Evaluation of relative biological efficiency of additives in sugarcane ensiling

The objective of this study was to evaluate the effects of adding alkalis on the fermentative pattern, aerobic stability and nutritive value of the sugarcane silage. A completely randomized design with 6 additives in two concentrations (1 or 2%), plus a control group, totalizing 13 treatments [(6x2)+1] with four replications, was used. The additives were sodium hydroxide (NaOH), limestone (CaCO3), urea (CO(NH2)(2)), sodium bicarbonate (NaHCO3), quicklime (CaO) and hydrated lime (Ca(OH)(2)). The material was ensiled in 52 laboratory silos using plastic buckets with 12 L of capacity. Silos were opened 60 days after ensiling, when organic acids concentration, aerobic stability and chemical composition were determined. The Relative Biological Efficiency (RBE) was calculated by the slope ratio method, using the data obtained from ratio between desirable and undesirable silage products, according to the equation: D/U ratio = [lactic/(ethanol + acetic + butyric)]. All additives affected dry matter, crude protein, acid detergent fiber, neutral detergent fiber contents and buffering capacity. Except for urea and quicklime, all additives increased the in vitro dry matter digestibility. In general, these additives altered the fermentative pattern of sugarcane silage, inhibiting alcoholic fermentation and improving lactic acid production. The additive that showed the best RBE in relation to sodium hydroxide (100%) was limestone (89.4%). The RBE values of urea, sodium bicarbonate and hydrated lime were 49.2%, 47.7% and 34.3%, respectively

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Genome of Rhodnius prolixus, an insect vector of Chagas disease, reveals unique adaptations to hematophagy and parasite infection

