This study examines the role of epidemiological analysis and modern preventive approaches in reducing the prevalence and progression of common dental diseases. Particular attention is given to dental caries and periodontal diseases, which remain among the most frequently encountered oral health conditions. The study considers the influence of oral hygiene, dietary habits, irregular dental attendance, socioeconomic factors, and delayed treatment on the development of dental pathology. Epidemiological assessment helps identify high-risk population groups and provides a basis for developing targeted preventive programs. Modern prevention includes regular dental examinations, professional oral hygiene, appropriate fluoride use, dietary counseling, early diagnosis, and individualized risk assessment. The integration of epidemiological monitoring with preventive dental care may contribute to earlier detection of disease, reduction of avoidable complications, and improvement of long-term oral health outcomes.

Исследование посвящено определению современных требований к преподаванию иностранных языков студентам нерусской аудитории. Рассмотрены коммуникативный, компетентностный, личностно ориентированный и цифровой подходы, а также влияние многоязычной среды на формирование иноязычной коммуникативной компетенции.

В статье на основе анализа отечественной и зарубежной литературы рассматриваются клинические и морфологические особенности двух наиболее распространенных донорских источников костной ткани для реконструкции сегментарных дефектов нижней челюсти: гребня подвздошной кости и малоберцовой кости. Показано, что выбор аутотрансплантата должен определяться протяженностью и локализацией дефекта, состоянием воспринимающего ложа и планом последующей дентальной реабилитации.

Ushbu maqolada ChatGPT’ning talabalarda matematik kompetensiyani rivojlantirishdagi o‘rni, undan foydalanish sabablari hamda buning natijasida yuzaga keladigan ta’limiy imkoniyatlar va cheklovlar tahlil qilinadi. Tadqiqot doirasida 150 nafar bakalavriat talabasi o‘rtasida so‘rovnoma o‘tkazildi hamda ChatGPT’ning algebra, matematik analiz, ehtimollik nazariyasi va geometrik isbotlashga oid masalalarni yechishdagi aniqligi eksperimental tarzda sinovdan o‘tkazildi. Natijalar shuni ko‘rsatadiki, ChatGPT algoritmlarga asoslangan va tahliliy masalalarni bajarishda yuqori natija (86–94% aniqlik) ko‘rsatgan bo‘lsa-da, geometrik isbotlash va mantiqiy asoslashni talab qiluvchi masalalarda uning aniqligi sezilarli darajada (61% gacha) pasayadi.

Menstrual cycle disorders are common reproductive health problems that may develop as a result of endocrine, metabolic, gynecological, and functional abnormalities. Early identification of menstrual disturbances is important for preventing reproductive complications and determining the underlying causes. This study aimed to develop and improve a structured screening algorithm for the early detection of menstrual cycle disorders. The proposed approach included assessment of menstrual history, clinical manifestations, risk factors, endocrine and metabolic status, as well as appropriate laboratory and instrumental investigations. The findings demonstrated that menstrual irregularity was associated with several potential risk factors, including increased body weight, polycystic ovary syndrome-related changes, thyroid dysfunction, hyperprolactinemia, metabolic abnormalities, and psychological stress. A three-stage screening algorithm was developed, consisting of initial clinical assessment, risk-factor stratification, and targeted laboratory and instrumental examination.