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Imigração e saúde: a (in)acessibilidade das mulheres imigrantes aos cuidados de saúde

A utilização dos serviços de saúde pelas populações imigrantes tem vindo a ser considerado um dos mais importantes indicadores da sua integração nas so- ciedades receptoras (Dias e col., 2009). No entanto, o conhecimento em torno da qualidade e da eficácia do acesso dos/as imigrantes aos cuidados de saúde, especialmente no que respeita às mulheres imigran- tes, é ainda escasso em Portugal (Fonseca e col., 2005). Embora os estudos nacionais tenham vindo, nas últimas décadas, a procurar traçar os diferentes perfis sociais das mulheres imigrantes em Portugal, sobretudo no que concerne às suas relações fami- liares ou laborais (Wall e col., 2005), a investigação no domínio da saúde é ainda parca e exclusora de uma análise centrada no género ou interseccional. Neste texto apresenta-se uma reflexão sobre os de- terminantes que condicionam a (in)acessibilidade das mulheres imigrantes aos cuidados de saúde, enfatizando-se os fatores que poderão estar a agir no sentido contrário à sua integração neste setor

Data standardization of plant-pollinator interactions

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.Fil: Salim, José A. Universidade de Sao Paulo; BrasilFil: Saraiva, Antonio M.. Universidade de Sao Paulo; BrasilFil: Zermoglio, Paula Florencia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Patagonia Norte. Instituto de Investigaciones En Recursos Naturales, Agroecologia y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones En Recursos Naturales, Agroecologia y Desarrollo Rural.; ArgentinaFil: Agostini, Kayna. Universidade Federal do São Carlos; BrasilFil: Wolowski, Marina. Universidade Federal de Alfenas; BrasilFil: Drucker, Debora P.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Soares, Filipi M.. Universidade de Sao Paulo; BrasilFil: Bergamo, Pedro J.. Jardim Botânico do Rio de Janeiro; BrasilFil: Varassin, Isabela G.. Universidade Federal do Paraná; BrasilFil: Freitas, Leandro. Jardim Botânico do Rio de Janeiro; BrasilFil: Maués, Márcia M.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Rech, Andre R.. Universidade Federal dos Vales do Jequitinhonha e Mucuri; BrasilFil: Veiga, Allan K.. Universidade de Sao Paulo; BrasilFil: Acosta, Andre L.. Instituto Tecnológico Vale; BrasilFil: Araujo, Andréa C. Universidade Federal do Mato Grosso do Sul; BrasilFil: Nogueira, Anselmo. Universidad Federal do Abc; BrasilFil: Blochtein, Betina. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Freitas, Breno M.. Universidade Estadual do Ceará; BrasilFil: Albertini, Bruno C.. Universidade de Sao Paulo; BrasilFil: Maia Silva, Camila. Universidade Federal Rural Do Semi Arido; BrasilFil: Nunes, Carlos E. P.. University of Stirling; BrasilFil: Pires, Carmen S. S.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Dos Santos, Charles F.. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Queiroz, Elisa P.. Universidade de Sao Paulo; BrasilFil: Cartolano, Etienne A.. Universidade de Sao Paulo; BrasilFil: de Oliveira, Favízia F. Universidade Federal da Bahia; BrasilFil: Amorim, Felipe W.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Fontúrbel, Francisco E.. Pontificia Universidad Católica de Valparaíso; ChileFil: da Silva, Gleycon V.. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Consolaro, Hélder. Universidade Federal de Catalão; Brasi

Data standardization of plant–pollinator interactions

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of termsinfo:eu-repo/semantics/publishedVersio

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

The dengue virus has a single-stranded positive-sense RNA genome of ∼10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1–4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in São José do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000–2001. Sixty DENV-3 from São José do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R0 = 1.53 and values for lineage 2 of R0 = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area