The long-term reduction of the Aral Sea area has led to an ecological catastrophe and a deterioration in the health of the population. The progressing demographic crisis necessitates research on factors that negatively impact the fertility of the population in the Aral region. To investigate the influence of Aral Sea dust–salt aerosols on rat testicular tissues, we exposed male rats to the inhalation of dust–salt aerosols for 7, 24, 30, 48 and 72 days. The results of the morphometric analysis of the rat testes tissues indicate that aerosols containing salts from the Aral Sea have a detrimental effect on the seminiferous epithelium, causing a depletion of the spermatogenic layer and reduction of seminiferous tubules lumen. The morphological signs of testicular damage in the experimental animal groups included low cellularity of seminiferous tubules, vacuolization of Sertoli cells, and a decrease in the number of Leydig cells in the interstitium. The smallest thickness of the spermatogenic layer and the lowest number of Leydig cells were observed in rats after the longest inhalation exposure to the dust–salt aerosols.

The distribution of the health workforce affects the availability of health service delivery to the public. In practice, the demographic and geographic maldistribution of the health workforce is a long-standing national crisis. In this study, we present an approach based on Functional Principal Component Analysis (FPCA) of data to identify patterns in the availability of health workers across different regions of Kazakhstan in order to forecast their needs up to 2033. FPCA was applied to the data to reduce dimensionality and capture common patterns across regions. To evaluate the forecasting performance of the model, we employed rolling origin cross-validation with an expanding window. The resulting scores were forecasted one year ahead using Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) methods. LSTM showed higher accuracy compared to ARIMA. The use of the FPCA method allowed us to identify national and regional trends in the dynamics of the number of doctors. We identified regions with different growth rates, highlighting where the most and least intensive growth is taking place. Based on the FPSA, we have predicted the need for doctors in each region in the period up to 2033. Our results show that the FPCA can serve as a significant tool for analyzing the situation relating to human resources in healthcare and be used for an approximate assessment of future needs for medical personnel.

Background: A good understanding of the demand for health services requires not only an analysis of the current and historical volume of health care provided but also relies on accurate forecasting of trends in the future. Such trends provide invaluable information for needs assessment, resource planning, facility evaluation and policy formulation. We set the task of assessing the load on the healthcare system of Kazakhstan in the next decade using indicators of general morbidity, outpatient visits, the need for medical personnel and financial costs of medical care. Methods: This study applies a dynamic Markov chain model to forecast population dynamics and ARIMAX method for healthcare demand forecasting. Results: In the next decade, the population of Kazakhstan is expected to grow by an average of 1.4% per year, reaching 23,334,397 people by 2033. The population growth will lead to an increase in the overall morbidity of the population in absolute values. The growth rate for children will be 1.6%, for adults - 0.8% per year. In this regard, the number of visits to medical specialists will increase by approximately 1.5% per year. Therefore, the demand for internists will increase by an average of 4.7% per year. The need for labour and material resources will entail an increase in financial costs. Total costs by 2033 will increase by 11.6% compared to 2023. Conclusions: Understanding the demand for health services requires not only the analysis of past and current health data but also relies on accurate forecasting of future trends. Assessing such trends provides invaluable information for identifying needs, planning resources, evaluating facilities, and formulating policies.

Background and Objectives: Purine-metabolism profiles across distinct thyroid phenotypes remain poorly characterized despite the recognized redox imbalance associated with thyroid dysfunction and autoimmune thyroiditis (AIT). We compared plasma and erythrocyte purine-metabolite profiles, derived purine ratios, and their associations with lipid peroxidation across four thyroid-disease phenotypes and healthy controls. Materials and Methods: This single-center cross-sectional study included 164 participants: hypothyroidism without AIT (n = 31), AIT with hypothyroidism (n = 30), nontoxic nodular goiter with euthyroidism (n = 42), euthyroid AIT (n = 37), and healthy controls (n = 24). Purine metabolites were assessed by direct UV spectrophotometry and expressed in relative extinction units; thiobarbituric acid-reactive substances (TBARS)-derived malondialdehyde (MDA) equivalents were measured in plasma and erythrocytes. Results: Plasma guanine and hypoxanthine were lower in AIT with hypothyroidism than in hypothyroidism without AIT and in euthyroid AIT than in nontoxic nodular goiter. Plasma X/HX and UA/HX were higher in both AIT groups than in controls. Plasma MDA was elevated in all thyroid-disease groups, whereas erythrocyte MDA was highest in hypothyroidism without AIT. Plasma UA/X correlated positively with both plasma and erythrocyte MDA, and plasma UA/HX with plasma MDA, with phenotype-dependent heterogeneity in stratified analyses. Conclusions: Thyroid phenotypes showed distinct compartment-specific purine and lipid-peroxidation patterns rather than a uniform AIT-dependent shift. Purine ratios should be interpreted as indirect, method-specific indices rather than direct measures of metabolic flux or XOR/XO/XDH activity.