22 resultados para type 2 fuzzy logic system
Resumo:
AIMS: Lipoprotein lipase (LPL), a pivotal enzyme in lipoprotein metabolism, catalyzes the hydrolysis of triglycerides of very low-density lipoproteins and chylomicrons. Assuming that the variants in the promoter of the LPL gene may be associated with changes in lipid metabolism leading to obesity and type 2 diabetes, we examined the role of promoter variants (-T93G and -G53C) in the LPL gene in an urban South Indian population. METHODS: The study subjects (619 type 2 diabetic and 731 normal glucose-tolerant (NGT) subjects) were chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The polymorphisms were genotyped using polymerase chain reaction-restriction-fragment length polymorphism (PCR-RFLP). Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. RESULTS: The two polymorphisms studied were not in LD. The -T93G was not associated with type 2 diabetes but was associated with obesity. 11.5% of the obese subjects (62/541) had the XG(TG+GG) genotype compared with 6.4% of the nonobese subjects (52/809; P=0.001). The odds ratio for obesity for the XG genotype was 1.766 (95% CI: 1.19-2.63, P=0.005). Subjects with XG genotype also had higher body mass index and waist circumference compared with those with TT genotype. With respect to G53C, subjects with the XC(GC+CC) genotype had 0.527 and 0.531 times lower risk for developing type 2 diabetes and obesity, respectively. CONCLUSIONS: Among Asian Indians, the -T93G SNP of the LPL gene is associated with obesity but not type 2 diabetes, whereas the -G53C SNP appears to be protective against both obesity and type 2 diabetes.
Resumo:
AIMS: The objective of the present investigation was to examine the relationship of three polymorphisms, Thr394Thr, Gly482Ser and +A2962G, of the peroxisome proliferator activated receptor-gamma co-activator-1 alpha (PGC-1alpha) gene with Type 2 diabetes in Asian Indians. METHODS: The study group comprised 515 Type 2 diabetic and 882 normal glucose tolerant subjects chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The three polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Haplotype frequencies were estimated using an expectation-maximization (EM) algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms studied were not in linkage disequilibrium. With respect to the Thr394Thr polymorphism, 20% of the Type 2 diabetic patients (103/515) had the GA genotype compared with 12% of the normal glucose tolerance (NGT) subjects (108/882) (P = 0.0004). The frequency of the A allele was also higher in Type 2 diabetic subjects (0.11) compared with NGT subjects (0.07) (P = 0.002). Regression analysis revealed the odds ratio for Type 2 diabetes for the susceptible genotype (XA) to be 1.683 (95% confidence intervals: 1.264-2.241, P = 0.0004). Age adjusted glycated haemoglobin (P = 0.003), serum cholesterol (P = 0.001) and low-density lipoprotein (LDL) cholesterol (P = 0.001) levels and systolic blood pressure (P = 0.001) were higher in the NGT subjects with the XA genotype compared with GG genotype. There were no differences in genotype or allelic distribution between the Type 2 diabetic and NGT subjects with respect to the Gly482Ser and +A2962G polymorphisms. CONCLUSIONS: The A allele of Thr394Thr (G --> A) polymorphism of the PGC-1 gene is associated with Type 2 diabetes in Asian Indian subjects and the XA genotype confers 1.6 times higher risk for Type 2 diabetes compared with the GG genotype in this population.
