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Background Impaired insulin sensitivity is a key abnormality underlying the development of type 2 diabetes. Measuring insulin sensitivity is therefore of importance in identifying individuals at risk of developing diabetes and for the evaluation of diabetes-focused interventions. A number of measures have been proposed for this purpose. Among these the hyperinsulinemic euglycemic clamp (HEC) is considered the gold standard. However, as the HEC is a costly, time consuming and invasive method requiring trained staff, there is a need for simpler so called surrogate measures. Main message A frequently used approach to evaluate surrogate measures is through correlation with the HEC. We discuss limitations with this method. We suggest other aspects to take into consideration, such as repeatability, reproducibility, systematic biases and discrimination ability. In addition, we focus on three frequently used surrogate measures. We argue that they are one-to-one transformations of each other, and therefore question the benefits of further comparison between them. They give the same results in all rank-based methods, for instance Spearman correlations, Mann-Whitney tests and receiver operating characteristic (ROC) analysis. Conclusions We suggest investigating further aspects than correlation alone when evaluating a surrogate measure of insulin sensitivity. We recommend choosing one of the three surrogate measures HOMA-IR, QUICKI and FIRI for analysis of a clinical study.

Chemically modified mRNA is an efficient, biocompatible modality for therapeutic protein expression. We report a first-time-in-human study of this modality, aiming to evaluate safety and potential therapeutic effects. Men with type 2 diabetes mellitus (T2DM) received intradermal injections of modified mRNA encoding vascular endothelial growth factor A (VEGF-A) or buffered saline placebo (ethical obligations precluded use of a non-translatable mRNA control) at randomized sites on the forearm. The only causally treatment-related adverse events were mild injection-site reactions. Skin microdialysis revealed elevated VEGF-A protein levels at mRNA-treated sites versus placebo-treated sites from about 4–24 hours post-administration. Enhancements in basal skin blood flow at 4 hours and 7 days post-administration were detected using laser Doppler fluximetry and imaging. Intradermal VEGF-A mRNA was well tolerated and led to local functional VEGF-A protein expression and transient skin blood flow enhancement in men with T2DM. VEGF-A mRNA may have therapeutic potential for regenerative angiogenesis. Chemically modified mRNA is a new approach for therapeutic protein expression that could be applied to angiogenesis. Here the authors show in a phase 1 clinical trial that a modified mRNA encoding VEGF-A is well tolerated in patients with type 2 diabetes.

This phase Ib study compared the effects of AZD9977, a selective mineralocorticoid receptor modulator with predicted low hyperkalemia risk, with spironolactone on serum potassium (sK+) in patients with heart failure (HF) with preserved or mildly reduced ejection fraction (EF; ≥40%), and renal impairment. Patients with HF with EF greater than or equal to 40% and estimated glomerular filtration rate of 40–70 ml/min/1.73 m2 were randomized to once‐daily AZD9977 100 mg or spironolactone 25 mg for 14 days, up‐titrated to AZD9977 200 mg or spironolactone 50 mg for another 14 days. The primary end point was relative change (%) in sK+ for AZD9977 versus spironolactone (baseline to day 28). Serum/urinary electrolytes, fractional excretion (FE) of Na+/K+, plasma aldosterone, cortisol, and renin, and safety were also assessed. Sixty‐eight patients were randomized (AZD9977, n = 33; spironolactone, n = 35). Mean (SD) age was 73.0 (8.5) years, 51.5% men. Mean sK+ change from baseline to day 28 was 5.7% (AZD9977) and 4.2% (spironolactone), and 1.5% and 4.2% at day 14. Relative change (95% confidence interval) in sK+ with AZD9977 versus spironolactone was −0.3% (−5.3% to 4.4%; day 28), and 3.4% (−0.8% to 7.5%; day 14). Median increase from baseline in plasma aldosterone at day 28 was 89.8 pmol/L for AZD9977 and 67.4 pmol/L for spironolactone. Median FE of K+ was 12.9% (AZD9977) and 10.1% (spironolactone). AZD9977 was well‐tolerated. No discontinuations due to hyperkalemia occurred with either treatment. Evidence of target engagement for AZD9977 with a favorable safety profile, supports further evaluation of AZD9977 in patients with HF and renal impairment.

In this thesis we study a class of mixture models obtained by mixing extreme value distributions over a positive stable distribution. This depicts a group structure, where the stable distribution is a group specific quantity and a function of the surroundings.The stable mixture models possess a number of interesting characteristics. A key feature of these models is that they are extreme value distributed, unconditionally as well as conditionally on the stable variables. Furthermore, all lower dimensional marginals belong to the same class of models. These properties make the models analytically tractable to work with and their applications comprehensible. Finally we have the flexibility quality. We prove that any multivariate extreme value distribution may be approximated by such a model. Because this class of mixture models has a finite parametrization, which in general multivariate extreme value distributions do not have, we now have a finite parametrization for all multivariate extreme value distributions. This means that, given enough complexity, any multivariate extreme value distribution may be described by our stable mixture models. The flexibility of the models enables us to study the dependence structure in a wide range of multivariate extreme value situations. In an environmental context, extreme values at several nearby points in space or time may have profound effects on climate. We present a number of stable mixture models and derive their bivariate dependencies. This gives us a set of models that enable us to study not only the extremal properties of several processes collectively, but also to in a straightforward way describe their inter-relationships.Finally we investigate extreme precipitation patterns in northern Sweden by fitting stable mixture models to annual precipitation maxima. From our results we are able to calculate risks for landslides.Keywords: multivariate extreme value theory, mixture model, stable variable, dependence measure