Intersecting hypersurfaces, topological densities and Lovelock Gravity

Intersecting hypersurfaces in classical Lovelock gravity are studied exploiting the description of the Lovelock Lagrangian as a sum of dimensionally continued Euler densities. We wish to present an interesting geometrical approach to the problem. The analysis allows us to deal most efficiently with the division of space-time into a honeycomb network of cells produced by an arbitrary arrangement of membranes of matter. We write the gravitational action as bulk terms plus integrals over each lower dimensional intersection. The spin connection is discontinuous at the shared boundaries of the cells, which are spaces of various dimensionalities. That means that at each intersection there are more than one spin connections. We introduce a multi-parameter family of connections which interpolate between the different connections at each intersection. The parameters live naturally on a simplex. We can then write the action including all the intersection terms in a simple way. The Lagrangian of Lovelock gravity is generalized so as to live on the simplices as well. Each intersection term of the action is then obtained as an integral over an appropriate simplex. Lovelock gravity and the associated topological (Euler) density are used as an example of a more general formulation. In this example one finds that singular sources up to a certain co-dimensionality naturally carry matter without introducing conical or other singularities in spacetime geometry.Comment: 24 pages, 2 figures, version 4: lengthened introduction, section on explicit junction conditions for intersections added. Accepted in Journal of Geometry and Physic

Implementation of U.K. Earth system models for CMIP6

We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere-land-ocean-sea ice model HadGEM3-GC3.1 and the Earth system model UKESM1 which adds a carbon-nitrogen cycle and atmospheric chemistry to HadGEM3-GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions.We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3-GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation.We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility

Determinants of host susceptibility to murine respiratory syncytial virus (RSV) disease identify a role for the innate immunity scavenger receptor MARCO gene in human infants

AbstractBackgroundRespiratory syncytial virus (RSV) is the global leading cause of lower respiratory tract infection in infants. Nearly 30% of all infected infants develop severe disease including bronchiolitis, but susceptibility mechanisms remain unclear.MethodsWe infected a panel of 30 inbred strains of mice with RSV and measured changes in lung disease parameters 1 and 5days post-infection and they were used in genome-wide association (GWA) studies to identify quantitative trait loci (QTL) and susceptibility gene candidates.FindingsGWA identified QTLs for RSV disease phenotypes, and the innate immunity scavenger receptor Marco was a candidate susceptibility gene; targeted deletion of Marco worsened murine RSV disease. We characterized a human MARCO promoter SNP that caused loss of gene expression, increased in vitro cellular response to RSV infection, and associated with increased risk of disease severity in two independent populations of children infected with RSV.InterpretationTranslational integration of a genetic animal model and in vitro human studies identified a role for MARCO in human RSV disease severity. Because no RSV vaccines are approved for clinical use, genetic studies have implications for diagnosing individuals who are at risk for severe RSV disease, and disease prevention strategies (e.g. RSV antibodies)

Priorities for mitigating greenhouse gas and ammonia emissions to meet UK policy targets

Agriculture is essential for providing food and maintaining food security while concurrently delivering multiple other ecosystem services. However, agricultural systems are generally a net source of greenhouse gases and ammonia. They, therefore, need to substantively contribute to climate change mitigation and net zero ambitions. It is widely acknowledged that there is a need to further reduce and mitigate emissions across sectors, including agriculture to address the climate emergency and emissions gap. This discussion paper outlines a collation of opinions from a range of experts within agricultural research and advisory roles following a greenhouse gas and ammonia emission mitigation workshop held in the UK in March 2022. The meeting identified the top mitigation priorities within the UK’s agricultural sector to achieve reductions in greenhouse gases and ammonia that are compatible with policy targets. In addition, experts provided an overview of what they believe are the key knowledge gaps, future opportunities and co-benefits to mitigation practices as well as indicating the potential barriers to uptake for mitigation scenarios discussed

Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases

Microglial activation plays central roles in neuroinflammatory and neurodegenerative diseases. Positron emission tomography (PET) targeting 18 kDa Translocator Protein (TSPO) is widely used for localising inflammation in vivo, but its quantitative interpretation remains uncertain. We show that TSPO expression increases in activated microglia in mouse brain disease models but does not change in a non-human primate disease model or in common neurodegenerative and neuroinflammatory human diseases. We describe genetic divergence in the TSPO gene promoter, consistent with the hypothesis that the increase in TSPO expression in activated myeloid cells depends on the transcription factor AP1 and is unique to a subset of rodent species within the Muroidea superfamily. Finally, we identify LCP2 and TFEC as potential markers of microglial activation in humans. These data emphasise that TSPO expression in human myeloid cells is related to different phenomena than in mice, and that TSPO-PET signals in humans reflect the density of inflammatory cells rather than activation state.Published versionThe authors thank the UK MS Society for financial support (grant number: C008-16.1). DRO was funded by an MRC Clinician Scientist Award (MR/N008219/1). P.M.M. acknowledges generous support from Edmond J Safra Foundation and Lily Safra, the NIHR Senior Investigator programme and the UK Dementia Research Institute which receives its funding from DRI Ltd., funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK. P.M.M. and D.R.O. thank the Imperial College Healthcare Trust-NIHR Biomedical Research Centre for infrastructure support and the Medical Research Council for support of TSPO studies (MR/N016343/1). E.A. was supported by the ALS Stichting (grant “The Dutch ALS Tissue Bank”). P.M. and B.B.T. are funded by the Swiss National Science Foundation (projects 320030_184713 and 310030_212322, respectively). S.T. was supported by an “Early Postdoc.Mobility” scholarship (P2GEP3_191446) from the Swiss National Science Foundation, a “Clinical Medicine Plus” scholarship from the Prof Dr. Max Cloëtta Foundation (Zurich, Switzerland), from the Jean et Madeleine Vachoux Foundation (Geneva, Switzerland) and from the University Hospitals of Geneva. This work was funded by NIH grants U01AG061356 (De Jager/Bennett), RF1AG057473 (De Jager/Bennett), and U01AG046152 (De Jager/Bennett) as part of the AMP-AD consortium, as well as NIH grants R01AG066831 (Menon) and U01AG072572 (De Jager/St George-Hyslop)

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the fi

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants