Rapid and reversible impairment of episodic memory by a high-fat diet in mice.

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. This work was supported by an EASTBIO BBSRC PhD studentship to F.H.M., L.M.W., C.G., A.C.M., G.W.H. and F.M.C. are supported by Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS).Peer reviewedPublisher PD

Mineralization and nitrification: Archaea dominate ammonia-oxidising communities in grassland soils

In grasslands, N mineralization and nitrification are important processes and are controlled by several factors, including the in situ microbial community composition. Nitrification involves ammonia oxidising archaea (AOA) and bacteria (AOB) and although AOA and AOB co-exist in soils, they respond differently to environmental characteristics and there is evidence of AOA/AOB niche differentiation. Here, we investigated temporal variation in N mineralization and nitrification rates, together with bacterial, archaeal and ammonia-oxidiser communities in grassland soils, on different geologies: clay, Greensand and Chalk. Across geologies, N mineralization and nitrification rates were slower in the autumn than the rest of the year. Turnover times for soil ammonium pools were <24 h, whilst several days for nitrate. In clay soils, bacterial, archaeal, AOA, and AOB communities were clearly distinct from those in Chalk and Greensand soils. Spatially and temporally, AOA were more abundant than AOB. Notably, Nitrososphaera were predominant, comprising 37.4% of archaeal communities, with the vast majority of AOA found in Chalk and Greensand soils. AOA abundance positively correlated with nitrate concentration, whereas AOB abundance correlated with ammonium and nitrite concentrations, suggesting that these N compounds may be potential drivers for AOA/AOB niche differentiation in these grassland soils

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5–40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in &gt;100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P &lt; 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

Author Correction: Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases.

Emmanuelle Souzeau, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this Article. This has now been corrected in both the PDF and HTML versions of the Article

Hemispheric reconfigurations in Northern Amazonia: The ‘Three Guianas’ amid regional change and Brazilian hegemony

© 2016 Southseries Inc., www.thirdworldquarterly.com. Regional and hemispheric reconfigurations in Latin America and the Caribbean are increasingly mediated by Brazilian power, and the engagement of Guyana, Suriname and French Guiana with this emerging context is intriguing. They are tentatively moving away from a Caribbean region with which they are culturally contiguous, towards a South American continent in which they are geographically located. This is partly a reflection of the gradual opening up of the Northern Amazonian space that they share collectively, and also with Venezuela and Brazil. These processes are occurring as cause and effect of Brazil’s emergence as a regional–and even regionally hegemonic–power. With reference to wider debates on regionalism and hegemony, we analyse the uncertain consequences of these shifts

Multimodel Ensembles of Wheat Growth: More Models are Better than One

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry

XUE. Molecular inventory in the inner region of an extremely irradiated Protoplanetary Disk

We present the first results of the eXtreme UV Environments (XUE) James Webb Space Telescope (JWST) program, that focuses on the characterization of planet forming disks in massive star forming regions. These regions are likely representative of the environment in which most planetary systems formed. Understanding the impact of environment on planet formation is critical in order to gain insights into the diversity of the observed exoplanet populations. XUE targets 15 disks in three areas of NGC 6357, which hosts numerous massive OB stars, among which some of the most massive stars in our Galaxy. Thanks to JWST we can, for the first time, study the effect of external irradiation on the inner ($< 10$ au), terrestrial-planet forming regions of proto-planetary disks. In this study, we report on the detection of abundant water, CO, CO$_2$, HCN and C$_2$H$_2$ in the inner few au of XUE 1, a highly irradiated disk in NGC 6357. In addition, small, partially crystalline silicate dust is present at the disk surface. The derived column densities, the oxygen-dominated gas-phase chemistry, and the presence of silicate dust are surprisingly similar to those found in inner disks located in nearby, relatively isolated low-mass star-forming regions. Our findings imply that the inner regions of highly irradiated disks can retain similar physical and chemical conditions as disks in low-mass star-forming regions, thus broadening the range of environments with similar conditions for inner disk rocky planet formation to the most extreme star-forming regions in our Galaxy.Comment: Accepted for publication in ApJ Letters. 20 pages, 7 figure