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To control the evolution of a pandemic such as COVID-19, knowing the conditions under which the pathogen is being transmitted represents a critical issue, especially when implementing protection strategies like social distancing and face masks wearing. For viruses and bacteria that spread via airborne and/or droplet pathways, this requires understanding how saliva droplets evolve over time after their expulsion by speaking or coughing. Within this context, the transition from saliva droplets to solid residues, due to water evaporation, is studied here both experimentally, considering the saliva from 5 men and 5 women, and via numerical modeling to accurately predict the dynamics of this process. The model assumes saliva to be a binary water/salt mixture and is validated against experimental results using saliva droplets that are suspended in an ultrasound levitator. We demonstrate that droplets with an initial diameter smaller than 21 μm will produce a solid residue that would be considered an aerosol of <5 μm diameter within less than 2 second (for any relative humidity less than 80% and/or any temperature greater than 20 °C). Finally, the model developed here accounts for the influence of the saliva composition, relative humidity and ambient temperature on droplet drying. Thus, the travel distance prior to becoming a solid residue can be deduced. We found that saliva droplets of initial size below 80 μm, which corresponds to the vast majority of speech and cough droplets, will become solid residues prior to touching the ground when expelled from a height of 160 cm.

Cholesterol has been shown to affect the extent of coronavirus binding and fusion to cellular membranes. The severity of Covid-19 infection is also known to be correlated with lipid disorders. Furthermore, the levels of both serum cholesterol and high-density lipoprotein (HDL) decrease with Covid-19 severity, with normal levels resuming once the infection has passed. Here we demonstrate that the SARS-CoV-2 spike (S) protein interferes with the function of lipoproteins, and that this is dependent on cholesterol. In particular, the ability of HDL to exchange lipids from model cellular membranes is altered when co-incubated with the spike protein. Additionally, the S protein removes lipids and cholesterol from model membranes. We propose that the S protein affects HDL function by removing lipids from it and remodelling its composition/structure. Graphical abstract

Acute flaccid myelitis; Enterovirus D68; Surveillance Mielitis flàcida aguda; Enterovirus D68; Vigilància Mielitis flácida aguda; Enterovirus D68; Vigilancia We report a rapid increase in enterovirus D68 (EV-D68) infections, with 139 cases reported from eight European countries between 31 July and 14 October 2021. This upsurge is in line with the seasonality of EV-D68 and was presumably stimulated by the widespread reopening after COVID-19 lockdown. Most cases were identified in September, but more are to be expected in the coming months. Reinforcement of clinical awareness, diagnostic capacities and surveillance of EV-D68 is urgently needed in Europe.

International audience; The influenza D virus (IDV) was first identified and characterized in 2011. Considering the virus' zoonotic potential, its genome nature (segmented RNA virus), its worldwide circulation in livestock and its role in bovine respiratory disease, an increased interest is given to IDV. However, few data are available on drivers of emergence of IDV. We first listed fifty possible drivers of emergence of IDV in ruminants and swine. As recently carried out for COVID-19 in pets (Transboundary and Emerging Diseases, 2020), a scoring system was developed per driver and scientific experts (N = 28) were elicited to (a) allocate a score to each driver, (b) weight the drivers' scores within each domain and (c) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order. Drivers with comparable likelihoods to play a role in the emergence of IDV in ruminants and swine in Europe were grouped using a regression tree analysis. Finally, the robustness of the expert elicitation was verified. Eight drivers were ranked with the highest probability to play a key role in the emergence of IDV: current species specificity of the causing agent of the disease; influence of (il)legal movements of live animals (ruminants, swine) from neighbouring/European Union member states and from third countries for the disease to (re-)emerge in a given country; detection of emergence; current knowledge of the pathogen; vaccine availability; animal density; and transport vehicles of live animals. As there is still limited scientific knowledge on the topic, expert elicitation of knowledge and multi-criteria decision analysis, in addition to clustering and sensitivity analyses, are very important to prioritize future studies, starting from the top eight drivers. The present methodology could be applied to other emerging animal diseases.

