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David Raubenheimer & Stephen Simpson: Nutritional Geometry & The Protein Leverage Hypothesis
Manage episode 435957730 series 3595107
المحتوى المقدم من Cameron Borg. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Cameron Borg أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
David Raubenheimer is a Professor of Nutritional Ecology at the University of Sydney who specialises in nutritional and appetite regulation. His approach is comparative, using ecological and evolutionary diversity to understand these interactions. David’s studies of insects, fish, birds and a variety of mammals have helped develop a new approach to human nutrition-related problems, such as the dietary causes of obesity. Stephen Simpson is a Professor in the School of Life and Environmental Sciences at the University of Sydney. He has a background in experimental psychology, zoology and nutritional biology. Stephen is one of the world’s foremost entomologists and nutritional biologists, and in 2015 he was made a Companion of the Order of Australia for eminent service to biological and biomedical science.
David and Stephen have been working together for decades on a unifying approach to nutrition and energy balance. Their investigations began with the question of why animals in the wild are so capable of regulating their food intake as to avoid the conditions of excess that humans are experiencing at startling rates. This led them to investigate the impacts of various ratios of macronutrients on food intake in animals from locusts to primates. Their findings led them to formulate the “Protein Leverage Hypothesis”, which broadly states that animals prioritise the consumption of protein and eat various foods until a ‘target’ of protein is met.
David & Stephen's Work:
Obesity: the protein leverage hypothesis
Nutrition, ecology and nutritional ecology: toward an integrated framework
My Work:
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