Repeatability characteristics of insulin response patterns and measures of insulin resistance

Background: Hyperinsulinaemia is emerging as an independent risk factor for metabolic disease, but diagnostic measures are limited. It is plausible that insulin resistance measures, such as homeostatic model assessment (HOMA) type 2 variants, may model hyperinsulinaemia, but repeatability data are limited. Kraft and Hayashi insulin response patterns may not only add value in diagnosing hyperinsulinaemia, but also lack suitable repeatability data. Aim: The aim of this study was to investigate the repeatability of insulin response patterns, and fasting and dynamic measures of insulin resistance, and to determine whether these latter measures can predict the insulin response pattern. Setting: This study was conducted at Auckland University of Technology Millennium Institute’s sports performance laboratories. Methods: Oral glucose (100 g) tolerance tests were conducted weekly on eight people. Six people completed four tests, while two completed at least two tests. Each test assessed insulin resistance and response patterns. Insulin resistance measures included fasting tests (HOMA2, McAuley Index) and a dynamic test (oral glucose insulin sensitivity [OGIS]). The insulin response patterns were assessed with both Kraft and Hayashi methodologies. Repeatability characteristics of ordinal variables were assessed by Bland and Altman methods, while Fleiss’ κ was applied to categorical variables. Results: Fasting measures of insulin resistance recorded poor repeatability (HOMA2) or poor sensitivity (McAuley Index) compared to the dynamic measure (OGIS). Kraft insulin response patterns were more repeatable compared to Hayashi patterns, based on a combination of Fleiss’ κ (0.290 vs. 0.186,) p-value (0.15 vs. 0.798) and 95% confidence intervals. Conclusions: Both hyperinsulinaemia and insulin resistance should be dynamically assessed with a multi-sampled oral glucose tolerance test. Further investigations are required to confirm a preferred methodology

Hyperinsulinemia: Best management practice

Chronic hyperinsulinemia associated with insulin resistance is directly and indirectly associated with many metabolic disorders that contribute to significant morbidity and mortality. Because hyperinsulinemia is not widely recognised as an independent health risk, there are few studies that assess management strategies. Medication management may not address the multiple issues associated with hyperinsulinemia. Lifestyle management includes physical activity, especially high intensity interval training, and dietary management. Reducing carbohydrate quantity and increasing nutrient density are discussed with carbohydrate-restricted and Mediterranean diets conferring additional benefits to a low-fat diet. Physical activity and dietary management provide the foundation for hyperinsulinemia management and may work synergistically. Of these principles, a combination of resistance and high intensity interval training, and carbohydrate restriction provide the two most effective frontline management strategies for managing hyperinsulinemia

Face valid phenotypes in a mouse model of the most common mutation in EEF1A2 related neurodevelopmental disorder, E122K

De novo heterozygous missense mutations in EEF1A2, encoding neuromuscular translation-elongation factor eEF1A2, are associated with developmental and epileptic encephalopathies. We used CRISPR/Cas9 to recapitulate the most common mutation, E122K, in mice. Although E122K heterozygotes were not observed to have convulsive seizures, they exhibited frequent electrographic seizures and EEG abnormalities, transient early motor deficits and growth defects. Both E122K homozygotes and Eef1a2-null mice developed progressive motor abnormalities, with E122K homozygotes reaching humane endpoints by P31. The null phenotype is driven by progressive spinal neurodegeneration; however, no signs of neurodegeneration were observed in E122K homozygotes. The E122K protein was relatively stable in neurons yet highly unstable in skeletal myocytes, suggesting that the E122K/E122K phenotype is instead driven by loss of function in muscle. Nevertheless, motor abnormalities emerged far earlier in E122K homozygotes than in nulls, suggesting a toxic gain of function and/or a possible dominant-negative effect. This mouse model represents the first animal model of an EEF1A2 missense mutation with face-valid phenotypes and has provided mechanistic insights needed to inform rational treatment design.</p

High Elmo1 expression aggravates and low Elmo1 expression prevents diabetic nephropathy

About one-third of patients with type 1 diabetes mellitus develop nephropathy, which often progresses to end-stage renal diseases. The present study demonstrates that below-normal Elmo1 expression in mice ameliorates the albuminuria and glomerular histological changes resulting from long-standing type 1 diabetes, whereas above-normal Elmo1 expression makes both worse. Increasing Elmo1 expression leads to aggravation of oxidative stress markers and enhances the expression of fibrogenic genes. Suppressing Elmo1 action in human patients could be a promising option for treating/preventing the progressive deterioration of renal function in diabetes