The Canada Research Chairs program provided funding for the core writing team. Field research funding was provided by A.G. Leventis Foundation; Agence Nationale de la Recherche, [grant number ANR-18-32–0010CE-01 (JCJC PEPPER)]; Agencia Estatal de Investigaci; Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (ARDITI), [grant number M1420-09-5369-FSE-000002]; Alan Peterson; ArcticNet; Arkadaşlar; Army Corp of Engineers; Artificial Reef Program; Australia's Integrated Marine Observing System (IMOS), National Collaborative; Research Infrastructure Strategy (NCRIS), University of Tasmania; Australian Institute of Marine Science; Australian Research Council, [grant number LP140100222]; Bai Xian Asia Institute; Batubay Özkan; BC Hydro Fish and Wildlife Compensation Program; Ben-Gurion University of the Negev; Bertarelli Foundation; Bertarelli Programme in Marine Science; Bilge Bahar; Bill and Melinda Gates Foundation; Biology Society of South Australia; Boston University; Burak Över; California State Assembly member Patrick O'Donnell; California State University Council on Ocean Affairs, Science & Technology; California State University Long Beach; Canada Foundation for Innovation (Major Science Initiative Fund and funding to Oceans Network Canada), [grant number MSI 30199 for ONC]; Cape Eleuthera Foundation; Centre National d'Etudes Spatiales; Centre National de la Recherche Scientifique; Charles Darwin Foundation, [grant number 2398]; Colombian Institute for the Development of Science and Technology (COLCIENCIAS), [grant number 811–2018]; Colombian Ministry of Environment and Sustainable Development, [grant number 0041–2020]; Columbia Basin Trust; Commission for Environmental Cooperation; Cornell Lab of Ornithology; Cultural practices and environmental certification of beaches, Universidad de la Costa, Colombia, [grant number INV.1106–01–002-15, 2020–21]; Department of Conservation New Zealand; Direction de l'Environnement de Polynésie Française; Disney Conservation Fund; DSI-NRF Centre of; Excellence at the FitzPatrick Institute of African Ornithology; Ecology Project International; Emin Özgür; Environment and Climate Change Canada; European Community: RTD programme - Species Support to Policies; European Community's Seventh Framework Programme; European Union; European Union's Horizon 2020 research and innovation programme, Marie Skłodowska-Curie, [grant number 798091, 794938]; Faruk Eczacıbaşı; Faruk Yalçın Zoo; Field research funding was provided by King Abdullah University of Science and Technology; Fish and Wildlife Compensation Program; Fisheries and Oceans Canada; Florida Fish and Wildlife Conservation Commission, [grant numbers FWC-12164, FWC-14026, FWC-19050]; Fondo Europeo de Desarrollo Regional; Fonds québécois de la recherche nature et technologies; Foundation Segré; Fundação para a Ciência e a Tecnologia (FCT Portugal); Galapagos National Park Directorate research, [grant number PC-41-20]; Gordon and Betty Moore Foundation, [grant number GBMF9881 and GBMF 8072]; Government of Tristan da Cunha; Habitat; Conservation Trust Foundation; Holsworth Wildlife Research Endowment; Institute of Biology of the Southern Seas, Sevastopol, Russia; Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; Instituto Nacional de Pesquisas Espaciais (INPE), Brazil; Israeli Academy of Science's Adams Fellowship; King Family Trust; Labex, CORAIL, France; Liber Ero Fellowship; LIFE (European Union), [grant number LIFE16 NAT/BG/000874]; María de Maeztu Program for Units of Excellence in R&D; Ministry of Science and Innovation, FEDER, SPASIMM,; Spain, [grant number FIS2016–80067-P (AEI/FEDER, UE)]; MOE-Korea, [grant number 2020002990006]; Mohamed bin Zayed Species Conservation Fund; Montreal Space for Life; National Aeronautics and Space Administration (NASA) Earth and Space Science Fellowship Program; National Geographic Society, [grant numbers NGS-82515R-20]; National Natural Science Fund of China; National Oceanic and Atmospheric Administration; National Parks Board, Singapore; National Science and Technology Major Project of China; National Science Foundation, [grant number DEB-1832016]; Natural Environment Research Council of the UK; Natural Sciences and Engineering Research Council of Canada (NSERC), Alliance COVID-19 grant program, [grant numbers ALLRP 550721–20, RGPIN-2014-06229 (year: 2014), RGPIN-2016-05772 (year: 2016)]; Neiser Foundation; Nekton Foundation; Network of Centre of Excellence of Canada: ArcticNet; North Family Foundation; Ocean Tracking Network; Ömer Külahçıoğlu; Oregon State University; Parks Canada Agency (Lake Louise, Yoho, and Kootenay Field Unit); Pew Charitable Trusts; Porsim Kanaf partnership; President's International Fellowship Initiative for postdoctoral researchers Chinese Academy of Sciences, [grant number 2019 PB0143]; Red Sea Research Center; Regional Government of the Azores, [grant number M3.1a/F/025/2015]; Regione Toscana; Rotary Club of Rhinebeck; Save our Seas Foundation; Science & Technology (CSU COAST); Science City Davos, Naturforschende Gesellschaft Davos; Seha İşmen; Sentinelle Nord program from the Canada First Research Excellence Fund; Servizio Foreste e Fauna (Provincia Autonoma di Trento); Sigrid Rausing Trust; Simon Fraser University; Sitka Foundation; Sivil Toplum Geliştirme Merkezi Derneği; South African National Parks (SANParks); South Australian Department for Environment and Water; Southern California Tuna Club (SCTC); Spanish Ministry for the Ecological Transition and the Demographic Challenge; Spanish Ministry of Economy and Competitiveness; Spanish Ministry of Science and Innovation; State of California; Sternlicht Family Foundation; Suna Reyent; Sunshine Coast Regional Council; Tarea Vida, CEMZOC, Universidad de Oriente, Cuba, [grant number 10523, 2020]; Teck Coal; The Hamilton Waterfront Trust; The Ian Potter Foundation, Coastwest, Western Australian State NRM; The Red Sea Development Company; The Wanderlust Fund; The Whitley Fund; Trans-Anatolian Natural Gas Pipeline; Tula Foundation (Hakai Institute); University of Arizona; University of Pisa; US Fish and Wildlife Service; US Geological Survey; Valencian Regional Government; Vermont Center for Ecostudies; Victorian Fisheries Authority; VMRC Fishing License Fund; and Wildlife Warriors Worldwide The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence. However, negative effects of lockdown on conservation also emerged, as confinement resulted in some park officials being unable to perform conservation, restoration and enforcement tasks, resulting in local increases in illegal activities such as hunting. Overall, there is a complex mixture of positive and negative effects of the pandemic lockdown on nature, all of which have the potential to lead to cascading responses which in turn impact wildlife and nature conservation. While the net effect of the lockdown will need to be assessed over years as data becomes available and persistent effects emerge, immediate responses were detected across the world. Thus initial qualitative and quantitative data arising from this serendipitous global quasi-experimental perturbation highlights the dual role that humans play in threatening and protecting species and ecosystems. Pathways to favorably tilt this delicate balance include reducing impacts and increasing conservation effectiveness 18 pages, 5 figures, supplementary data https://doi.org/10.1016/j.biocon.2021.109175.-- The data supporting the findings of this study are available in the Supplementary Materials (Appendix 3–5, Table A3-A5). Raw datasets (where available) and results summary tables for each analysis of human mobility and empirical datasets are deposited in a github repository: https://github.com/rjcommand/PAN-Environment With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S Peer reviewed

