21 resultados para Metabolic flexibility


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Objective: To compare measurements of sleeping metabolic rate (SMR) in infancy with predicted basal metabolic rate (BMR) estimated by the equations of Schofield. Methods: Some 104 serial measurements of SMR by indirect calorimetry were performed in 43 healthy infants at 1.5, 3, 6, 9 and 12 months of age. Predicted BMR was calculated using the weight only (BMR-wo) and weight and height (BMR-wh) equations of Schofield for 0-3-y-olds. Measured SMR values were compared with both predictive values by means of the Bland-Altman statistical test. Results: The mean measured SMR was 1.48 MJ/day. The mean predicted BMR values were 1.66 and 1.47 MJ/day for the weight only and weight and height equations, respectively. The Bland-Altman analysis showed that BMR-wo equation on average overestimated SMR by 0.18 MJ/day (11%) and the BMR-wh equation underestimated SMR by 0.01 MJ/day (1%). However the 95% limits of agreement were wide: - 0.64 to - 0.28MJ/day (28%) for the former equation and - 0.39 to +0.41 MJ/day (27%) for the latter equation. Moreover there was a significant correlation between the mean of the measured and predicted metabolic rate and the difference between them. Conclusions: The wide variation seen in the difference between measured and predicted metabolic rate and the bias probably with age indicates there is a need to measure actual metabolic rate for individual clinical care in this age group.

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in a recent publication, Eriksson et al. [1] explored the relationship between size at birth and resting metabolic rate and body composition in adulthood in a cohort of over 300 men and women. They reported an unexpected finding that people of both sexes who had a low birth weight also had a higher metabolic activity per unit muscle tissue. This conclusion was drawn from an analysis where resting metabolic rate (expressed as kcal/kg fat-free mass) in adulthood was examined relative to the birth weight of the subject. One explanation that they suggested was that the apparent increased activity of muscle tissue resulted from an increased sympathetic drive associated with low birth weight. There may be a less physiological reason for the findings of Eriksson et al. Whilst the data are not given specifically in the text, it can be seen clearly from Fig. 1 in the paper that the mean fat-free mass measured in adulthood increased, in both sexes, from the lightest birth weight group to the heaviest birth weight group when the cohort were divided into tertiles based on birth weight. The crux of the issue is that in many - indeed most - cases, expressing resting energy expenditure as kcal/kg fat-free mass does not totally adjust for fat-free mass [2 - 5], and a bias is introduced so that those who have a higher fat-free mass will tend to have a lower resting energy expenditure when expressed per kg fat-free mass. This bias found when expressing many physiological parameters relative to body size, body weight or body composition has long been known [6], and should be carefully considered by appropriate adjustment and hence analysis.

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Filipe et al. (2001) proposed an anaerobic metabolic model for glycogen-accumulating organisms (GAO) in which the succinate-propionate pathway was used to describe the production of propionyl-CoA. However, propionyl-CoA is only an intermediate product in the above pathway. Stopping at propionyl-CoA instead of propionate (the end product of the pathway) results in the consumption of one ATP from succinate to succinyl-CoA, which was not accounted for in the model of Filipe et al. (2001). This resulted in significant errors in the stoichiometric coefficients in the final metabolic model. A modified model is presented in this communication and is shown to fit the experimental data significantly better than the original model. (C) 2002 Wiley Periodicals, Inc.

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This paper considers the question of which is better: the batch or the continuous activated sludge processes? It is an important question because dissension still exists in the wastewater industry as to the relative merits of each of the processes. A review of perceived differences in the processes from the point of view of two related disciplines, process engineering and biotechnology, is presented together with the results of previous comparative studies. These reviews highlight possible areas where more understanding is required. This is provided in the paper by application of the flexibility index to two case studies. The flexibility index is a useful process design tool that measures the ability of the process to cope with long term changes in operation.

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Glycogen-accumulating organisms (GAO) have the potential to directly compete with polyphosphate-accumulating organisms (PAO) in EBPR systems as both are able to take up VFA anaerobically and grow on the intracellular storage products aerobically. Under anaerobic conditions GAO hydrolyse glycogen to gain energy and reducing equivalents to take up VFA and to synthesise polyhydroxyalkanoate (PHA). In the subsequent aerobic stage, PHA is being oxidised to gain energy for glycogen replenishment (from PHA) and for cell growth. This article describes a complete anaerobic and aerobic model for GAO based on the understanding of their metabolic pathways. The anaerobic model has been developed and reported previously, while the aerobic metabolic model was developed in this study. It is based on the assumption that acetyl-CoA and propionyl-CoA go through the catabolic and anabolic processes independently. Experimental validation shows that the integrated model can predict the anaerobic and aerobic results very well. It was found in this study that at pH 7 the maximum acetate uptake rate of GAO was slower than that reported for PAO in the anaerobic stage. On the other hand, the net biomass production per C-mol acetate added is about 9% higher for GAO than for PAO. This would indicate that PAO and GAO each have certain competitive advantages during different parts of the anaerobic/aerobic process cycle. (C) 2002 Wiley Periodicals, Inc.