Leptin reduces body weight in ob/ob mice by decreasing food intake and increasing energy expenditure; however, the mechanisms by which it does the latter are not known. Here we report that 30% of the weight loss induced by leptin treatment of ob/ob mice is due to changes in energy expenditure. In assessing leptin's effects on specific tissues, we found that hepatic basal metabolic rate was paradoxically decreased 1.7-fold with leptin treatment, which was the result of a 1.6-fold reduction in mitochondrial volume density and altered substrate oxidation kinetics. The altered kinetics were associated with a decrease in protein levels of 2 mitochondrial respiratory chain components-cytochrome c oxidase subunit VIa and cytochrome c oxidase subunit IV. In addition to reduced hepatic metabolism, there was reduced long chain fatty acid production and a 2.5-fold increase in hepatic lipid export, both of which explain the reduced steatosis in leptin-treated animals. These data help clarify the role of the liver in leptin-mediated weight loss and define the mechanisms by which leptin alters hepatic metabolism and corrects steatosis.O besity is a significant global health problem and a leading contributor to morbidity and mortality in the developed and developing world. Obese individuals are at a higher risk for the development of coronary heart disease, diabetes, hypertension, and cancer (1). A fuller understanding of the biological underpinnings of this disorder remains critical for the development of new treatments.Body weight is maintained at a stable level by a tightly controlled balance between energy intake and expenditure. While food intake is well appreciated as contributing to the regulation weight, it is increasingly clear that differences in energy expenditure, basal metabolic rates, and/or adaptive thermogenesis, are also important variables that contribute to obesity (2-4). For example, low energy expenditure is highly predictive of future weight gain (5, 6). Furthermore, weight loss in humans is met with a compensatory decrease in metabolic rate and increase in appetite, which work in concert to resist further changes in weight (7). Pharmacological agents that augment the increase in resting metabolic rate induced by exercise, and thus counteract the compensatory metabolic changes discussed above, could potentially be valuable tools in our battle against morbid obesity (1,8,9).Leptin is an adipocyte-secreted, negative feedback hormone that acts on the hypothalamus to regulate both food intake and energy expenditure (10, 11). Leptin-deficient ob/ob mice show markedly reduced levels of energy expenditure and become obese even when pair fed compared with littermate controls (12, 13). This and other studies have indicated that leptin's effects on caloric intake in treated ob/ob mice only partially account for leptin-mediated weight loss (12,(14)(15)(16). Thus in addition to reducing caloric intake, leptin treatment of ob/ob mice increases total energy expenditure, selectively promotes fat metabolism, and prevents...
Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. As time progresses, the product may fail due to time phenomena such as time-dependent operating conditions, component degradation, etc. The degradation of reliability with time may increase the lifecycle cost due to potential warranty costs, repairs, and loss of market share, affecting the sustainability of environmentally friendly products. In the design for lifecycle cost, we must account for product quality and time-dependent reliability. Quality is a measure of our confidence that the product conforms to specifications as it leaves the factory. Quality is time independent, and reliability is time dependent. This article presents a design methodology to determine the optimal design of time-dependent multiresponse systems by minimizing the cost during the life of the product. The conformance of multiple responses is treated in a series-system fashion. The lifecycle cost includes a production, an inspection, and an expected variable cost. All costs depend on quality and/or reliability. The key to our approach is the calculation of the so-called system cumulative probability of failure. For that, we use an equivalent time-invariant “composite” limit state and a niching genetic algorithm with lazy learning metamodeling. A two-mass vibratory system example and an automotive roller clutch example demonstrate the calculation of the cumulative probability of failure and the design for lifecycle cost.
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