O artigo apresenta nas duas primeiras páginas nota de correção.Submitted by sandra infurna ([email protected]) on 2016-03-31T12:56:45Z No. of bitstreams: 1 andre_torres_etal_IOC_2015.pdf: 1095119 bytes, checksum: df9054f950a043553746f4758ab01c35 (MD5)Approved for entry into archive by sandra infurna ([email protected]) on 2016-03-31T15:33:31Z (GMT) No. of bitstreams: 1 andre_torres_etal_IOC_2015.pdf: 1095119 bytes, checksum: df9054f950a043553746f4758ab01c35 (MD5)Made available in DSpace on 2016-03-31T15:33:31Z (GMT). No. of bitstreams: 1 andre_torres_etal_IOC_2015.pdf: 1095119 bytes, checksum: df9054f950a043553746f4758ab01c35 (MD5) Previous issue date: 2015Universidade Federal do Rio de Janeiro. Instituto de Química. Departamento de Bioquímica. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Simon Fraser University. Biological Sciences. Burnaby, BC, Canada.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina / Universidad Nacional del Noroeste de Buenos Aires. Centro de Bioinvestigaciones. Pergamino, Argentina.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Universidade Federal do Rio de Janeiro. Instituto de Biologia. Departamento de Genética. Rio de Janeiro, RJ, Brasil.Universidad de la República. Facultad de Ciencias. Sección Genética Evolutiva. Montevideo, Uruguay.European Bioinformatics Institute. European Molecular Biology Laboratory. Welcome Trust Genome Campus. Hinxton, Cambridge, United Kingdom.Universidade Federal do Rio de Janeiro. Instituto de Química. Departamento de Bioquímica. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.University of Notre Dame. Department of Biological Sciences. Notre Dame, IN.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Estadual Paulista. Departamento de Biologia. São Paulo, SP, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brasil.The Barcelona Institute of Science and Technology. Centre for Genomic Regulation. Barcelona, Spain / Universitat Pompeu Fabra. Barcelona, Spain.Institut de Recherche pour le Development. Centre National de la Recherche Scientifique. Laboratoire d`Evolution, Génome et Spéciation. Gif sur Yvette, France / Université Paris-Sud, Orsay, France.European Bioinformatics Institute. European Molecular Biology Laboratory. Welcome Trust Genome Campus. Hinxton, Cambridge, United Kingdom.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Université François Rabelais. Centre National de la Recherche Sicentifique. Institut de Recherche sur la Biologie de l`Insect. Tours, France.Université Paris-Sud, Orsay, France.Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata (INIBIOLP, CONICET). La Plata, Argentina.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Biologia. Departamento de Genética. Rio de Janeiro, RJ, Brasil.University of Toronto. Department of Biology. Mississauga, ON, Canada.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brasil.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina.Centers for Disease Control and Prevention. Entomology Branch. Division of Parasitic Diseases and Malaria. Atlanta, GA, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Biologia. Departamento de Genética. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brasil.Universidade Estadual do Norte Fluminense Darcy Ribeiro. Centro de Biociências e Biotecnologia. Laboratório de Química e Função de Proteínas e Peptídeos. Campos de Goytacazes, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil /Universidade Federal do Rio de Janeiro. Faculdade de Farmácia. Departamento de Biotecnologia Farmacêutica. Rio de Janeiro, RJ, Brasil.Centers for Disease Control and Prevention. Entomology Branch. Division of Parasitic Diseases and Malaria. Atlanta, GA, USA.The Barcelona Institute of Science and Technology. Centre for Genomic Regulation. Barcelona, Spain / Universitat Pompeu Fabra. Barcelona, Spain.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.European Bioinformatics Institute. European Molecular Biology Laboratory. Welcome Trust Genome Campus. Hinxton, Cambridge, United Kingdom.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina.Universidade Federal do Rio de Janeiro. Instituto de Química. Departamento de Bioquímica. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil.Instituto Politécnico Nacional. Centro de Investigación y de Estudios Avanzados. oDepartment of Physiology, Biophysics and Neuroscience. Mexico City, Mexico.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Fisiologia e BIoquímica. Belo Horizonte, MG, Brasil.Florida International University. Department of Biological Sciences. Miami, FL, USA.Florida International University. Department of Biological Sciences. Miami, FL, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal Rural do Rio de Janeiro. Instituto de Ciências Biológicas e da Saúde. Departamento de Biologia Animal. Seropédica, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.University of Toronto. Department of Biology. Mississauga, ON, Canada.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata (INIBIOLP, CONICET). La Plata, Argentina.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal de Minas Gerais.Instituto de Ciências Biológicas. Departamento de Parasitologia. Belo Horizonte, MG, Brasil.The John Hopkins University. Bloomberg School of Public Health. Deparment of Molecular Microbiology and Immunology. Baltimore, MD, USA.Instituto Federal de Educação Ciência e Tecnologia do Rio de Janeiro. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Espirito Santo. Núcleo de Doenças Infecciosas. Vitória, ES, Brasil.University of Illinois at Urbana–Champaign. Department of Entomology. Urbana, IL, USA.Instituto Federal de Educação Ciência e Tecnologia do Rio de Janeiro. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.The Barcelona Institute of Science and Technology. Centre for Genomic Regulation. Barcelona, Spain / Universitat Pompeu Fabra. Barcelona, Spain.