of health care delivery in Kazakhstan. Internal consistency (Cronbach α) and content validity indices were calculated. Additional evaluations covered clarity, structure, and practical applicability. Results The final TUQ-MAST-KZ instrument contains 27 items capturing technological, clinical, organizational, and behavioral dimensions of telemedicine use. The scale demonstrated high content validity (scale-level content validity index=0.94). Internal consistency was excellent, with an overall Cronbach α of 0.924. Respondents reported that the questionnaire was clearly structured, easy to complete, and relevant to clinical practice. Organizational items identified key barriers to telemedicine adoption, including limited infrastructure, insufficient managerial support, and the need for additional training. Conclusions TUQ-MAST-KZ is a valid, reliable, and practice-oriented instrument for assessing physicians’ perceptions of telemedicine services in Kazakhstan. It can support digital health monitoring, implementation analysis, educational planning, and policy development. Future studies should evaluate its applicability across broader samples and diverse clinical specialties.
Acinetobacter baumannii has emerged as one of the most challenging opportunistic pathogens in modern healthcare due to its remarkable ability to acquire and disseminate antimicrobial resistance determinants. Carbapenem-resistant A. baumannii (CRAB) is now recognized by the World Health Organization as a critical priority pathogen, highlighting the urgent need for improved diagnostic, surveillance, and therapeutic strategies. This review synthesizes current evidence on the relationship between phenotypic antimicrobial susceptibility patterns and underlying genetic determinants of resistance in A. baumannii. A structured literature search was conducted across major biomedical databases (PubMed/MEDLINE, Scopus, Web of Science, and the Cochrane Library), supplemented by citation tracking and relevant institutional sources, focusing on studies published between 2016 and 2026. The analysis integrates findings from studies examining phenotypic antimicrobial susceptibility testing (AST) with molecular and genomic investigations of resistance mechanisms, including carbapenemases, aminoglycoside-modifying enzymes, efflux pumps, and resistance-associated genomic islands. Particular attention is given to the complex and sometimes discordant relationship between genotype and phenotype, where the presence of resistance genes does not always translate directly into phenotypic resistance due to regulatory mechanisms, gene expression variability, and genomic context. The review further discusses methodological differences in AST standards and genomic prediction approaches that may contribute to variability across studies. Collectively, the evidence supports a multidimensional interpretation of antimicrobial resistance in A. baumannii, emphasizing the necessity of integrating phenotypic and genotypic data for accurate diagnostics, surveillance, and clinical decision-making. This integrated perspective may contribute to improved understanding of resistance evolution and support the development of more effective strategies for managing multidrug-resistant A. baumannii infections.
