Background: Sleep quality is frequently highlighted in the literature as a key factor for overall health. Poor sleep quality significantly affects both physical and mental health, diminishing quality of life and potentially harming personal finances. While this issue is influenced by various risk factors, no well-studied research has been conducted on it in Mongolia. Aim: The aim of this study was to assess the frequency of poor sleep quality among visitors to the Sleep center in Mongolia and to identify the factors associated with poor sleep quality. Materials and Methods: This study, conducted using a cross-sectional design, included 200 participants aged 18 to 65 years who visited the Sleep Center at the General Hospital for State Special Servants between January and May 2024. Data were collected using a structured questionnaire. Sleep quality was assessed using the Mongolian version of the Pittsburgh Sleep Quality Index, with a global score above 6 indicating poor sleep. Participants were divided into two groups: “Good sleepers” (n=105) and “Poor sleepers” (n=95). Socio-demographic and clinical variables such as age, sex, levels of education were also recorded. The level of depression, anxiety, and stress was assessed using the DASS 21 (Depression Anxiety Stress Scale) criteria. Univariate analysis was performed using the t-test, Mann-Whitney U test for continuous data, the Х2 or Fishers’s exact test for categorical data, and logistic regression for multivariable analysis. A P-value of less than or equal to 0.05 was considered significant. Results: Poor sleep quality, indicated by a PSQI global score above 6, was observed in 52.5% of the total participants. Univariate analtysis’s test results showed that age, being female, having depression, anxiety, BMI ≥ 25, alcoholism, comorbidities, and using concomitant medications were significantly associated with poor sleep quality (all p<0.05). In the multivariate logistic regression analysis, 50 < age (OR 3.133, 95% CI, 1.245-7.884, p<0.05), BMI ≥ 25 (OR 2.084, 1.039-4.179, p<0.05), alcoholism (OR 3.018, 95% CI, 1.495-6.093, p<0.01) and depression (OR 15.957, 95% CI, 1.592-159.922, p<0.05) were identified as significant risk factors for poor sleep quality. Depression and alcoholism were associated with longer sleep latency and decreased daytime activity (p<0.05). Conclusions 1. In our study, more than half of the participants experienced poor sleep quality. 2. Age over fifty, depression, BMI ≥ 25, and alcoholism emerged as independent significant risk factors for sleep disturbance. Alterations in sleep latency, sleep disruption, and impaired daytime functioning may be associated with poor sleep quality.

Background: This study explores the potential of food industry by-products, such as plant peels, stems, and slags, as valuable sources of lignocellulosic material (LCM), which contains 25-40% xylan. These underutilized resources, often discarded as waste, hold the promise of sustainable applications in biotechnology. By safely extracting xylooligosaccharides (XOS) from LCM biomass, the value of these materials can be significantly enhanced, contributing to green production and supporting sustainable development. XOS, recognized for its prebiotic activity, has been shown to promote the growth of beneficial gut bacteria, making it a vital research area in the fields of food science, medicine, and technology. Aim: To extract and characterize oligosaccharides derived from by-products of the food industry, evaluate their physicochemical properties, and investigate selected biological activities. Materials and Methods: This study utilized microwave pretreatment and enzymatic hydrolysis to isolate and purify XOS from wheat bran and brewers’ spent grains (BSG), provided by Altan Taria LLC and APU CoL, respectively. Microwave irradiation at 200°C for 5 minutes was employed as a pretreatment step, followed by hydrolysis using commercial xylanase (Thermomyces lanuginosus, recombinant Aspergillus oryzae, 2500 BXU/g) at 55°C for 24 hours. The resulting hydrolysate underwent filtration with activated carbon and ethanol precipitation to yield purified XOS. Analytical methods, including FTIR spectroscopy, TLC and HPLC, were used for structural and compositional analysis of the purified oligosaccharides. In vitro tests evaluated the ability of XOS to support the growth of beneficial gut bacteria, including Bifidobacterium spp., Lactobacillus fermentum (ATCC 9338), and Lactobacillus casei (ATCC 344), using XOS-enriched media. Additionally, in vivo studies were conducted on rats to determine the biological effects of XOS on gut microbiota. Results: The results demonstrated that prolonged enzymatic hydrolysis for more than 10 hours, using 0.25 g of xylanase per 100 g of substrate, resulted in optimal yields. XOS purity was measured at 87.6% with an 8.1 g yield from wheat bran and 89% purity with a 7.2 g yield from brewers’ spent grains. Structural analysis confirmed the presence of xylobiose, xylotriose, and xylotetraose, with xylotetraose being the most abundant component in WBP-XOS (47.5%), and xylobiose dominating BGS’s derived XOS (47.8%). Biological effects revealed that wheat bran-derived XOS significantly supported the growth of Bifidobacterium spp. and L. fermentum (ATCC 9338) in a concentration-dependent manner, whereas no significant effect was observed on L. casei (ATCC 344). In vivo studies confirmed that XOS consumption increased populations of Bifidobacterium spp. and Akkermansia muciniphila spp. in gut microbiota (p<0.05). Furthermore, XOS consumption reduced plasma cholesterol, triglycerides, and LDL-C levels while increasing HDL-C levels, demonstrating metabolic benefits. Conclusion This research establishes that XOS with prebiotic activity can be efficiently extracted and purified from food industry by-products using microwave-assisted enzymatic hydrolysis. This approach highlights the potential of utilizing agricultural and industrial waste for producing functional prebiotics, contributing to sustainable practices and offering valuable applications in health and nutrition.

