AVONET: Morphological, ecological and geographical data for all birds

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.Fil: Tobias, Joseph A.. Imperial College London; Reino Unido. University of Oxford; Reino UnidoFil: Sheard, Catherine. University of Oxford; Reino Unido. University of Bristol; Reino UnidoFil: Pigot, Alex L.. University of Oxford; Reino Unido. University College London; Estados UnidosFil: Devenish, Adam J. M.. Imperial College London; Reino UnidoFil: Yang, Jingyi. Imperial College London; Reino UnidoFil: Sayol, Ferran. University College London; Estados UnidosFil: Neate Clegg, Montague H. C.. University of Oxford; Reino Unido. University of Utah; Estados UnidosFil: Alioravainen, Nico. University of Oxford; Reino Unido. Natural Resources Institute Finland; FinlandiaFil: Weeks, Thomas L.. Imperial College London; Reino Unido. Natural History Museum; Reino UnidoFil: Barber, Robert A.. Imperial College London; Reino UnidoFil: Walkden, Patrick A.. Imperial College London; Reino Unido. Natural History Museum; Reino UnidoFil: MacGregor, Hannah E. A.. University of Oxford; Reino Unido. University of Bristol; Reino UnidoFil: Jones, Samuel E. I.. University of Oxford; Reino Unido. University of London; Reino UnidoFil: Vincent, Claire. Organización de Las Naciones Unidas; ArgentinaFil: Phillips, Anna G.. Senckenberg Biodiversity And Climate Research Centre; AlemaniaFil: Marples, Nicola M.. Trinity College; Estados UnidosFil: Montaño Centellas, Flavia A.. Universidad Mayor de San Andrés; Bolivia. University of Florida; Estados UnidosFil: Leandro Silva, Victor. Universidade Federal de Pernambuco; BrasilFil: Claramunt, Santiago. University of Toronto; Canadá. Royal Ontario Museum; CanadáFil: Darski, Bianca. Universidade Federal do Rio Grande do Sul; BrasilFil: Freeman, Benjamin G.. University of British Columbia; CanadáFil: Bregman, Tom P.. University of Oxford; Reino Unido. Future-Fit Foundation; Reino UnidoFil: Cooney, Christopher R.. University Of Sheffield; Reino UnidoFil: Hughes, Emma C.. University Of Sheffield; Reino UnidoFil: Capp, Elliot J. R.. University Of Sheffield; Reino UnidoFil: Varley, Zoë K.. University Of Sheffield; Reino Unido. Natural History Museum; Reino UnidoFil: Friedman, Nicholas R.. Okinawa Institute of Science and Technology Graduate University; JapónFil: Korntheuer, Heiko. Johannes Gutenberg Universitat Mainz; AlemaniaFil: Corrales Vargas, Andrea. Universidad Nacional de Costa Rica; Costa RicaFil: García, Natalia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; Argentin

Exhausted Cytotoxic Control of Epstein-Barr Virus in Human Lupus

Systemic Lupus Erythematosus (SLE) pathology has long been associated with an increased Epstein-Barr Virus (EBV) seropositivity, viremia and cross-reactive serum antibodies specific for both virus and self. It has therefore been postulated that EBV triggers SLE immunopathology, although the mechanism remains elusive. Here, we investigate whether frequent peaks of EBV viral load in SLE patients are a consequence of dysfunctional anti-EBV CD8+ T cell responses. Both inactive and active SLE patients (n = 76 and 42, respectively), have significantly elevated EBV viral loads (P = 0.003 and 0.002, respectively) compared to age- and sex-matched healthy controls (n = 29). Interestingly, less EBV-specific CD8+ T cells are able to secrete multiple cytokines (IFN-γ, TNF-α, IL-2 and MIP-1β) in inactive and active SLE patients compared to controls (P = 0.0003 and 0.0084, respectively). Moreover, EBV-specific CD8+ T cells are also less cytotoxic in SLE patients than in controls (CD107a expression: P = 0.0009, Granzyme B release: P = 0.0001). Importantly, cytomegalovirus (CMV)-specific responses were not found significantly altered in SLE patients. Furthermore, we demonstrate that EBV-specific CD8+ T cell impairment is a consequence of their Programmed Death 1 (PD-1) receptor up-regulation, as blocking this pathway reverses the dysfunctional phenotype. Finally, prospective monitoring of lupus patients revealed that disease flares precede EBV reactivation. In conclusion, EBV-specific CD8+ T cell responses in SLE patients are functionally impaired, but EBV reactivation appears to be an aggravating consequence rather than a cause of SLE immunopathology. We therefore propose that autoimmune B cell activation during flares drives frequent EBV reactivation, which contributes in a vicious circle to the perpetuation of immune activation in SLE patients

