1a.Objectives (from AD-416):
ARS and the Cooperator are interested in better understanding how diet and lifestyle can contribute to regulating energy substrate utilization and the prevention of obesity and diabetes. The objective of this cooperative activity is to examine the relationship of physical activity to fuel management and glucose regulation. Ambulatory monitoring (AM) methodologies and mathematical modeling of physiological processes used in this project can provide important information for the study of these national health problems.
1b.Approach (from AD-416):
Both parties are involved in independent research projects which examine the relationship of specific metabolic parameters to fuel use by the individual and the development of methods to assess current status of fuel stores in free-living humans. The objective of this cooperation is the developmet of mathematical models and data processing routines which relate real-time measurement of relevant metabolic parameters to fuel metabolism and in particular glucose regulation. The parties agree that meeting the objectives of this project will strengthen and enhance ongoing research within the scope of this agreement.
Through this collaboration, we are developing advanced mathematical models to predict the water and metabolic fuel requirements of physically active humans. In a cohort of older women, we measured instantaneous substrate oxidation and compared the impaired glucose tolerance state and the euglycemic state. Using room-size calorimeter during a 48 hour period, the subjects performed three bouts of postprandial exercise on the second day of measurement. Instantaneous gas exchange rates were estimated along with the instantaneous respiratory quotient (RQ) for the whole 48-hour experiment. The relative dynamics of oxygen consumption and RQ showed a greater reliance on the carbohydrate as energy source in the dysglycemic state compared to the euglycemic state. Also, the rate of glucose mobilization, quantified as the time lag between peaks in oxygen consumption and peaks in RQ, was found to be higher in the euglycemic state. We are also developing a model for real-time monitoring of heat flux. We used the Equivital physiologic monitoring system (Hidalgo Limited, UK) to collect core temperature and heart rate (HR) data in order to develop and test our new algorithm. The core temperature data were collected using a telemetry pill (VitalSense, Respironics, USA). The algorithm uses the antecedent samples of core temperature along with the current readings of the heart rate to predict the core temperature signal 20 minutes ahead in real time. We compared the performance of the new algorithm with the previously developed auto regressive algorithm and found that the prediction time lag is reduced by 50% from 10 to 5 minutes.