Introduction: Total environment 24 % of all estimated global deaths are linked to the environment. As of 2022, Ulaanbaatar has a population of 1,691,800, vehicles 435,725, thermal power plants 4, market and shopping centers 111, factories 13,465, and 225 gas stations. Also, 1.5 million tons of waste are generated annually, 1135.6 tons of coal are used, and environmental pollution is increasing year by year. Therefore, it is necessary to investigate the heavy metal contamination of the soil of Ulaanbaatar city and protect the health of the population. Purpose: To determine heavy metals pollution in the soil of Ulaanbaatar city Materials and Methods: We used descriptive research design in this study. Secondary data from Meteorological and Environmental Monitoring Department was used. The content of heavy metals such as lead (Pb), mercury (Hg), chromium (Cr), and cadmium (Cd)) in the soil was evaluated in comparison with the maximum permissible amount specified in the MNS 5850:2019 standard. Statistical analyzing was calculated using SPSS-25 software, and p<0.05 was considered statistically significant. Results: The average concentration of heavy metals in the soil of residential areas of 9 districts of Ulaanbaatar city is cadmium 0.43 mg/kg (min=0, max=26.6), mercury 0.22 mg/kg (min=0, max=4), chromium 11.2 mg/kg ( min=0, max=1609.6), lead is 24.4 mg/kg (min=0, max=257.2). Cadmium concentration in soil Bagakhangai (25%), Baganuur (19.7%), Khan-Uul (18.9%), lead concentration in Nalaikh (8.3%), Bayanzurkh (5.4%), Chingeltei (3.3), mercury concentration in Baganuur ( 24.7%), Khan-Uul (18.4%), and chromium concentration in certain locations of Khan-Uul (4.7%) districts exceeded the standards, respectively. The concentration of soil cadmium (21.2%) and lead (7.7%) near the technical market, mercury concentration (26.3%) near the market and shopping center, and chromium concentration (58.9%) near the central treatment plant exceeded the maximum permissible levels. Conclusion Cadmium and mercury pollution were mainly detected in the heavy metal pollution of the soil of Ulaanbaatar city, and there is heavy metal pollution in certain locations of Baganuur and Khan-Uul districts. Heavy metal pollution is caused by activities such as technical markets, auto repair shops, markets, shopping centers, and treatment plants.

BackgroundThere are 137 soums of 17 provinces have plague foci in Mongolia. The 51.7% of them is case, 23.4%- low, 9.5% - high, 0.7% - hyper active. Main host of plague foci is marmot in Mongolia. According last20 year’s surveillance study, about 75.5% of Y.pestis was isolated from marmot, marmot carcassesand their flea. Human plague cases has been caused illegal hunting marmot in Mongolia. Even legaldocument which prohibited marmot hunting was appeared since 2005, people has been hunting marmotfor selling marmot meat, skin and other products. It is depends economy crises and other public issues inMongolia. Also influenced increase risk of human plague and being reverse result in plague preventionactivities.Materials and MethodsStudy was used data of rodent for zoonotic diseases suspicious which tested plague in National centerfor zoonotic disease (NCZD) in 2005-2015 and 13 local center for zoonotic diseases in 1988-2015. Datawas kept in NCZD and National archival authority. For mapping we used Arc View 3.2.ResultsTotally 397 event information of suspicious rodents and other animals was received in NCZD from 8 districtsof Ulaanbaatar city in 2002-2015. Most of information was received from Songinokhairkhan-64.2%district and smallest number was from Nalaikh district-0.3%. 92.2% of them were marmot, 0.1% of themwere marmot raw products for treatment purpose. Totally 1285 animal samples were tested by plaguedisease and the result was negative. Five hundred thirty tree marmots were carried to Ulaanbaatar from10 provinces. In that time plague foci were active and Y.pestis was isolated in provinces which marmotwas carried to Ulaanbaatar.In 1988-2015, totally 257 marmots and animals of 515 event information was received in15 provinces.Including 13.2% of them were birds, 84% of them marmot, 1.6% of them were livestock, 1.2% of themother animals. About 216 marmots were tested by plague. 51.2% of them were detected positive results.We develop conclusion based laboratory investigation result even it need high cost to take earlyprevention and response measures.Conclusion1. It is high risk to spread plague by carrying suspicious animal in urban area. Therefore, it is importantto take early response measures even it high cost. In further, increase cost and support rapid test ofhigh technology.2. To organize rational advertisement and increase knowledge of population about not doing illegalhunting, not selling marmot raw products in urban area, not using marmot raw products for treatmentuse and avoid contact with marmot carcasses.3. It is important to cooperate joint response measures with policeman, inspection agency andveterinary and human health sectors in Mongolia.