A physiological systems approach to modeling and resetting of mouse thermoregulation under heat stress.

Heat stroke (HS) is a serious civilian and military health issue. Due to the limited amount of experimental data available in humans, this study was conducted on a mouse mathematical model fitted on experimental data collected from mice under HS conditions, with the assumption there is good agreement among mammals. Core temperature (T(c)) recovery responses in a mouse model consist of hypothermia and delayed fever during 24 h of recovery that represent potential biomarkers of HS severity. The objective of this study was to develop a simulation model of mouse T(c) responses and identify optimal treatment windows for HS recovery using a three-dimensional predictive heat transfer simulation model. Several bioenergetic simulation variables, including nonlinear metabolic heat production (W/m³), temperature-dependent convective heat transfer through blood mass perfusion (W/m³), and activity-related changes in circadian T(c) were used for model simulation. The simulation results predicted the experimental data with few disparities. Using this simulation model, we tested a series of ambient temperature treatment strategies to minimize hypothermia and delayed fever to accelerate HS recovery. Using a genetic algorithm, we identified eight time segments (ambient temperature = 27, 30, 31, 29, 28, 28, 27, 26°C) of 110 min total duration that optimized HS recovery in our model simulation.