Drag-Reducing Polymers Improve Vascular Hemodynamics and Tissue Oxygen Supply in Mouse Model of Diabetes Mellitus.

Diabetes mellitus (DM) is a chronic metabolic disease characterised by hyperglycaemia and glucose intolerance caused by impaired insulin action and/or defective insulin secretion. Long-term hyperglycaemia leads to various structural and functional microvascular changes within multiple tissues, including the brain, which involves blood-brain barrier alteration, inflammation and neuronal dysfunction. We have shown previously that drag-reducing polymers (DRP) improve microcirculation and tissue oxygen supply, thereby reducing neurologic impairment in different rat models of brain injury. We hypothesised that DRP could improve cerebral and skin microcirculation in the situation of progressive microangiopathies associated with diabetes using a mouse model of diabetes mellitus. Diabetes was induced in C57BL/6 J mice with five daily consecutive intraperitoneal injections of streptozotocin (50 mg/kg/day). Animals with plasma glucose concentrations greater than 250 mg/dL were considered diabetic and were used in the study following four months of diabetes. DRP (2 ppm) was injected biweekly during the last two weeks of the experiment. Cortical and skin (ear) microvascular cerebral blood flow (mCBF) and tissue oxygen supply (NADH) were measured by two-photon laser scanning microscopy (2PLSM). Cerebrovascular reactivity (CVR) was evaluated by measuring changes in arteriolar diameters and NADH (tissue oxygen supply) during the hypercapnia test. Transient hypercapnia was induced by a 60-second increase of CO2 concentration in the inhalation mixture from 0% to 10%. Compared to non-diabetic animals, diabetic mice had a significant reduction in the density of functioning capillaries per mm3 (787 ± 52 vs. 449 ± 25), the linear velocity of blood flow (1.2 ± 0.31 vs. 0.54 ± 0.21 mm/sec), and the tissue oxygen supply (p < 0.05) in both brain and skin. DRP treatment was associated with a 50% increase in all three parameters (p < 0.05). According to the hypercapnia test, CVR was impaired in both diabetic groups but more preserved in DRP mice (p < 0.05). Our study in a diabetic mouse model has demonstrated the efficacy of hemorheological modulation of blood flow by DRP to achieve increased microcirculatory flows and tissue oxygen supply.

Relationship of body fat with insulin resistance and cardiometabolic risk factors among normal glucose-tolerant subjects.

BACKGROUND: The amount of body fat, rather than the amount of excess weight, determines the health risks of obesity, type 2 diabetes mellitus, and cardiovascular disease. AIMS: To look at the association of body fat percentage with cardiometabolic risk factors in subjects with normal glucose tolerance (NGT). SETTINGS AND DESIGN: Cross-section study from the Chennai Urban Rural Epidemiology Study. MATERIALS AND METHODS: Body fat was measured by Beurer body fat analyzer. Metabolic syndrome (MS) was diagnosed based on modified ATPIII guidelines. STATISTICAL ANALYSIS: Student's t test or one-way ANOVA (with Tukey's HSD) was used to compare groups for continuous variables. RESULTS: Body mass index, waist circumference, systolic and diastolic blood pressure, HOMA IR, serum cholesterol, and LDL cholesterol increased significantly with increasing tertiles of body fat (P<0.001). There was a linear increase in the percentage of body fat with increase in number of components of MS (no metabolic abnormality: 25 ± 11, one metabolic abnormality: 28 ± 10, two metabolic abnormalities: 33 ± 8, and three and more metabolic abnormalities: 35 ± 7) (P<0.001). Regression models showed significant association of body fat with MS after adjusting for age, gender, insulin resistance, and glycated hemoglobin (Odds ratio: 1.04, 95% confidence interval: 1.04 - 1.08, P<0.001). In linear regression analysis, body fat showed a significant association with insulin resistance after adjusting for age, gender, and glycated hemoglobin (ß=0.030, P<0.001). CONCLUSIONS: A significant association exists between body fat, MS, and cardiometabolic risk factors even among subjects with NGT.