Background: Healthcare workers play a key role in the transmission of methicillin-resistant Staphylococcus aureus (MRSA) in healthcare settings. Staphylococcus aureus is a major cause of healthcare associated infections, including surgical site infections, ventilator-associated pneumonia, and bloodstream infections.
The anterior nares serve as an important reservoir for this pathogen, facilitating its spread within healthcare environments. In recent years, the rising prevalence of antimicrobial resistance has become a major public health concern, leading to increased morbidity, mortality, and healthcare costs.
Therefore, assessing nasal carriage and antimicrobial resistance patterns among healthcare workers is essential for effective infection prevention and control. Objective: To detect Staphylococcus aureus from nasal swabs of healthcare workers and to determine its antimicrobial susceptibility profile, with a particular focus on resistant strains. Materials and Methods: This descriptive cross-sectional study included 159 healthcare workers from six private hospitals in Songino Khairkhan district. Nasal vestibule swabs were collected and cultured on 5% blood agar and CHROMagar™ MRSA. Bacterial identification was performed using conventional microbiological techniques and API identification systems. Antimicrobial susceptibility testing was conducted using the disk diffusion method and interpreted according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Statistical analysis was performed using SPSS version 24. The study protocol was submitted to and approved by the Research Ethics Subcommittee of “Ach” Medical University on November 11, 2025. Written informed consent was obtained from all participants prior to sample collection. Results: A total of 159 nasal swabs were collected from healthcare workers, from which 58 (36.5%) bacterial strains were isolated. Staphylococcus aureus was the most prevalent pathogen, accounting for 50 (86.2%) of the total isolates, representing an overall carrier rate of 31.4% (50/159) among the participants. Other identified species included Enterococcus spp. (n=5, 8.6%), Streptococcus viridans (n=2, 3.4%), and Klebsiella pneumoniae (n=1, 1.7%). Antimicrobial susceptibility testing revealed that 76% (n=38) of the S. aureus isolates were Methicillin-Resistant S. aureus (MRSA), and 21% (n=10) were Multi-Drug Resistant (MDR). Additionally, Vancomycin-Resistant S. aureus (VRSA) and Vancomycin-Resistant Enterococci (VRE) were each detected at a rate of 0.6% Conclusion Antibiotic-resistant bacteria were identified in 44 (27.7%) of samples collected from healthcare workers, indicating the presence of multidrug resistance.
The detection of methicillin-resistant Staphylococcus aureus (MRSA), along with vancomycin resistant Staphylococcus aureus (VRSA), among healthcare workers indicates a potential risk for the dissemination of highly resistant pathogens.

Background: Sand play benefits young children’s physical, cognitive, and socio-emotional development and can help meet the WHO’s daily activity recommendation of 180 minutes. Children consider playing with sand as a pleasurable activity, which allows them to interact with materials, explore, and use them creatively to develop their imagination. However, sand provides a favorable environment for the growth and development of microorganisms. Objective: To assess bacterial and parasitic contamination in playground sand and compare the findings with established hygiene standards. Materials and Methods: The study was conducted using a descriptive cross-sectional design. Thirteen kindergartens were selected through simple random sampling from a total of 39 public kindergartens in Bayangol District, Ulaanbaatar. The research was carried out using laboratory analysis methods. Collected data were compiled using Microsoft Excel and Word 2016, and processed with SPSS version 24 Results: The total bacterial contamination of the sand samples collected in the study was 2.2 Ч 10⁵ CFU/g, indicating heavy contamination. The analysis showed that Clostridium perfringens was present in 100% of samples (n=13), Escherichia coli in 92.8% (n=12), Bacillus subtilis in 46.1% (n=6), and Acinetobacter in 7.7% (n=1). Additionally, mold was detected in 38.4% of the samples (n=5). Parasite eggs were found in 54% (n=7) of the samples from the 13 kindergartens. Analysis of the types of parasite eggs revealed that Ascaris lumbricoides was present in 28.5% (n=2), Enterobius vermicularis in 28.5% (n=2), Balantidium coli in 57.1% (n=4), and Toxocara spp. in 14.2% (n=1) of the positive samples. Conclusion Playground sand is highly contaminated with bacteria and parasites, posing infection risks, and is influenced by animal feces, poor sanitation, and environmental conditions.

