Exercise preserves pancreatic β-cell mass and function in obese OLETF rats
Published on: 19th June, 2018
Although exercise has been proposed to be beneficial to type 2 diabetes, its effects on β-cell function and mass remain unclear. In the present study, the effects of long-term swimming training on the function and mass of β-cells in diabetic OLETF rats were examined. At 44 weeks of age after developing diabetes, the OLETF rats were divided into two groups: a control group and an exercise group. The exercise group had a daily swimming for 12 weeks. While not found with the control rats, in the obese OLETF rats, the exercise reduced the weight gain which was associated with improved glucose tolerance and elevated circulating insulin levels as determined by the oral glucose tolerance test and insulin ELISA. The exercise improved plasma total cholesterol and triglyceride levels, and also significantly increased the islet β-cell mass and pancreatic insulin content associated with decreased β-cell apoptosis and elevated activation of the serine/threonine kinase, Akt. The present studies suggest that exercise improves diabetes symptoms via enhancement of the β-cell mass and function through decreasing glucolipotoxicity and reducing β-cell apoptosis by activating Akt in obese OLETF rats.
Long monitoring of Birds of Elssuki Area. Sinnar State, Sudan
Published on: 16th April, 2024
This study aims to make a database of the birds in the area of Elssuki, Sinnar state - Sudan. The period of study spanning from 2008 to 2023 with a mix of methods used to identify bird species in many sites in the locality, these methods include road count, line transects, and direct count besides registering every strange, rare, or unusual single species seen in the area. All these methods are used by different researchers and applied in such studies in Sudan.The study revealed that the area is one of the important areas enriched of birds in Sinnar state of 19 orders 53 families. The total number of species is 129 species. It included all birds; water birds, tree birds, diving birds, dabbling birds, swimming birds, small waders, and passerines which the most. The study concluded that there is a need for comprehensive and regular studies and short and long-term monitoring to identify, classify, and establish a database for Sudan Birds Atlas.
Deep Learning-Powered Genetic Insights for Elite Swimming Performance: Integrating DNA Markers, Physiological Biometrics and Performance Analytics
Published on: 21st March, 2025
The integration of deep learning and genetic analysis has transformed the assessment of elite sports performance, particularly in competitive swimming. This study examines the fusion of deep learning techniques with DNA markers, physiological biometrics, and performance analytics to enhance the prediction and optimization of swimmer performance. A structured dataset comprising genetic sequences, physiological parameters, and biomechanical attributes was utilized to train a neural network model capable of categorizing swimmers based on genetic predisposition and athletic potential. The model achieved high classification accuracy, demonstrating a strong link between genetic markers, physiological traits, and competitive swimming outcomes. The findings emphasize the potential of AI-driven analytics in talent identification, customized training adaptations, and injury prevention. Furthermore, the study highlights the effectiveness of deep learning in analyzing complex genomic and physiological data to generate meaningful insights for performance enhancement. While the results validate the feasibility of using genetic and AI-based models for performance prediction, further studies are needed to broaden dataset diversity, integrate epigenetic influences, and test the model across varied athlete populations. This research contributes to the expanding field of AI-driven sports science and provides a solid foundation for incorporating genomics with deep learning to enhance elite athletic performance.
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