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil./ Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal de Uberlândia. Faculdade de Computação. Instituto de Genética e Bioquímica. Laboratório de Bioinformática e Análises Moleculares. Uberlândia, MG, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, BrasilUniversidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, BrasilUniversity of Santiago de Compostela. Instituto de Investigaciones Sanitarias. School of Medicine– Center for Resesarch in Molecular Medicine and Chronic Diseases. Department of Physiology. Santiago de Compostela, Spain.Virginia Polytechnic Institute. Department of Biochemistry. Blacksburg, VA, USA.University of Cambridge. Deparment of Veterinary Medicine. Cambridge, United Kingdom.Simon Fraser University. Biological Sciences. Burnaby, BC, Canada.National Institutes of Health. National Institute of Allergy and Infectious Diseases. Section of Vector Biology. Rockville, MD, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Estadual do Norte Fluminense Darcy Ribeiro. Centro de Biociências e Biotecnologia. Laboratório de Química e Função de Proteínas e Peptídeos. Campos de Goytacazes, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, BrasilEuropean Bioinformatics Institute. European Molecular Biology Laboratory. Welcome Trust Genome Campus. Hinxton, Cambridge, United Kingdom.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.University of Manitoba.Department of Biological Sciences. Winnipeg, MB, Canada.Centers for Disease Control and Prevention. Entomology Branch. Division of Parasitic Diseases and Malaria. Atlanta, GA, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil..Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.University of Geneva Medical School. Department of Genetic Medicine and Development. Geneva 1211, Switzerland / Swiss Institute of Bioinformatics. Geneva 1211, Switzerland / Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory. Cambridge, MA, USA / The Broad Institute of MIT and Harvard. Cambridge, MA, USA.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Grupo de Pesquisa em Ecologia de Doenças Transmissíveis na Amazônia. AM, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal de Uberlândia. Faculdade de Computação. Instituto de Genética e Bioquímica. Laboratório de Bioinformática e Análises Moleculares. Uberlândia, MG, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Ciências Biomédicas. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Parasitologia. Belo Horizonte, MG, Brasil.National Institutes of Health. National Center for Biotechnology Information. Rockville, MD, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Ciências Médicas. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Química. Departamento de Bioquímica. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil.Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones Bioquímicas de La Plata (INIBIOLP, CONICET). La Plata, Argentina.Universidade Estadual Paulista. Departamento de Biologia. São Paulo, SP, Brasil.European Bioinformatics Institute. European Molecular Biology Laboratory. Welcome Trust Genome Campus. Hinxton, Cambridge, United Kingdom.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Universidade Estadual do Norte Fluminense Darcy Ribeiro. Centro de Biociências e Biotecnologia. Laboratório de Química e Função de Proteínas e Peptídeos. Campos de Goytacazes, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.The John Hopkins University. Bloomberg School of Public Health. Deparment of Molecular Microbiology and Immunology. Baltimore, MD, USA.University of Notre Dame. Department of Computer Science and Engineering. Notre Dame, IN.Universidad Nacional de La Plata. Centro Regional de Estudios Genomicos. La Plata, Argentina.Universidade Federal Rural do Rio de Janeiro. Instituto de Ciências Biológicas e da Saúde. Departamento de Biologia Animal. Seropédica, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sérgio Arouca. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Núcleo de Pesquisas Ecológicas de Macaé. Macaé, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Ciências Biomédicas. Rio de Janeiro, RJ, Brasil.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Washington University School of Medicine. McDonnell Genome Institute. St. Louis, MO, USA.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Instituto de Bioquímica Médica Leopoldo de Meis. Programa de Biologia Molecular e Biotecnologia. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Rhodnius prolixus not only has served as a model organism for the study of insect physiology, but also is a major vector of Chagas disease, an illness that affects approximately seven million people worldwide. We sequenced the genome of R. prolixus, generated assembled sequences covering 95% of the genome (∼702 Mb), including 15,456 putative protein-coding genes, and completed comprehensive genomic analyses of this obligate blood-feeding insect. Although immunedeficiency (IMD)-mediated immune responses were observed, R. prolixus putatively lacks key components of the IMD pathway, suggesting a reorganization of the canonical immune signaling network. Although both Toll and IMD effectors controlled intestinal microbiota, neither affected Trypanosoma cruzi, the causal agent of Chagas disease, implying the existence of evasion or tolerance mechanisms. R. prolixus has experienced an extensive loss of selenoprotein genes, with its repertoire reduced to only two proteins, one of which is a selenocysteine-based glutathione peroxidase, the first found in insects. The genome contained actively transcribed, horizontally transferred genes from Wolbachia sp., which showed evidence of codon use evolution toward the insect use pattern. Comparative protein analyses revealed many lineage-specific expansions and putative gene absences in R. prolixus, including tandem expansions of genes related to chemoreception, feeding, and digestion that possibly contributed to the evolution of a blood-feeding lifestyle. The genome assembly and these associated analyses provide critical information on the physiology and evolution of this important vector species and should be instrumental for the development of innovative disease control methods

Paediatric COVID-19 mortality: a database analysis of the impact of health resource disparity

Background The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries.Methods The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria.Results A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)).Conclusion Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

Background: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]). Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

International audienceBackground: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs).Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support.Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]).Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable