Modeling the inflammatory response in the hypothalamus ensuing heat stroke: Iterative cycle of model calibration, identifiability analysis, experimental design and data collection

摘要: Heat Stroke (HS) is a life-threatening illness caused by prolonged exposure to heat that causes severe hyperthermia and nervous system abnormalities. The long term consequences of HS are poorly understood deeper insight required find possible treatment strategies. Elevated pro- anti-inflammatory cytokines during recovery suggest play major role in the immune response. In this study, we developed mathematical model understand interactions dynamics hypothalamus, main thermoregulatory center brain. Uncertainty identifiability analysis calibrated parameters revealed non-identifiable due limited amount data. To overcome lack parameters, an iterative cycle optimal experimental design, data collection, re-calibration reduction was applied further informative experiments were suggested. Additionally, new method approximating prior distribution for Bayesian design based on profile likelihood presented.