Zugl.: Giessen, Universiẗat, Habil.-Schr., 2004.

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Fever has been shown to increase metabolic rate and there is evidence that there is an induction of heat production in brown adipose tissue (BAT). This thesis examines heat production in BAT during fever by measuring GDP-binding to BAT mitochondria and the gene expression of UCP and lipoprotein lipase (LPL). Rats were injected iv. with lipopolysaccharide (LPS; 10 μg/kg body weight) and developed a triphasic fever characterized by an initial decrease in core temperature. Ketoprofen (3 mg/kg body weight), an inhibitor of prostaglandin synthesis, attenuated the increases in core temperature throughout the response but had no effect on the initial hypothermia. Animals made febrile with LPS showed no increase in GDP-binding to BAT mitochondria when compared to saline controls. UCP mRNA and LPL mRNA levels in BAT were also unaffected by the fever. Acute cold exposure induced increases in all of the above parameters. Measurements of the quantity of <I>ob</I> mRNA and LPL mRNA in the WAT of febrile rats revealed no changes in the expression of either gene. Acute cold exposure decreased the levels of <I>ob</I> mRNA, with smaller, but statistically insignificant decreases in LPL mRNA. Genetically obese (<I>fa/fa</I>) Zucker rats and lean controls responded to iv. LPS (10 μg/kg body weight) with a fever characterized by an initial hypothermia. The obese rats had lower levels of UCP mRNA in BAT, but not LPL mRNA, than lean controls. In addition, levels of <I>ob</I> mRNA were considerably elevated in the obese variant but, surprisingly, these differences were not statistically significant. It is concluded that fever does not necessarily involve thermogenesis in BAT and, that changes in energy balance during fever are not manifested as changes in the expression of the <I>ob</I> gene in WAT.

Influential models, capable of predicting human responses to hot and cold environments and potentially suitable for use in practical applications, have been identified and implemented in usable forms onto computers. Six models have been evaluated: the Gagge and Nishi 2-node model of human thermoregulation, the Stolwijk and Hardy 25-node model of human thermoregulation, the Givoni and Goldman model of rectal temperature response, the ISO/DIS 7933 analytical determination and interpretation of thermal stress using calculation of required sweat rate model, the Ringuest 25-node model of human thermoregulation, and the Wissler 225-node model of human thermoregulation. A preliminary evaluation enabled the Ringuest and Wissler models to be eliminated from further investigation. In the case of the Ringuest model this was because of its poor predictions, and for the Wissler model because of practical difficulties with its implementation and use. The remaining models were modified to quantify the insulative effects of clothing by the method considered to be most appropriate, given the current state of knowledge. The modified versions of the models were evaluated by comparing their predictions with human data published previously in the literature. Experimental data were available for a wide range of environmental conditions, with air temperatures ranging from -10 to 50 °C, and with different levels of air movement, humidity, work and clothing. Data for a total of 590 subject exposures were used. The experimental data were grouped into environment categories to enable effects such as the influence of wind or clothing, on the accuracy of the models' predictions to be examined. This categorization also enables advice to be given as to which model is likely to provide the most accurate predictions for a particular combination of environmental conditions. For the majority of environment categories, for which evaluation data were available, at least one of the models was able to predict to an accuracy comparable with the degree of variation that occurred within the data from the human subjects. It may be concluded from the evaluation that it is possible to accurately predict deep body and mean skin temperature responses to cool, neutral, warm and hot environmental conditions. The models' predictions of deep body temperature in the cold are poor. Overall, the 25-node model probably provided the most accurate predictions. The 2-node model was often accurate, but could be poor for exercise conditions. The rectal temperature model usually overestimated deep body temperature, except for very hot or heavy exercise conditions, where its predictions were reasonable. The ISO model's allowable exposure times were often acceptable, but would not have protected subjects for some exercise conditions.