83 resultados para carbohydrate metabolism

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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OBJECTIVE Low-fat hypocaloric diets reduce insulin resistance and prevent type 2 diabetes in those at risk. Low-carbohydrate, high-fat diets are advocated as an alternative, but reciprocal increases in dietary fat may have detrimental effects on insulin resistance and offset the benefits of weight reduction.

RESEARCH DESIGN AND METHODS We investigated a low-fat (20% fat, 60% carbohydrate) versus a low-carbohydrate (60% fat, 20% carbohydrate) weight reduction diet in 24 overweight/obese subjects ([mean ± SD] BMI 33.6 ± 3.7 kg/m2, aged 39 ± 10 years) in an 8-week randomized controlled trial. All food was weighed and distributed, and intake was calculated to produce a 500 kcal/day energy deficit. Insulin action was assessed by the euglycemic clamp and insulin secretion by meal tolerance test. Body composition, adipokine levels, and vascular compliance by pulse-wave analysis were also measured.

RESULTS Significant weight loss occurred in both groups (P < 0.01), with no difference between groups (P = 0.40). Peripheral glucose uptake increased, but there was no difference between groups (P = 0.28), and suppression of endogenous glucose production was also similar between groups. Meal tolerance–related insulin secretion decreased with weight loss with no difference between groups (P = 0.71). The change in overall systemic arterial stiffness was, however, significantly different between diets (P = 0.04); this reflected a significant decrease in augmentation index following the low-fat diet, compared with a nonsignificant increase within the low-carbohydrate group.

CONCLUSIONS This study demonstrates comparable effects on insulin resistance of low-fat and low-carbohydrate diets independent of macronutrient content. The difference in augmentation index may imply a negative effect of low-carbohydrate diets on vascular risk.

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The long-term impact of dietary carbohydrate type, in particular sucrose, on insulin resistance and the development of diabetes and atherosclerosis is not established. Current guidelines for the healthy population advise restriction of sucrose intake. We investigated the effect of high- versus low-sucrose diet (25 vs. 10%, respectively, of total energy intake) in 13 healthy subjects aged 33 +/- 3 years (mean +/- SE), BMI 26.6 +/- 0.9 kg/m(2), in a randomized crossover design with sequential 6-week dietary interventions separated by a 4-week washout. Weight maintenance, eucaloric diets with identical macronutrient profiles and fiber content were designed. All food was weighed and distributed. Insulin action was assessed using a two-step euglycemic clamp; glycemic profiles were assessed by the continuous glucose monitoring system and vascular compliance by pulse-wave analysis. There was no change in weight across the study. Peripheral glucose uptake and suppression of endogenous glucose production were similar after each diet. Glycemic profiles and measures of vascular compliance did not change. A rise in total and LDL cholesterol was observed. In this study, a high-sucrose intake as part of an eucaloric, weight-maintaining diet had no detrimental effect on insulin sensitivity, glycemic profiles, or measures of vascular compliance in healthy nondiabetic subjects.

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Background: Metabolism by peptidases plays an important role in modulating the levels of biologically-active neuropeptides. The metabolism of the anti-inflammatory neuropeptide calcitonin gene-related peptide (GCRP), but not the pro-inflammatory neuropeptides substance P (SP) and neurokinin A (NKA) by components of the gingival crevicular fluid (GCF), could potentiate the inflammatory process in periodontitis.

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Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.