Discovery of sisunatovir (RV521), an inhibitor of respiratory syncytial virus fusion

RV521 is an orally bioavailable inhibitor of respiratory syncytial virus (RSV) fusion that was identified after a lead optimization process based upon hits that originated from a physical property directed hit profiling exercise at Reviral. This exercise encompassed collaborations with a number of contract organizations with collaborative medicinal chemistry and virology during the optimization phase in addition to those utilized as the compound proceeded through preclinical and clinical evaluation. RV521 exhibited a mean IC50 of 1.2 nM against a panel of RSV A and B laboratory strains and clinical isolates with antiviral efficacy in the Balb/C mouse model of RSV infection. Oral bioavailability in preclinical species ranged from 42 to >100% with evidence of highly efficient penetration into lung tissue. In healthy adult human volunteers experimentally infected with RSV, a potent antiviral effect was observed with a significant reduction in viral load and symptoms compared to placebo

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

Rapidly Escalating Hepcidin and Associated Serum Iron Starvation Are Features of the Acute Response to Typhoid Infection in Humans

BACKGROUND: Iron is a key pathogenic determinant of many infectious diseases. Hepcidin, the hormone responsible for governing systemic iron homeostasis, is widely hypothesized to represent a key component of nutritional immunity through regulating the accessibility of iron to invading microorganisms during infection. However, the deployment of hepcidin in human bacterial infections remains poorly characterized. Typhoid fever is a globally significant, human-restricted bacterial infection, but understanding of its pathogenesis, especially during the critical early phases, likewise is poorly understood. Here, we investigate alterations in hepcidin and iron/inflammatory indices following experimental human typhoid challenge. METHODOLOGY/PRINCIPAL FINDINGS: Fifty study participants were challenged with Salmonella enterica serovar Typhi and monitored for evidence of typhoid fever. Serum hepcidin, ferritin, serum iron parameters, C-reactive protein (CRP), and plasma IL-6 and TNF-alpha concentrations were measured during the 14 days following challenge. We found that hepcidin concentrations were markedly higher during acute typhoid infection than at baseline. Hepcidin elevations mirrored the kinetics of fever, and were accompanied by profound hypoferremia, increased CRP and ferritin, despite only modest elevations in IL-6 and TNF-alpha in some individuals. During inflammation, the extent of hepcidin upregulation associated with the degree of hypoferremia. CONCLUSIONS/SIGNIFICANCE: We demonstrate that strong hepcidin upregulation and hypoferremia, coincident with fever and systemic inflammation, are hallmarks of the early innate response to acute typhoid infection. We hypothesize that hepcidin-mediated iron redistribution into macrophages may contribute to S. Typhi pathogenesis by increasing iron availability for macrophage-tropic bacteria, and that targeting macrophage iron retention may represent a strategy for limiting infections with macrophage-tropic pathogens such as S. Typhi

Profiling Movement and Gait Quality Characteristics in Pre-School Children

There is a dearth of suitable metrics capable of objectively quantifying motor competence. Further, objective movement quality characteristics during free play have not been investigated in pre-school children. The aims of this study were to characterize children's free play physical activity and investigate how gait quality characteristics cluster with free play in pre-school children (3–5 years old). Sixty-one children (39 boys; 4.3 ± 0.7 years, 1.04 ± 0.05 m, 17.8 ± 3.2 kg) completed the movement assessment battery for children and took part in free play while wearing an ankle- and hip-mounted accelerometer. Characteristics of movement quality were profiled using a clustering algorithm. Spearman's rho and the Mann-Whitney U tests were used to assess relationships between movement quality characteristics and motor competence classification differences in integrated acceleration and spectral purity, respectively. Significant differences were found between motor competency classifications for spectral purity and integrated acceleration (p < .001). Spectral purity was hierarchically clustered with motor competence and integrated acceleration. Significant positive correlations were found between spectral purity, integrated acceleration and motor competence (p < .001). This is the first study to report spectral purity in pre-school children and the results suggest that the underlying frequency component of movement is clustered with motor competence

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages