Disruption of marine habitats by artificial light at night from global coastal megacities

Half of globally significant megacities are situated near the coast, exposing urban marine ecosystems to multiple stressors such as waste-water discharge containing a host of organic and inorganic pollutants, air and noise pollution. In addition to these well recognized sources, artificial light at night (ALAN) pollution is inseparable from cities but poorly quantified in marine ecosystems to date. We have developed a time- and wavelength-resolving hydrological optical model that includes solar (daylight and twilight components), lunar and ALAN source terms and propagates these spectrally through a tidally varying water column using Beer’s Law. Our model shows that for 8 globally distributed cities surface ALAN dosages are up to a factor of 6 greater than moonlight, as ALAN intensities vary little throughout the night, over monthly or seasonal cycles. Moonlight only exceeds ALAN irradiances over the ±3-day period around full moon, and particularly during the brightest moons (mid-latitude winter, at zenith). Unlike the relatively stable surface ALAN, underwater ALAN varies spectrally and in magnitude throughout the night due to tidal cycles. The extent of ALAN in-water attenuation is location-specific, driven by the season, tidal range and cycle, and water clarity. This work highlights that marine ALAN ecosystem pollution is a particularly acute global change issue near some of the largest cities in the world

Current and novel biomarkers of thrombotic risk in COVID-19: a Consensus Statement from the International COVID-19 Thrombosis Biomarkers Colloquium

© Springer Nature Limited 2022. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1038/s41569-021-00665-7Coronavirus disease 2019 (COVID-19) predisposes patients to thrombotic and thromboembolic events, owing to excessive inflammation, endothelial cell activation and injury, platelet activation and hypercoagulability. Patients with COVID-19 have a prothrombotic or thrombophilic state, with elevations in the levels of several biomarkers of thrombosis, which are associated with disease severity and prognosis. Although some biomarkers of COVID-19-associated coagulopathy, including high levels of fibrinogen and d-dimer, were recognized early during the pandemic, many new biomarkers of thrombotic risk in COVID-19 have emerged. In this Consensus Statement, we delineate the thrombotic signature of COVID-19 and present the latest biomarkers and platforms to assess the risk of thrombosis in these patients, including markers of platelet activation, platelet aggregation, endothelial cell activation or injury, coagulation and fibrinolysis as well as biomarkers of the newly recognized post-vaccine thrombosis with thrombocytopenia syndrome. We then make consensus recommendations for the clinical use of these biomarkers to inform prognosis, assess disease acuity, and predict thrombotic risk and in-hospital mortality. A thorough understanding of these biomarkers might aid risk stratification and prognostication, guide interventions and provide a platform for future research.Peer reviewe

Phylogenomic analysis of a 55.1 kb 19-gene dataset resolves a monophyletic Fusarium that includes the Fusarium solani Species Complex

Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user¿s needs and established successful practice. In 2013, the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani species complex (FSSC). Subsequently, this concept was challenged in 2015 by one research group who proposed dividing the genus Fusarium into seven genera, including the FSSC described as members of the genus Neocosmospora, with subsequent justification in 2018 based on claims that the 2013 concept of Fusarium is polyphyletic. Here, we test this claim and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a genus Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students, and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species described as genus Neocosmospora were recombined in genus Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural, and practical taxonomic option availabl

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The vascular genetics of primary Raynaud's phenomenon

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN023260 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Series evaluation of Tweedie exponential dispersion model densities

Exponential dispersion models, which are linear exponential families with a dispersion parameter, are the prototype response distributions for generalized linear models. The Tweedie family comprises those exponential dispersion models with power mean-variance relationships. The normal, Poisson, gamma and inverse Gaussian distributions belong to the Tweedie family. Apart from these special cases, Tweedie distributions do not have density functions which can be written in closed form. Instead, the densities can be represented as infinite summations derived from series expansions. This article describes how the series expansions can be summed in an numerically efficient fashion. The usefulness of the approach is demonstrated, but full machine accuracy is shown not to be obtainable using the series expansion method for all parameter values. Derivatives of the density with respect to the dispersion parameter are also derived to facilitate maximum likelihood estimation. The methods are demonstrated on two data examples and compared with with Box-Cox transformations and extended quasi-likelihoood