Introduction: This study highlights the importance of access to treatment services and medicines. Research has shown that a significant portion of direct expenses for individuals who are not covered by health insurance is allocated to treatment, diagnostics, and medication costs, indicating issues with the accessibility and quality of health services.
According to the World Health Organization recommendations, if out-of-pocket health expenses exceed 25% of total health financing, it heightens the risk of deepening poverty and creates inequalities related to income.
Although policies and programs aimed at increasing access to subsidized medicines are being implemented, the expected outcomes and actual implementation of these initiatives have not fully met the health needs of the entire population.
Therefore, addressing these issues is essential. For instance, improving the regulation of medicine prices, ensuring adequate supply, and enhancing the subsidy system may be necessary steps moving forward. Methods: This study was conducted using a cross sectional design, employing methods such as document analysis, comparative study, and synthesis.
The list of discounted medicines provided by the health insurance fund includes 650 items from 161 manufacturers across 40 countries. Among these medicines, 7% have expired registration, 9% have been removed from registration, 11% are out of stock, and 73% are supplied normally. Of the medicines listed, 7% are domestic, and 93% are imported, with 39% coming from Asian countries and 54% from European countries, indicating a high reliance on imports for medicine supply and accessibility. A study of the medicines supplied by the pharmaceutical supply organizations shows that 16.5% of the prices are above the maximum price set by the health insurance fund, indicating the need for establishing medicine prices based on research and evidence. Conclusion Out of the 650 types of medicines registered in the list of subsidized medicines, 27% are in a status of expired, removed, or out of stock. The price from the pharmaceutical supply organizations exceeds the upper limit of the subsidized medicine prices set by the insurance fund, covering 83.5% of the total group of medicines.
Therefore, it is necessary to update the list of subsidized medicines from the health insurance fund based on research and evidence.

Abstract Over the past decade, Big Data and Artificial Intelligence (AI) have emerged as transformative forces in healthcare, particularly in pharmaceutical policy, regulation, and drug safety surveillance. These technologies enable the systematic collection, integration, and analysis of large-scale and heterogeneous data, thereby strengthening evidence-based decision-making across the pharmaceutical lifecycle. International experience demonstrates that the integration of AI and Big Data supports early detection of adverse drug reactions (ADRs), enhances pharmacovigilance systems, automates regulatory processes, and accelerates drug discovery and development. AI-driven methods, including machine learning and natural language processing (NLP), facilitate the identification of latent patterns and risk signals from diverse data sources such as clinical trials, Real World Evidence (RWE), electronic health records, and spontaneous reporting systems.
Despite these global advances, the application of AI and Big Data within Mongolia’s pharmaceutical policy and regulatory framework remains limited. Key challenges include fragmented and poorly integrated data sources, insufficient data standardization, underdeveloped information technology infrastructure, limited human resource capacity, and gaps in legal and ethical governance. International initiatives offer valuable reference models for addressing these challenges. The World Health Organization’s VigiBase employs AI and NLP techniques to identify global ADR trends, the U.S. Food and Drug Administration’s Sentinel Initiative integrates RWE to support proactive drug safety monitoring, and the Republic of Korea’s Disease Control and Prevention Agency has implemented an NLP-based pharmacovigilance system for automated risk detection.
This study aims to assess the applicability of Big Data and AI in Mongolia’s pharmaceutical policy and regulatory system through a comparative analysis of international best practices and the identification of key implementation gaps. The findings emphasize the need for integrated data systems, harmonized standards, localized AI application models, and robust regulatory and ethical frameworks. Overall, the study highlights the potential of Big Data and AI to modernize pharmaceutical policy and regulation in Mongolia and provides evidence-based directions for sustainable implementation aligned with international best practices.

