Background: A personalized approach to occupational medicine allows specialists to 1 prevent professional hazards such as stress-related depression and anxiety in extreme work environments. Objective: we aim to detect genetic markers of low resilience to stress. Methods: The study cohort included 97 elite athletes and 167 special forces personnel. The research team collected buccal mucosa samples and examined psychological status with the Hospital Anxiety and Depression Scale (HADS). We assessed 35 variants within selected genes that are most often associated with low resilience to stress, anxiety, and depression. Fisher’s Exact test was used to determine nonrandom associations between scores in the HADS scale and the genetic variants. We also trained machine learning models to predict score values from genotyping findings and ranked genetic biomarkers according to their predictive power. Results: High-risk depression profiles included C/T genotype of MTHFR C677T and A/C variant of MTHFR A1298C. Susceptibility to anxiety was associated with several polymorphisms regulating neuroactive substances, immune response, and coagulation. The ML models accurately detect depression or anxiety levels with MAE/ROV of 17.69±1.35 and 17.86±2.09% respectively. Conclusions: The study findings justify a polymorphic nature of anxiety and confirm the immune system's involvement in regulating stress response.

Background: Aging rate is affected by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle and environmental factors. In accelerated aging (AA), biological age exceeds the chronological one. Objective: To undertake a critical reappraisal of the AA concept and to reveal its weaknesses and limitations. Methods: We reviewed over 300 recent articles dealing with physiology of brain aging and pathophysiology of neurodegeneration. Results: (1) Organ systems age at different rates, which interferes with application of the AA concept to individual organs. (2) Aging rate can be decelerated due to individual structure–functional reserves built with cognitive, physical training or pharmacological interventions. (3) The AA concept lacks standardised terminology and methodology. (4) Specific molecular biomarkers (MBM) reflect aging. To consolidate the AA theory, researchers should validate numerous MBM candidates. (5) Aging factors, mechanisms and the exact nature of their biological outcomes are not well understood. Conclusion: Although considered as a perspective theory, the AA concept has serious limitations and it requires an update.

Herein, we examined the effects of weather parameters and individual clinicodemographic risk factors on hemorrhagic stroke (HS) incidence, severity on admission, and disability at discharge in a harsh desert climate. In a retrospective design we studied patients admitted to a stroke unit in Arab Emirates in 2016-2019. With a distributed lag nonlinear model we explored immediate and delayed effects of weather on stroke incidence. Supervised machine learning was used to build models predictive of scores in NIHSS and mRS scales. We assessed model performance by calculating ROC AUC, F1 scores, specificity, and sensitivity. HS risk increased after a significant change in any weather parameter. The risk was reduced below baseline after 1-week adjustment to environmental changes. Climate input from the previous 3 days yielded reliable classification models. Humidex was a better predictor of severity than air temperature, whereas body mass index, age, and time of day at stroke onset were the strongest clinical predictors. Weather parameters before admission were stronger predictors of disease severity than individual clinical factors. We addressed limitations of previous studies by analyzing a full set of climate parameters: ambient temperature, relative humidity, humidex, atmospheric pressure, and wind speed. Predictive models may help to optimize patient management and develop preventative strategies.