11 research outputs found

    Pelas ruas de Maringå, PR: uma anålise do Plano de Gestão da Arborização Urbana. e2321826

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    Roadside tree planting is sometimes neglected by many Brazilian city councils, as they do not consider trees as part of urban infrastructure. So, this paper aims to analyze the planning of street tree planting in the city of MaringĂĄ, located in the Northern State of ParanĂĄ. The specific objectives were (i) to identify municipal legislations regarding urban tree planting from 1950 to 2022; and (ii) to analyze the 2020 MaringĂĄ Urban Tree Management Plan (PGAU). It analyzed the urban occupation and street tree planting history, as well as the PGAU, by means of bibliographical and documental research. MaringĂĄ initially had its tree planting planning carried out by the Companhia de Melhoramentos Norte do ParanĂĄ between 1947 and 1982, and later by the Municipal Government, which published its PGAU only in the year 2020. It is concluded that the PGAU is an important planning management document developed by this municipality, but it has some deficiencies that could be further improve

    Mobilidade populacional e produção da leishmaniose tegumentar americana no Estado do Paranå, sul do Brasil

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    SĂŁo escassas as informaçÔes sobre o papel da mobilidade populacional na manutenção da leishmaniose tegumentar americana no estado do ParanĂĄ. Avalia-se a mobilidade populacional como fator de risco para esta endemia em trĂȘs mesorregiĂ”es do ParanĂĄ, utilizando dados gerados na Universidade Estadual de MaringĂĄ, no perĂ­odo de 1987 a 2004. Foram notificados 1.933 casos, predominando os casos migrantes (54,4%). Os municĂ­pios com maior nĂșmero de casos notificados foram MaringĂĄ (358), Doutor Camargo (108) e Terra Boa (105). Os casos rurais foram predominantemente autĂłctones (89,8%), enquanto os urbanos, na maioria (84,8%) migrantes (p<0,0001). Para os casos rurais autĂłctones, nĂŁo houve predomĂ­nio entre os sexos (p=0,127); para os casos urbanos migrantes, prevaleceu o sexo masculino (p<0,0001). Os casos migrantes foram na maioria relacionados com a mobilidade intra e intermunicipal. A mobilidade populacional parece ser uma variĂĄvel importante na epidemiologia desta doença no Estado do ParanĂĄ

    A Transcript Finishing Initiative for Closing Gaps in the Human Transcriptome

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    We report the results of a transcript finishing initiative, undertaken for the purpose of identifying and characterizing novel human transcripts, in which RT-PCR was used to bridge gaps between paired EST clusters, mapped against the genomic sequence. Each pair of EST clusters selected for experimental validation was designated a transcript finishing unit (TFU). A total of 489 TFUs were selected for validation, and an overall efficiency of 43.1% was achieved. We generated a total of 59,975 bp of transcribed sequences organized into 432 exons, contributing to the definition of the structure of 211 human transcripts. The structure of several transcripts reported here was confirmed during the course of this project, through the generation of their corresponding full-length cDNA sequences. Nevertheless, for 21% of the validated TFUs, a full-length cDNA sequence is not yet available in public databases, and the structure of 69.2% of these TFUs was not correctly predicted by computer programs. The TF strategy provides a significant contribution to the definition of the complete catalog of human genes and transcripts, because it appears to be particularly useful for identification of low abundance transcripts expressed in a restricted set of tissues as well as for the delineation of gene boundaries and alternatively spliced isoforms

    Field and classroom initiatives for portable sequence-based monitoring of dengue virus in Brazil

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    This work was supported by Decit, SCTIE, Brazilian Ministry of Health, Conselho Nacional de Desenvolvimento CientĂ­fico - CNPq (440685/ 2016-8, 440856/2016-7 and 421598/2018-2), Coordenação de Aperfeiçoamento de Pessoal de NĂ­vel Superior - CAPES - (88887.130716/2016-00), European Union’s Horizon 2020 Research and Innovation Programme under ZIKAlliance Grant Agreement (734548), STARBIOS (709517), Fundação de Amparo Ă  Pesquisa do Estado do Rio de Janeiro – FAPERJ (E-26/2002.930/2016), International Development Research Centre (IDRC) Canada (108411-001), European Union’s Horizon 2020 under grant agreements ZIKACTION (734857) and ZIKAPLAN (734548).Fundação Ezequiel Dias. LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Minas Gerais. Belo Horizonte, MG, Brazil / Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil / Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto LeĂŽnidas e Maria Deane. LaboratĂłrio de Ecologia de Doenças TransmissĂ­veis na AmazĂŽnia. Manaus, AM, Brazil.Secretaria de SaĂșde do Estado de Mato Grosso do Sul. LaboratĂłrio Central de SaĂșde PĂșblica. Campo Grande, MS, Brazil.Fundação Ezequiel Dias. LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Dr. Giovanni Cysneiros. GoiĂąnia, GO, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Professor Gonçalo Moniz. Salvador, BA, Brazil.Secretaria de SaĂșde do Estado da Bahia. Salvador, BA, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Dr. Milton Bezerra Sobral. Recife, PE, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Mato Grosso. CuiabĂĄ, MT, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Distrito Federal. BrasĂ­lia, DF, Brazil.Fundação Ezequiel Dias. LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Coordenação Geral dos LaboratĂłrios de SaĂșde PĂșblica. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Coordenação Geral dos LaboratĂłrios de SaĂșde PĂșblica. BrasĂ­lia, DF, Brazil.Organização Pan-Americana da SaĂșde / Organização Mundial da SaĂșde. BrasĂ­lia, DF, Brazil.Organização Pan-Americana da SaĂșde / Organização Mundial da SaĂșde. BrasĂ­lia, DF, Brazil.Organização Pan-Americana da SaĂșde / Organização Mundial da SaĂșde. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde Coordenação Geral das Arboviroses. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde Coordenação Geral das Arboviroses. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde Coordenação Geral das Arboviroses. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde Coordenação Geral das Arboviroses. BrasĂ­lia, DF, Brazil.Fundação Hemocentro de RibeirĂŁo Preto. RibeirĂŁo Preto, SP, Brazil.Gorgas Memorial Institute for Health Studies. Panama, Panama.Universidade Federal da Bahia. VitĂłria da Conquista, BA, Brazil.Laboratorio Central de Salud PĂșblica. AsunciĂłn, Paraguay.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Coordenação Geral dos LaboratĂłrios de SaĂșde PĂșblica. BrasĂ­lia, DF, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, BrazilFundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, BrazilMinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Mato Grosso do Sul. Campo Grande, MS, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Mato Grosso do Sul. Campo Grande, MS, Brazil.Instituto de Investigaciones en Ciencias de la Salud. San Lorenzo, Paraguay.Secretaria de Estado de SaĂșde de Mato Grosso do Sul. Campo Grande, MS, Brazil.Fundação Oswaldo Cruz. Campo Grande, MS, Brazil.Fundação Hemocentro de RibeirĂŁo Preto. RibeirĂŁo Preto, SP, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Dr. Giovanni Cysneiros. GoiĂąnia, GO, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Dr. Giovanni Cysneiros. GoiĂąnia, GO, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Professor Gonçalo Moniz. Salvador, BA, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Dr. Milton Bezerra Sobral. Recife, PE, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Distrito Federal. BrasĂ­lia, DF, Brazil.Secretaria de SaĂșde de Feira de Santana. Feira de Santana, Ba, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Secretaria de SaĂșde do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.Hospital das Forças Armadas. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. BrasĂ­lia, DF, Brazil.Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Lisboa, Portugal.University of Sydney. School of Life and Environmental Sciences and School of Medical Sciences. Marie Bashir Institute for Infectious Diseases and Biosecurity. Sydney, NSW, Australia.University of KwaZulu-Natal. College of Health Sciences. KwaZulu-Natal Research Innovation and Sequencing Platform. Durban, South Africa.University of Oxford. Peter Medawar Building. Department of Zoology. Oxford, UK.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Universidade Estadual de Feira de Santana. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Universidade de BrasĂ­lia. BrasĂ­lia, DF, Brazil.Universidade Salvador. Salvador, BA, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de FlavivĂ­rus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. LaboratĂłrio de Hantaviroses e Rickettsioses. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto LeĂŽnidas e Maria Deane. LaboratĂłrio de Ecologia de Doenças TransmissĂ­veis na AmazĂŽnia. Manaus, AM, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Faculdade de Medicina VeterinĂĄria. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Faculdade de Medicina VeterinĂĄria. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado do ParanĂĄ. Curitiba, PR, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado de RondĂŽnia. Porto Velho, RO, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado do Amazonas. Manaus, AM, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado do Rio Grande do Norte. Natal, RN, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica do Estado de Mato Grosso. CuiabĂĄ, MT, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Professor Gonçalo Moniz. Salvador, BA, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Professor Gonçalo Moniz. Salvador, BA, Brazil.LaboratĂłrio Central de SaĂșde PĂșblica Noel Nutels. Rio de Janeiro, RJ, Brazil.Instituto Adolfo Lutz. SĂŁo Paulo, SP, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Universidade de SĂŁo Paulo. Instituto de Medicina Tropical. SĂŁo Paulo, SP, Brazil.Universidade de SĂŁo Paulo. Instituto de Medicina Tropical. SĂŁo Paulo, SP, Brazil.Universidade de SĂŁo Paulo. Instituto de Medicina Tropical. SĂŁo Paulo, SP, Brazil.University of Oxford. Peter Medawar Building. Department of Zoology. Oxford, UK.Instituto Nacional de Enfermedades Virales Humanas Dr. Julio Maiztegui. Pergamino, Argentina.Gorgas Memorial Institute for Health Studies. Panama, Panama.Gorgas Memorial Institute for Health Studies. Panama, Panama.Gorgas Memorial Institute for Health Studies. Panama, Panama.Instituto de Salud PĂșblica de Chile. Santiago, Chile.Instituto de DiagnĂłstico y Referencia EpidemiolĂłgicos Dr. Manuel MartĂ­nez BĂĄez. Ciudad de MĂ©xico, MĂ©xico.Instituto Nacional de Enfermedades Infecciosas Dr Carlos G MalbrĂĄn. Buenos Aires, Argentina.Ministerio de Salud PĂșblica de Uruguay. Montevideo, Uruguay.Instituto Costarricense de InvestigaciĂłn y Enseñanza em NutriciĂłn y Salud. Tres RĂ­os, Costa Rica.Instituto Nacional de Investigacion en Salud Publica Dr Leopoldo Izquieta PĂ©rez. Guayaquil, Ecuador.Instituto Nacional de Investigacion en Salud Publica Dr Leopoldo Izquieta PĂ©rez. Guayaquil, Ecuador.Universidade Federal de Pernambuco. Recife, PE, Brazil.Secretaria de SaĂșde do Estado de Minas Gerais. Belo Horizonte. MG, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. BrasĂ­lia, DF, Brazil.MinistĂ©rio da SaĂșde. Secretaria de VigilĂąncia em SaĂșde. BrasĂ­lia, DF, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Fundação Hemocentro de RibeirĂŁo Preto. RibeirĂŁo Preto, SP, Brazil.Secretaria de SaĂșde de Feira de Santana. Feira de Santana, BA, Brazil.Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas. Belo Horizonte, MG, Brazil.Brazil experienced a large dengue virus (DENV) epidemic in 2019, highlighting a continuous struggle with effective control and public health preparedness. Using Oxford Nanopore sequencing, we led field and classroom initiatives for the monitoring of DENV in Brazil, generating 227 novel genome sequences of DENV1-2 from 85 municipalities (2015–2019). This equated to an over 50% increase in the number of DENV genomes from Brazil available in public databases. Using both phylogenetic and epidemiological models we retrospectively reconstructed the recent transmission history of DENV1-2. Phylogenetic analysis revealed complex patterns of transmission, with both lineage co-circulation and replacement. We identified two lineages within the DENV2 BR-4 clade, for which we estimated the effective reproduction number and pattern of seasonality. Overall, the surveillance outputs and training initiative described here serve as a proof-of-concept for the utility of real-time portable sequencing for research and local capacity building in the genomic surveillance of emerging viruses

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

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    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

    NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

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    Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

    Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

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    The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications

    NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

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    Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data

    Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

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    Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)
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