Role of surface friction on shallow nonprecipitating convection

The role of surface friction on shallow nonprecipitating convection is investigated using a series of large-eddy simulations with varying surface friction velocity and with a cloud identification algorithm. As surface friction intensifies, convective rolls dominate over convective cells and secondary overturning circulation becomes stronger in the subcloud layer, thus transporting more moisture upward and more heat downward between the subcloud and cloud layers. Identifying individual clouds, using the identification algorithm based on a three-dimensional topological analysis, reveals that intensified surface friction increases the number of clouds and the degree of tilting in the downstream direction. Highly intensified surface friction increases wind shear across the cloud base and induces cloud tilting, which leads to a vertically parabolic profile of liquid water mixing ratio instead of the classical two-layer structure (conditionally unstable and trade inversion layers). Furthermore, cloud tilting induces more cloud cover and more cloud mass flux much above the cloud base (e.g. 0.8 km 1.2 km) because of increased lateral entrainment rate. Similarly, profiles of directly measured entrainment and detrainment rates show that detrainment in the lower cloud layer becomes smaller with stronger surface friction

Molecular characterization of projection neuron subtypes in the mouse olfactory bulb

Projection neurons (PNs) in the mammalian olfactory bulb (OB) receive input from the nose and project to diverse cortical and subcortical areas. Morphological and physiological studies have highlighted functional heterogeneity, yet no molecular markers have been described that delineate PN subtypes. Here, we used viral injections into olfactory cortex and fluorescent nucleus sorting to enrich PNs for high-throughput single nucleus and bulk RNA deep sequencing. Transcriptome analysis and RNA in situ hybridization identified distinct mitral and tufted cell populations with characteristic transcription factor network topology, cell adhesion and excitability-related gene expression. Finally, we describe a new computational approach for integrating bulk and snRNA-seq data, and provide evidence that different mitral cell populations preferentially project to different target regions. Together, we have identified potential molecular and gene regulatory mechanisms underlying PN diversity and provide new molecular entry points into studying the diverse functional roles of mitral and tufted cell subtypes

Metabolic syndrome and risk of incident diabetes: findings from the European Prospective Investigation into Cancer and Nutrition-Potsdam Study

<p>Abstract</p> <p>Background</p> <p>Several aspects concerning the relationship between the metabolic syndrome and incident diabetes are incompletely understood including the magnitude of the risk estimate, potential gender differences in the associations between the metabolic syndrome and incident diabetes, the associations between the components of the metabolic syndrome and incident diabetes, and whether the metabolic syndrome provides additional prediction beyond its components. To shed light on these issues, we examined the prospective association between the metabolic syndrome defined by the National Cholesterol Education Program (NCEP) and International Diabetes Federation (IDF) and diabetes.</p> <p>Methods</p> <p>We used data for 2796 men and women aged 35–65 years from the European Prospective Investigation into Cancer and Nutrition-Potsdam Study followed for an average of 6.9 years. This analysis employed a case-cohort design that included 697 participants who developed diabetes and 2099 participants who did not. Incident diabetes was identified on the basis of self-reports and verified by contacting the patient's attending physician.</p> <p>Results</p> <p>The adjusted hazard ratio for the NCEP definition was 4.62 (95% confidence interval [CI]: 3.90–5.48) and that for the IDF definition was 4.59 (95% CI: 3.84–5.50). The adjusted hazard ratios for the NCEP but not IDF definition were higher for women than men. When participants who had no cardiometabolic abnormalities were used as the reference group for the NCEP definition, the adjusted hazard ratio for having 3 or more abnormalities increased to 22.50 (95% CI: 11.21–45.19). Of the five components, abdominal obesity and hyperglycemia were most strongly associated with incident diabetes.</p> <p>Conclusion</p> <p>In this study population, both definitions of the metabolic syndrome provided similar estimates of relative risk for incident diabetes. The increase in risk for participants with the metabolic syndrome according to the NCEP definition was very large when contrasted with the risk among those who had no cardiometabolic abnormalities.</p

Prediction of circulating adipokine levels based on body fat compartments and adipose tissue gene expression

BACKGROUND: Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels. OBJECTIVES: To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine plasma concentrations of the adipokines adiponectin, leptin, soluble leptin receptor, resistin, interleukin 6, and fatty acid-binding protein 4 (FABP4). METHODS: We performed a cross-sectional analysis of 156 participants from the EPIC Potsdam cohort study and analyzed multiple regression models and partial correlation coefficients. RESULTS: For leptin and FABP4 concentrations, 81 and 45% variance were explained by SAT mass, VAT mass, and gene expression in SAT in multivariable regression models. For the remaining adipokines, AT mass and gene expression explained <16% variance of plasma concentrations. Gene expression in SAT was a less important predictor compared to AT mass. SAT mass was a better predictor than VAT mass for leptin (partial correlation r = 0.81, 95% confidence interval 0.75–0.86, vs. r = 0.58, 95% confidence interval 0.46–0.67), while differences between AT compartments were small for the other adipokines. CONLUSIONS: While plasma levels of leptin and FABP4 can be explained in a large and medium part by the amount of AT and SAT gene expression, surprisingly, these predictors explained only little variance for all other investigated adipokines