English Contract Law and the Great War: the development of a doctrine of frustration

This article examines changes that occurred in English contract law as a result of the demands made upon Great Britain by the Great War. The focus is on the development of the doctrine of frustration in English law. In particular, it is argued that the development of the doctrine of frustration was fashioned from internal legal forces in the form of both existing case law and emergency legislation in response to the demands placed upon the nation by a global war. The way in which the doctrine of frustration developed during the Great War arose as a direct result of the way in which Britain chose to meet the logistical demands created by the way it fought the Great War

The Role of Mitochondria in the Activation/Maintenance of SOCE: Membrane Contact Sites as Signaling Hubs Sustaining Store-Operated Ca2+ Entry

Store-operated Ca2+ entry (SOCE) is a cell signaling pathway essential for immune and muscle function controlled by dynamic interactions between Ca2+-sensing STIM proteins on the endoplasmic reticulum (ER) and Ca2+-permeable ORAI channels on the plasma membrane (PM). STIM-ORAI interactions occur at membrane contact sites (MCS), evolutionarily conserved cellular structures characterized by the close apposition (10-20 nm) between the ER and target membranes that facilitate the exchange of lipids by non-vesicular transport mechanisms. STIM-ORAI interactions were considered to be restricted to ER-PM MCS, but recent evidence indicates that productive interactions take place between ER-bound STIM1 and Ca2+ channels located in intracellular organelles. Interactions between the ER and endosomes or lysosomes regulate the lipid homeostasis of these organelles and the propagation of Ca2+ signals initiated by the release of Ca2+ from acidic stores. Intracellular MCS also regulate the efficiency of phagocytosis, a fundamental cellular process essential for immunity and tissue homeostasis, by ensuring the coordinated opening of Ca2+ channels on phagocytic vacuoles and of Ca2+ release channels on juxtaposed ER stores. In this chapter, we review the current knowledge on the molecular composition and architecture of membrane contact sites that sustain Ca2+ signals at the plasma membrane and in intracellular organelles

The Family Streptomycetaceae

The family Streptomycetaceae comprises the genera Streptomyces, Kitasatospora, and Streptacidiphilus that are very difficult to differentiate both with genotypic and phenotypic characteristics. A separate generic status for Kitasatospora and Streptacidiphilus is questionable. Members of the family can be characterized as non-acid-alcohol-fast actinomycetes that generate most often an extensively branched substrate mycelium that rarely fragments. At maturity, the aerial mycelium forms chains of few to many spores. A large variety of pigments is produced, responsible for the color of the substrate and aerial mycelium. The organisms are chemoorganotrophic with an oxidative type of metabolism and grow within different pH ranges. Streptomyces are notable for their complex developmental cycle and production of bioactive secondary metabolites, producing more than a third of commercially available antibiotics. Antibacterial, antifungal, antiparasitic, and immunosuppressant compounds have been identified as products of Streptomyces secondary metabolism. Streptomyces can be distinguished from other filamentous actinomycetes on the basis of morphological characteristics, in particular by vegetative mycelium, aerial mycelium, and arthrospores. The genus comprises at the time of writing more than 600 species with validated names. 16S rRNA gene sequence-based analysis for species delineation within the Streptomycetaceae is of limited value. The variations within the 16S rRNA genes—even in the variable regions—are too small to resolve problems of species differentiation and to establish a taxonomic structure within the genus. Comprehensive comparative studies including protein-coding gene sequences with higher phylogenetic resolution and genome-based studies are needed to clarify the species delineation within the Streptomycetaceae

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)