Angle selective backscattered electron contrast in the low-voltage scanning electron microscope: Simulation and experiment for polymers.

Recently developed detectors can deliver high resolution and high contrast images of nanostructured carbon based materials in low voltage scanning electron microscopes (LVSEM) with beam deceleration. Monte Carlo Simulations are also used to predict under which exact imaging conditions purely compositional contrast can be obtained and optimised. This allows the prediction of the electron signal intensity in angle selective conditions for back-scattered electron (BSE) imaging in LVSEM and compares it to experimental signals. Angle selective detection with a concentric back scattered (CBS) detector is considered in the model in the absence and presence of a deceleration field, respectively. The validity of the model prediction for both cases was tested experimentally for amorphous C and Cu and applied to complex nanostructured carbon based materials, namely a Poly(N-isopropylacrylamide)/Poly(ethylene glycol) Diacrylate (PNIPAM/PEGDA) semi-interpenetration network (IPN) and a Poly(3-hexylthiophene-2,5-diyl) (P3HT) film, to map nano-scale composition and crystallinity distribution by avoiding experimental imaging conditions that lead to a mixed topographical and compositional contrast.

Proinsulin-to-C-peptide ratio versus proinsulin-to-insulin ratio in the prediction of incident diabetes: the Insulin Resistance Atherosclerosis Study (IRAS).

AIMS: Associations of proinsulin-to-insulin ratios with incident type 2 diabetes have been inconsistent. The use of C-peptide as the denominator in the ratio may allow for better prediction because C-peptide concentration is not affected by hepatic insulin clearance. The objective of this paper was to compare fasting intact and split proinsulin-to-insulin ratios (PI/I, SPI/I) with intact and split proinsulin-to-C-peptide ratios (PI/C-pep, SPI/C-pep) in the prediction of type 2 diabetes. METHODS: Prospective data on 818 multi-ethnic adults without diabetes at baseline from the Insulin Resistance Atherosclerosis Study (IRAS) were used. Insulin sensitivity (S(I)) and acute insulin response (AIR) were determined from frequently sampled intravenous glucose tolerance tests, and fasting intact and split proinsulin were measured using specific two-site monoclonal antibody-based immunoradiometric assays. Associations of proinsulin ratios with type 2 diabetes were determined using logistic regression and differences in prediction were assessed by comparing areas under the receiver operating characteristic curve (AROCs). RESULTS: In logistic regression analyses, PI/C-pep and SPI/C-pep were more strongly associated with incident type 2 diabetes (n = 128) than PI/I and SPI/I, and were significantly better predictors of diabetes in AROC analyses (PI/C-pep = 0.662 vs PI/I = 0.603, p = 0.02; SPI/C-pep = 0.690 vs SPI/I = 0.631, p = 0.01). Both PI/C-pep and SPI/C-pep were associated with type 2 diabetes after adjustment for age, sex, ethnicity, waist circumference, impaired glucose tolerance, lipids and S(I). Both PI/C-pep and SPI/C-pep were significantly associated with incident type 2 diabetes in models that included AIR. CONCLUSIONS: Proinsulin-to-C-peptide ratios were stronger predictors of diabetes in comparison with proinsulin-to-insulin ratios. These findings support the use of C-peptide as the denominator for proinsulin ratios, to more accurately reflect the degree of disproportional hyperproinsulinaemia.

Associations between the intake of caffeinated and decaffeinated coffee and measures of insulin sensitivity and beta cell function.

AIMS/HYPOTHESIS: Although protective relationships between coffee consumption and type 2 diabetes mellitus have consistently been observed, few studies have examined the relationships between coffee consumption and underlying pathophysiological defects that characterise diabetes aetiology. The aim of this study was to explore the associations between caffeinated and decaffeinated coffee consumption and measures of insulin sensitivity and secretion. METHODS: The study population included 954 multi-ethnic non-diabetic adults from the Insulin Resistance Atherosclerosis Study (IRAS). Multiple regression analyses were performed to examine the cross-sectional relationships between caffeinated and decaffeinated coffee intake and insulin sensitivity and acute insulin response, measured by a frequently sampled intravenous glucose tolerance test, 2 h postload glucose measured by OGTT, fasting insulin, and proinsulin to C-peptide ratios. RESULTS: Caffeinated coffee intake was positively associated with insulin sensitivity (ß = 0.054; SE = 0.026; p = 0.04) and inversely related to 2 h postload glucose (ß = -0.37; SE = 0.10; p = 0.0003) in fully adjusted models. Caffeinated coffee intake was not associated with acute insulin response or proinsulin ratios. Decaffeinated coffee intake was inversely related to 2 h postload glucose (ß = -0.47; SE = 0.18; p = 0.0096) and positively related to acute insulin response (ß = 0.191; SE = 0.077; p = 0.0132). Decaffeinated coffee intake was inversely related to the ratios of both intact and split proinsulin to C-peptide (ß = -0.150; SE = 0.061; p = 0.0148; ß = -0.254; SE = 0.068; p = 0.0002, respectively). CONCLUSIONS/INTERPRETATION: In this cross-sectional study, caffeinated coffee was positively related to insulin sensitivity and decaffeinated coffee was favourably related to measures of beta cell function. These results provide pathophysiological insight as to how coffee could impact the risk of type 2 diabetes mellitus.