Introduction: University students encounter multiple academic, psychosocial, and environmental stressors during their transition to higher education. Nursing students may be particularly vulnerable because of concurrent academic and clinical demands. Objective: To identify the relationships among perceived stress, social support, and psychological anxiety among nursing students. Methods: A cross-sectional quantitative study was conducted among first- to fourth-year nursing students at the International University of Ulaanbaatar. After excluding 16 incomplete questionnaires, 119 valid responses were analyzed using descriptive statistics, reliability testing, and correlation analysis in SPSS version 26.
Participants had a mean age of 22.39±5.60 years, and 86.6% were female. The mean item scores were 3.15±0.40 for perceived stress, 4.11±0.78 for social support, and 2.35±0.39 for total anxiety. Perceived stress was positively correlated with total anxiety (r=.310, p=.001), personal anxiety (r=.307, p=.001), and situational anxiety (r=.261, p=.004), and negatively correlated with age (r=-.213, p=.020). Social support was not significantly correlated with perceived stress (r=.015, p=.872) but was negatively correlated with total anxiety (r=-.253, p=.005) and personal anxiety (r=-.334, p<.001). Conclusion Students’ perceived stress was associated with anxiety. Higher social support was related to lower anxiety, although a direct relationship between social support and perceived stress was not observed in this sample.

Background: Cerebral cavernous malformations (CCM) present with varied symptoms and are diagnosed only on MRI, which shows characteristic appearances. Genetic factors play a role, with familial cases following an autosomal dominant inheritance pattern. Case: This is the clinical case of a 48-year-old woman with a history of long-standing arterial hypertension. She was admitted to the Stroke Department with headache, nausea, vomiting, right-sided sensory disturbance, and dysarthria. Based on the clinical presentation and MRI, multiple supra- and infratentorial and intraxial lesions with heterogeneous components were identified, exhibiting hypointense rings on T1- and T2-weighted sequences and a “blooming” effect on T2*/GRE sequences, characteristic of cerebral cavernomas, displaying a “popcorn” appearance. Conclusion In CCM, management requires a multidisciplinary approach, with surgical resection the gold standard for symptomatic cases. Accurate determination of familial or sporadic origin is crucial for tailored treatment.

Background: Primary central nervous system lymphoma (PCNSL) is a rare form of extranodal non-Hodgkin lymphoma that is confined to the brain, spinal cord, leptomeninges, or eyes. Case: Our patient was a 52-year-old immunocompetent male who presented with progressive ataxia, dizziness, weakness and pain in both legs, imbalance, nausea, bladder/bowel retention and fever for over 18 months. After repetitive brain and spinal MRI, he was diagnosed with encephalomeningomyelitis and received four courses of steroid therapy, but his clinical symptoms continued to worsen. He was unable to undergo brain tissue analysis due to his persistent fever. We present a case of PCNSL based on the history, clinical presentation, repeated brain imaging, cerebrospinal fluid analysis, and clinical treatment. Conclusion Early diagnosis through accurate interpretation of imaging and timely management is crucial for improved outcomes in PCNSL.

This literature review provides a comprehensive synthesis of empirical research on tuberculosis (TB) case detection mechanisms, transmission dynamics, and associated risk factors, examining diverse epidemiological contexts across the United States, the United Kingdom, India, the Netherlands, the Dominican Republic, and Mongolia.
Specifically, the selected literature evaluates the differential transmission potential between smear-positive and smear-negative cases, quantifies secondary infection risks among close contacts, and examines the clinical utility of advanced molecular diagnostics.
The analyzed data draw upon a substantial body of empirical evidence spanning six decades, focusing primarily on the timeline from 1960 to 2020. By integrating both international and national research findings, this review highlights the significance of early tuberculosis detection and clarifies patterns of disease transmission.