Resumo:
Resistant starch (RS) has been shown to beneficially affect insulin sensitivity in healthy individuals and those with metabolic syndrome, but its effects on human type 2 diabetes (T2DM) are unknown. This study aimed to determine the effects of increased RS consumption on insulin sensitivity and glucose control and changes in postprandial metabolites and body fat in T2DM. Seventeen individuals with well-controlled T2DM (HbA1c 46.6±2 mmol/mol) consumed, in a random order, either 40 g of type 2 RS (HAM-RS2) or a placebo, daily for 12 weeks with a 12-week washout period in between. At the end of each intervention period, participants attended for three metabolic investigations: a two-step euglycemic–hyperinsulinemic clamp combined with an infusion of [6,6-2H2] glucose, a meal tolerance test (MTT) with arterio-venous sampling across the forearm, and whole-body imaging. HAM-RS2 resulted in significantly lower postprandial glucose concentrations (P=0.045) and a trend for greater glucose uptake across the forearm muscle (P=0.077); however, there was no effect of HAM-RS2 on hepatic or peripheral insulin sensitivity, or on HbA1c. Fasting non-esterified fatty acid (NEFA) concentrations were significantly lower (P=0.004) and NEFA suppression was greater during the clamp with HAM-RS2 (P=0.001). Fasting triglyceride (TG) concentrations and soleus intramuscular TG concentrations were significantly higher following the consumption of HAM-RS2 (P=0.039 and P=0.027 respectively). Although fasting GLP1 concentrations were significantly lower following HAM-RS2 consumption (P=0.049), postprandial GLP1 excursions during the MTT were significantly greater (P=0.009). HAM-RS2 did not improve tissue insulin sensitivity in well-controlled T2DM, but demonstrated beneficial effects on meal handling, possibly due to higher postprandial GLP1.
Resumo:
Isolated source monitoring recollection deficits indicate that abnormalities in glucose metabolism are not detrimental for global episodic memory processes. This enhances our understanding of how metabolic disorders are associated with memory impairments.
Resumo:
Abnormalities in glucose tolerance such as type 2 diabetes can have demonstrable negative effects on a range of cognitive functions. However, there was no evidence that low GL breakfasts administered acutely could confer benefits for cognitive function (ClincalTrials.gov identifier, NCT01047813).
Resumo:
Background: Stable-isotope ratios of carbon (13C/12C, expressed as δ13C) and nitrogen (15N/14N, or δ15N) have been proposed as potential nutritional biomarkers to distinguish between meat, fish, and plant-based foods. Objective: The objective was to investigate dietary correlates of δ13C and δ15N and examine the association of these biomarkers with incident type 2 diabetes in a prospective study. Design: Serum δ13C and δ15N (‰) were measured by using isotope ratio mass spectrometry in a case-cohort study (n = 476 diabetes cases; n = 718 subcohort) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)–Norfolk population-based cohort. We examined dietary (food-frequency questionnaire) correlates of δ13C and δ15N in the subcohort. HRs and 95% CIs were estimated by using Prentice-weighted Cox regression. Results: Mean (±SD) δ13C and δ15N were −22.8 ± 0.4‰ and 10.2 ± 0.4‰, respectively, and δ13C (r = 0.22) and δ15N (r = 0.20) were positively correlated (P < 0.001) with fish protein intake. Animal protein was not correlated with δ13C but was significantly correlated with δ15N (dairy protein: r = 0.11; meat protein: r = 0.09; terrestrial animal protein: r = 0.12, P ≤ 0.013). δ13C was inversely associated with diabetes in adjusted analyses (HR per tertile: 0.74; 95% CI: 0.65, 0.83; P-trend < 0.001], whereas δ15N was positively associated (HR: 1.23; 95% CI: 1.09, 1.38; P-trend = 0.001). Conclusions: The isotope ratios δ13C and δ15N may both serve as potential biomarkers of fish protein intake, whereas only δ15N may reflect broader animal-source protein intake in a European population. The inverse association of δ13C but a positive association of δ15N with incident diabetes should be interpreted in the light of knowledge of dietary intake and may assist in identifying dietary components that are associated with health risks and benefits.
Resumo:
In order to enhance the quality of care, healthcare organisations are increasingly resorting to clinical decision support systems (CDSSs), which provide physicians with appropriate health care decisions or recommendations. However, how to explicitly represent the diverse vague medical knowledge and effectively reason in the decision-making process are still problems we are confronted. In this paper, we incorporate semiotics into fuzzy logic to enhance CDSSs with the aim of providing both the abilities of describing medical domain concepts contextually and reasoning with vague knowledge. A semiotically inspired fuzzy CDSSs framework is presented, based on which the vague knowledge representation and reasoning process are demonstrated.