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- W4387621009 abstract "Background: Metabolic differences between genders have been observed in humans, with studies reporting differences in body composition, metabolic rates, and response to dietary interventions and how they may affect the risk of cardiovascular disease (CVD) and diabetes. However, most research in CVD models has been conducted exclusively on male mice, resulting in strong gender bias. Moreover, in CVD research investigating differences in hypertension, it is important to note the sexual dimorphisms for these pathologies that result from genetic and hormonal differences. More specifically, age-related CVD rates are lower for women, which has been associated with the protective role of sex steroid hormones in women, which affect the prevalence of metabolic syndrome. However, further research is required to investigate the exact role of these hormones in explaining the lower age-specific CVD rates and the metabolic differences between males and females. Methodology and Result: Adult wild-type C57B6 mice were housed individually in a metabolic cage. We used the indirect calorimetric method to monitor oxygen consumption, carbon dioxide release, respiratory exchange ratio (RER), and energy expenditure of individual mice. Our initial study shows female mice have better volunteer exercise capacity than male mice. Conclusion: This study will address a significant gap in the literature by investigating metabolic differences between genders without gender bias. Our study's findings will provide a foundation for future research in CVD and contribute to developing gender-specific interventions for metabolic disorders." @default.
- W4387621009 created "2023-10-14" @default.
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- W4387621009 date "2023-08-04" @default.
- W4387621009 modified "2023-10-15" @default.
- W4387621009 title "Abstract P3121: Overcoming Gender Bias In Cardiovascular Research Using Mice Models By Monitoring Metabolic Differences Between Genders Using Indirect Calorimetry" @default.
- W4387621009 doi "https://doi.org/10.1161/res.133.suppl_1.p3121" @default.
- W4387621009 hasPublicationYear "2023" @default.
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