Background: Cardiovascular disease remains a leading cause of mortality worldwide, and unhealthy diet, physical inactivity, excess body weight, central obesity, and metabolic alterations during young adulthood may increase cardiovascular risk later in life. In addition to conventional lipid parameters, the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C), total cholesterol-to-high-density lipoprotein cholesterol (TC/HDL-C), and low-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol (LDL-C/HDL-C) ratios have been investigated as additional indicators of alterations in lipid metabolism and atherogenic risk. Although lipid parameters and metabolic risk factors have been investigated among university students in Mongolia, assessment of metabolic risk among nursing students is of practical importance because of the characteristics of their future professional roles. This provided the rationale for the present study. Aim: To determine peripheral blood lipid ratios among students of the School of Nursing, Mongolian National University of Medical Sciences (MNUMS), and assess their associations with selected metabolic risk factors. Materials and Methods: An analytical cross-sectional study was conducted among 98 first- to fourth-year students aged 18–24 years. Data were collected using a 33-item structured questionnaire, anthropometric measurements, blood pressure measurements, and peripheral blood biochemical testing. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glucose were measured using a Sinocare portable analyzer, and TG/HDL-C, TC/HDL-C, and LDL-C/HDL-C ratios were calculated. Body mass index (BMI), waist circumference, and systolic and diastolic blood pressure were measured using standardized procedures. Differences between groups were assessed using the Mann–Whitney U and Kruskal–Wallis tests, and associations between variables were evaluated using Spearman’s correlation analysis. A p-value <0.05 was considered statistically significant. Results: The mean age of the participants was 20.85±1.52 years, and 75.5% were female. Mean TC, TG, HDL-C, and LDL-C levels were 3.69±0.75, 1.17±0.67, 1.24±0.38, and 2.00±0.65 mmol/L, respectively. Mean TG/HDL-C, TC/HDL-C, and LDL-C/HDL-C ratios were 1.06±0.92, 3.28±0.87, and 1.80±0.66, respectively. Mean BMI was 22.93±4.11 kg/m², waist circumference was 75.96±11.28 cm, glucose was 5.63±0.72 mmol/L, and systolic and diastolic blood pressure were 113.31±9.88 and 70.72±8.49 mmHg, respectively. The TG/HDL-C ratio was positively correlated with BMI (rₛ=0.336), waist circumference (rₛ=0.381), glucose (rₛ=0.278), systolic blood pressure (rₛ=0.294), and diastolic blood pressure (rₛ=0.322). The TC/HDL-C ratio was significantly associated with BMI, waist circumference, and systolic and diastolic blood pressure, whereas the LDL-C/HDL-C ratio was significantly associated with waist circumference and systolic blood pressure. Waist circumference was significantly associated with all three lipid ratios, with the strongest correlation observed for TC/HDL-C (rₛ=0.485, p<0.001). Conclusion BMI, waist circumference, glucose, and selected blood pressure measures were positively associated with lipid ratios among the study participants. In particular, waist circumference was significantly associated with all three lipid ratios: TG/HDL-C, TC/HDL-C, and LDL-C/HDL-C. These findings indicate the importance of considering waist circumference and lipid parameters in addition to BMI when assessing metabolic risk among university students.

Background: Nicotine-containing vaporized liquids—composed of propylene glycol, glycerin, water, flavorings, and the thickening agent vitamin E acetate—have been implicated in the development of EVALI. Under conditions of low liquid levels and overheating, these substances release toxic carbonyl compounds (e.g., formaldehyde, acetaldehyde, acrolein). In a 2019 national survey, 3.5% of adolescents aged 13–15 reported cigarette use, and 10% used e-cigarettes. Aim: To study the changes in the behavior, lung, and hippocampal structures of rats due to the effects of electronic cigarettes and their vapor. Materials and Methods: In this study, nineteen 14-day-old SHR rats were exposed to 1 g/mg/day of nicotine and dry hit vapor (control, nicotine and dry hit groups) for four weeks. Behavioral assessments (Open Field Test, Elevated Plus Maze, Conditioned Place Preference), bronchoalveolar lavage (BAL), and histological analysis of lung and hippocampal tissue were conducted. Results: The dry hit vapor group showed significantly reduced body weight (p=0.034), increased anxiety (p=0.006, p=0.025), and avoidance of the smoky chamber. BAL revealed elevated total cells, neutrophils, and macrophages (p=0.01, p=0.04) in both nicotine and dry hit groups. Lung tissue exhibited alveolar septal thickening, inflammation, and emphysema- like changes. Extensive neuronal death was observed in the hippocampus. Conclusion Anxiety-like behavior was observed in both the burn and control groups. Analysis of BAL in the dry hit group revealed inflammation predominantly characterized by macrophage infiltration. Histological examination of lung tissue from both experimental groups demonstrated a reduction in the number of alveoli, accompanied by acute inflammation and thickening of the interalveolar septa. In the hippocampal region, neuronal loss and a reduction in neuronal density were also observed.