On October 2020, the US Food and Drug Administration (FDA) approved remdesivir as the first drug for the treatment of coronavirus disease 2019 (COVID-19), increasing remdesivir prescriptions worldwide. However, potential cardiovascular (CV) toxicities associated with remdesivir remain unknown. We aimed to characterize the CV adverse drug reactions (ADRs) associated with remdesivir using VigiBase, an individual case safety report database of the World Health Organization (WHO). Disproportionality analyses of CV-ADRs associated with remdesivir were performed using reported odds ratios and information components. We conducted in vitro experiments using cardiomyocytes derived from human pluripotent stem cell cardiomyocytes (hPSC-CMs) to confirm cardiotoxicity of remdesivir. To distinguish drug-induced CV-ADRs from COVID-19 effects, we restricted analyses to patients with COVID-19 and found that, after adjusting for multiple confounders, cardiac arrest (adjusted odds ratio [aOR]: 1.88, 95% confidence interval [CI]: 1.08-3.29), bradycardia (aOR: 2.09, 95% CI: 1.24-3.53), and hypotension (aOR: 1.67, 95% CI: 1.03-2.73) were associated with remdesivir. In vitro data demonstrated that remdesivir reduced the cell viability of hPSC-CMs in time- and dose-dependent manners. Physicians should be aware of potential CV consequences following remdesivir use and implement adequate CV monitoring to maintain a tolerable safety margin. Funding Agencies|Yonsei University College of Medicine for 2021 [2021-32-0049] Funding Source: Medline

The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease ADAM9 . This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified ADAM9 as a driver of disease severity and a candidate therapeutic target.

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We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective. Funder: Bundesministerium f��r Bildung und Forschung (BMBF) Funder: Bundesministerium f��r Bildung und Forschung

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans’ mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas. Significance From 1990 to 2018, the Black–White American life expectancy gap fell 48.9% and mortality inequality decreased, although progress stalled after 2012 as life expectancy plateaued. Had improvements continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. Despite decreasing mortality inequality, income-based life expectancy gaps remain starker in the United States than in European countries. At the same time, European mortality improved strongly and even those U.S. populations with the longest life spans–White Americans living in the highest-income areas–experience higher mortality at all ages than Europeans in high-income areas in 2018. Hence, mortality rates of both Black and White Americans could fall much further in both high-income and low-income areas.