Morganhjort1179

Creatine availability in adipose tissue has been shown to have profound effects on thermogenesis and energy balance in mice. However, whether dietary creatine supplementation affects brown adipose tissue (BAT) activation in humans is unclear. In the present study, we report the results of a double-blind, randomized, placebo-controlled, cross-over trial (NCT04086381) in which 14 young, healthy, vegetarian adults, who are characterized by low creatine levels, received 20 g of creatine monohydrate per day or placebo. Participants were eligible if they met the following criteria male or female, white, aged 18-30 years, consuming a vegetarian diet (≥6 months) and body mass index 20-25 kg m-2. BAT activation after acute cold exposure was determined by calculating standard uptake values (SUVs) acquired by [18F]fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. BAT volume (-31.32 (19.32) SUV (95% confidence interval (CI) -73.06, 10.42; P = 0.129)), SUVmean (-0.34 (0.29) SUV (95% CI -0.97, 0.28; P = 0.254)) and SUVmax (-2.49 (2.64) SUV (95% CI -8.20, 3.21; P = 0.362)) following acute cold exposure were similar between placebo and creatine supplementation. No side effects of creatine supplementation were reported; one participant experienced bowel complaints during placebo, which resolved without intervention. Our data show that creatine monohydrate supplementation in young, healthy, lean, vegetarian adults does not enhance BAT activation after acute cold exposure.Nonlinear data visualization methods, such as t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP), summarize the complex transcriptomic landscape of single cells in two dimensions or three dimensions, but they neglect the local density of data points in the original space, often resulting in misleading visualizations where densely populated subsets of cells are given more visual space than warranted by their transcriptional diversity in the dataset. Here we present den-SNE and densMAP, which are density-preserving visualization tools based on t-SNE and UMAP, respectively, and demonstrate their ability to accurately incorporate information about transcriptomic variability into the visual interpretation of single-cell RNA sequencing data. Applied to recently published datasets, our methods reveal significant changes in transcriptomic variability in a range of biological processes, including heterogeneity in transcriptomic variability of immune cells in blood and tumor, human immune cell specialization and the developmental trajectory of Caenorhabditis elegans. Our methods are readily applicable to visualizing high-dimensional data in other scientific domains.Coexisting microbial cells of the same species often exhibit genetic variation that can affect phenotypes ranging from nutrient preference to pathogenicity. Here we present inStrain, a program that uses metagenomic paired reads to profile intra-population genetic diversity (microdiversity) across whole genomes and compares microbial populations in a microdiversity-aware manner, greatly increasing the accuracy of genomic comparisons when benchmarked against existing methods. We use inStrain to profile >1,000 fecal metagenomes from newborn premature infants and find that siblings share significantly more strains than unrelated infants, although identical twins share no more strains than fraternal siblings. Infants born by cesarean section harbor Klebsiella with significantly higher nucleotide diversity than infants delivered vaginally, potentially reflecting acquisition from hospital rather than maternal microbiomes. Genomic loci that show diversity in individual infants include variants found between other infants, possibly reflecting inoculation from diverse hospital-associated sources. inStrain can be applied to any metagenomic dataset for microdiversity analysis and rigorous strain comparison.Single-cell transcriptomic analysis is widely used to study human tumors. Vorinostat HDAC inhibitor However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.Magic-angle twisted bilayer graphene (MATBG) exhibits a range of correlated phenomena that originate from strong electron-electron interactions. These interactions make the Fermi surface highly susceptible to reconstruction when ±1, ±2 and ±3 electrons occupy each moiré unit cell, and lead to the formation of various correlated phases1-4. Although some phases have been shown to have a non-zero Chern number5,6, the local microscopic properties and topological character of many other phases have not yet been determined. Here we introduce a set of techniques that use scanning tunnelling microscopy to map the topological phases that emerge in MATBG in a finite magnetic field. By following the evolution of the local density of states at the Fermi level with electrostatic doping and magnetic field, we create a local Landau fan diagram that enables us to assign Chern numbers directly to all observed phases. We uncover the existence of six topological phases that arise from integer fillings in finite fields and that originate from a cascade of symmetry-breaking transitions driven by correlations7,8.