Microfluidic qPCR Enables High Throughput Quantification of Microbial Functional Genes but Requires Strict Curation of Primers

Quantification of microbial functional genes enhances predictions of soil biogeochemical process rates, but reliance on low-throughput quantitative PCR (qPCR) limits the scope of ecological studies to a handful of targets. Here, we explore whether microfluidic qPCR (MFQPCR) is a viable high-throughput alternative for functional gene quantification, by evaluating the efficiency, specificity and sensitivity of 29 established and 12 newly designed primer pairs targeting taxonomic, nitrogen-cycling, and hydrocarbon degradation genes in genomic DNA soil extracts, under three different sets of MFQPCR assay conditions. Without curation, commonly-used qPCR primer pairs yielded an extreme range of reaction efficiencies (25.9–100.1%), but when conditions were optimized, MFQPCR produced copy-number estimates comparable to traditional qPCR. To guide microbial soil ecologists considering adoption of MFQPCR, we present suggestions for primer selection, including omission of inosines, degeneracy scores of &lt; 9, amplicon sizes of ≤ 211 bp, and GC content of 32–61%. We conclude that, while the nanoliter reaction volumes, rapid thermocycling and one-size-fits-all reaction conditions of MFQPCR necessitates more stringent primer selection criteria than is commonly applied in soil microbial ecology, the ability to quantify up to 96 targets in 96 samples makes MFQPCR a valuable tool for monitoring shifts in functional community abundances. MFQPCR will particularly suit studies targeting multiple clade-specific functional genes, or when primer design is informed by previous knowledge of the environment

Predicting Chandra CCD Degradation with the Chandra Radiation Model

Not long after launch of the Chandra X-Ray Observatory, it was discovered that the Advanced CCD Imaging Spectrometer (ACIS) detector was rapidly degrading due to radiation. Analysis by Chandra personnel showed that this degradation was due to 10w energy protons (100 - 200 keV) that scattered down the optical path onto the focal plane. In response to this unexpected problem, the Chandra Team developed a radiation-protection program that has been used to manage the radiation damage to the CCDs. This program consists of multiple approaches - scheduled sating of the ACIS detector from the radiation environment during passage through radiation belts, real-time monitoring of space weather conditions, on-board monitoring of radiation environment levels, and the creation of a radiation environment model for use in computing proton flux and fluence at energies that damage the ACIS detector. This radiation mitigation program has been very successful. The initial precipitous increase in the CCDs' charge transfer inefficiency (CTI) resulting from proton damage has been slowed dramatically, with the front-illuminated CCDS having an increase in CTI of only 2.3% per year, allowing the ASIS detector's expected lifetime to exceed requirements. This paper concentrates on one aspect of the Chandra radiation mitigation program, the creation of the Chandra Radiation Model (CRM). Because of Chandra's highly elliptical orbit, the spacecraft spends most of its time outside of the trapped radiation belts that present the severest risks to the ACIS detector. However, there is still a proton flux environment that must be accounted for in all parts of Chandra's orbit. At the time of Chandra's launch there was no engineering model of the radiation environment that could be used in the outer regions of the spacecraft's orbit, so the CRM was developed to provide the flux environment of 100 - 200 keV protons in the outer magnetosphere, magnetosheath, and solar wind regions of geospace. This presentation describes CRM, its role in Chandra operations, and its prediction of the ACIS CTI increase

The mobility of two kinase domains in the Escherichia coli chemoreceptor array varies with signalling state

Motile bacteria sense their physical and chemical environment through highly cooperative, ordered arrays of chemoreceptors. These signalling complexes phosphorylate a response regulator which in turn governs flagellar motor reversals, driving cells towards favourable environments. The structural changes that translate chemoeffector binding into the appropriate kinase output are not known. Here, we apply high-resolution electron cryotomography to visualize mutant chemoreceptor signalling arrays in well-defined kinase activity states. The arrays were well ordered in all signalling states, with no discernible differences in receptor conformation at 2–3 nm resolution. Differences were observed, however, in a keel-like density that we identify here as CheA kinase domains P1 and P2, the phosphorylation site domain and the binding domain for response regulator target proteins. Mutant receptor arrays with high kinase activities all exhibited small keels and high proteolysis susceptibility, indicative of mobile P1 and P2 domains. In contrast, arrays in kinase-off signalling states exhibited a range of keel sizes. These findings confirm that chemoreceptor arrays do not undergo large structural changes during signalling, and suggest instead that kinase activity is modulated at least in part by changes in the mobility of key domains