Insulin doseresponse curves for stimulation of splanchnic glucose uptake and suppression of endogenous glucose production differ in nondiabetic humans and are abnormal in people with type 2 diabetes.

To determine whether the insulin dose-response curves for suppression of endogenous glucose production (EGP) and stimulation of splanchnic glucose uptake (SGU) differ in nondiabetic humans and are abnormal in type 2 diabetes, 14 nondiabetic and 12 diabetic subjects were studied. Glucose was clamped at ϳ9.5 mmol/l and endogenous hormone secretion inhibited by somatostatin, while glucagon and growth hormone were replaced by an exogenous infusion. Insulin was progressively increased from ϳ150 to ϳ350 and ϳ700 pmol/l by means of an exogenous insulin infusion, while EGP, SGU, and leg glucose uptake (LGU) were measured using the splanchnic and leg catheterization methods, combined with a [3-3 H]glucose infusion. In nondiabetic subjects, an increase in insulin from ϳ150 to ϳ350 pmol/l resulted in maximal suppression of EGP, whereas SGU continued to increase (P < 0.001) when insulin was increased to ϳ700 pmol/l. In contrast, EGP progressively decreased (P < 0.001) and SGU progressively increased (P < 0.001) in the diabetic subjects as insulin increased from ϳ150 to ϳ700 pmol/l. Although EGP was higher (P < 0.01) in the diabetic than nondiabetic subjects only at the lowest insulin concentration, SGU was lower (P < 0.01) in the diabetic subjects at all insulin concentrations tested. On the other hand, in contrast to LGU and overall glucose disposal, the increment in SGU in response to both increments in insulin did not differ in the diabetic and nondiabetic subjects, implying a right shifted but parallel dose-response curve. These data indicate that the dose-response curves for suppression of glucose production and stimulation of glucose uptake differ in nondiabetic subjects and are abnormal in people with type 2 diabetes. Taken together, these data also suggest that agents that enhance SGU in diabetic patients (e.g. glucokinase activators) are likely to improve glucose tolerance. Diabete

Profiles of glucose metabolism in different prediabetes phenotypes, classified by fasting glycemia, 2-hour OGTT, glycated hemoglobin, and 1-hour OGTT:An IMI DIRECT study

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P &lt; 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P &lt; 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio &gt;2, P &lt; 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.</p

Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes:An IMI-DIRECT study

AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk

Reaction rates and transport in neutron stars

Understanding signals from neutron stars requires knowledge about the transport inside the star. We review the transport properties and the underlying reaction rates of dense hadronic and quark matter in the crust and the core of neutron stars and point out open problems and future directions.Comment: 74 pages; commissioned for the book "Physics and Astrophysics of Neutron Stars", NewCompStar COST Action MP1304; version 3: minor changes, references updated, overview graphic added in the introduction, improvements in Sec IV.A.

Subcellular trafficking of the substrate transporters GLUT4 and CD36 in cardiomyocytes

Cardiomyocytes use glucose as well as fatty acids for ATP production. These substrates are transported into the cell by glucose transporter 4 (GLUT4) and the fatty acid transporter CD36. Besides being located at the sarcolemma, GLUT4 and CD36 are stored in intracellular compartments. Raised plasma insulin concentrations and increased cardiac work will stimulate GLUT4 as well as CD36 to translocate to the sarcolemma. As so far studied, signaling pathways that regulate GLUT4 translocation similarly affect CD36 translocation. During the development of insulin resistance and type 2 diabetes, CD36 becomes permanently localized at the sarcolemma, whereas GLUT4 internalizes. This juxtaposed positioning of GLUT4 and CD36 is important for aberrant substrate uptake in the diabetic heart: chronically increased fatty acid uptake at the expense of glucose. To explain the differences in subcellular localization of GLUT4 and CD36 in type 2 diabetes, recent research has focused on the role of proteins involved in trafficking of cargo between subcellular compartments. Several of these proteins appear to be similarly involved in both GLUT4 and CD36 translocation. Others, however, have different roles in either GLUT4 or CD36 translocation. These trafficking components, which are differently involved in GLUT4 or CD36 translocation, may be considered novel targets for the development of therapies to restore the imbalanced substrate utilization that occurs in obesity, insulin resistance and diabetic cardiomyopathy

Core Outcomes for Colorectal Cancer Surgery: A Consensus Study

Background: Colorectal cancer (CRC) is a major cause of worldwide morbidity and mortality. Surgical treatment is common, and there is a great need to improve the delivery of such care. The gold standard for evaluating surgery is within well-designed randomized controlled trials (RCTs); however, the impact of RCTs is diminished by a lack of coordinated outcome measurement and reporting. A solution to these issues is to develop an agreed standard “core” set of outcomes to be measured in all trials to facilitate cross-study comparisons, meta-analysis, and minimize outcome reporting bias. This study defines a core outcome set for CRC surgery. Methods and Findings: The scope of this COS includes clinical effectiveness trials of surgical interventions for colorectal cancer. Excluded were nonsurgical oncological interventions. Potential outcomes of importance to patients and professionals were identified through systematic literature reviews and patient interviews. All outcomes were transcribed verbatim and categorized into domains by two independent researchers. This informed a questionnaire survey that asked stakeholders (patients and professionals) from United Kingdom CRC centers to rate the importance of each domain. Respondents were resurveyed following group feedback (Delphi methods). Outcomes rated as less important were discarded after each survey round according to predefined criteria, and remaining outcomes were considered at three consensus meetings; two involving international professionals and a separate one with patients. A modified nominal group technique was used to gain the final consensus. Data sources identified 1,216 outcomes of CRC surgery that informed a 91 domain questionnaire. First round questionnaires were returned from 63 out of 81 (78%) centers, including 90 professionals, and 97 out of 267 (35%) patients. Second round response rates were high for all stakeholders (>80%). Analysis of responses lead to 45 and 23 outcome domains being retained after the first and second surveys, respectively. Consensus meetings generated agreement on a 12 domain COS. This constituted five perioperative outcome domains (including anastomotic leak), four quality of life outcome domains (including fecal urgency and incontinence), and three oncological outcome domains (including long-term survival). Conclusion: This study used robust consensus methodology to develop a core outcome set for use in colorectal cancer surgical trials. It is now necessary to validate the use of this set in research practice

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes : an IMI-DIRECT study

Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.Peer reviewe