18 research outputs found
Genotypic characterization of psittacid herpesvirus isolates from Brazil
AbstractThirty-six isolates of psittacid herpesvirus (PsHV), obtained from 12 different species of psittacids in Brazil, were genotypically characterized by restriction fragment length polymorphism (RFLP) analysis and PCR amplification. RFLP analysis with the PstI enzyme revealed four distinct restriction patterns (A1, X, W and Y), of which only A1 (corresponding to PsHV-1) had previously been described. To study PCR amplification patterns, six pairs of primers were used. Using this method, six variants were identified, of which, variants 10, 8, and 9 (in this order) were most prevalent, followed by variants 1, 4, and 5. It was not possible to correlate the PCR and RFLP patterns. Twenty-nine of the 36 isolates were shown to contain a 419bp fragment of the UL16 gene, displaying high similarity to the PsHV-1 sequences available in GenBank. Comparison of the results with the literature data suggests that the 36 Brazilian isolates from this study belong to genotype 1 and serotype 1
A Constelação Familiar Sistêmica como uma Ferramenta Pedagógica e de Mediação entre Família e Escola
O presente artigo relata a experiência terapêutica de Constelação Familiar ou Sistêmica em uma Escola de Ensino Fundamental e Médio, da rede pública, em Fortaleza-CE, Brasil. O projeto de Constelação Familiar nesta escola surgiu da grande demanda de apoio aos estudantes com dificuldades de aprendizagem e comportamento, percebida pela equipe técnica. Os procedimentos metodológicos desta pesquisa foram realizados, utilizando como técnicas a terapia de constelação familiar, análise de entrevistas com os alunos, pais e professores, e observação do comportamento dos estudantes que participaram das constelações familiares, dentro da rotina escolar
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Herpesvirus equino 3 em um garanhão
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Previous issue date: 2010Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Escola de Veterinária. Belo Horizonte, MG, Brasil.Em agosto de 2008, um garanhão da raça Mangalarga Marchador, de quatro anos de idade, com histórico clínico de apatia, inapetência e edema de prepúcio e escroto, apresentou, ao exame clínico, exsudato purulento fluindo pelo óstio prepucial, prepúcio e mucosa peniana com inúmeras lesões circulares de bordos elevados e hiperêmicos, centro ulcerado recoberto por material amarelado de aspecto fibrinoso, com distribuição multifocal. Histologicamente, a mucosa peniana apresentou áreas de ulceração associadas a infiltrado inflamatório misto, com necrose multifocal e moderado acúmulo de fibrina, que se estendiam para o tecido conjuntivo adjacente. O diagnóstico morfológico foi de balanopostite ulcerativa fibrino-necrótica multifocal intensa, similar ao encontrado em casos de exantema coital equino (ECE), causado pelo herpesvírus equino 3 (EHV-3). Amostra de pele do prepúcio e sangue, colhido em EDTA, foram submetidos a ensaios de PCR específicos para EHV-3, observando-se a amplificação de um produto de tamanho esperado de 518pb. A detecção do EHV-3 foi confirmada por meio de seu sequenciamento, sendo a sequência de nucleotídeos depositada no GenBank sob o número GQ336877. As sequências de nucleotídeos e as de aminoácidos deduzidos apresentaram identidade de 99% e 100%, respectivamente, com a sequência de EHV-3 disponível no GenBank, número AF081188. Após 15 dias de tratamento, houve completa cicatrização das lesões, com despigmentação da pele, principalmente, no prepúcio e na bolsa escrotal. Com base nos achados clínicos, histopatológicos, PCR e sequenciamento, concluiu-se tratar de um caso de exantema coital equino, sendo o primeiro com confirmação definitiva do agente etiológico no Brasil