Principais ferramentas de abordagem familiar para paciente índice com depressão / Main family approach tools for index patients with depression

Objetivo: Realizar abordagem familiar em três dos tipos de configurações familiares existentes com pacientes índices com depressão e exemplificar a aplicação de algumas ferramentas. Métodos: Trata-se de um estudo descritivo, de caráter qualitativo e quantitativo e de natureza investigativa exploratória, realizado com seis tipos de famílias. Os instrumentos utilizados foram questionário sociodemográfico, produzido pelos próprios autores e aplicado em visitas domiciliares, utilizando como critério depressão em pelo menos um membro de cada família e um roteiro de aplicação das ferramentas genograma, ecomapa e ciclo de vida. Resultados: A amostra apresentou três tipos de configurações familiares com duas famílias dos tipos nuclear, monoparental e extensiva. De acordo com as ferramentas utilizadas os resultados obtidos mostram que as trocas emocionais intrafamiliares, as ligações da família com o meio e a forma de cada família lidar com os ajustes da etapa de desenvolvimento em que se encontram influenciam no convívio uma vez que quando se encontra fragilizada a probabilidade de um desequilíbrio emocional e do surgimento de uma possível doença são mais prevalentes. Conclusão: As ferramentas utilizadas na abordagem familiar permitiram uma visão holística e detalhada das famílias entrevistadas e melhor percepção para favorecer a abordagem profissional.

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

Molecular evidence of Borrelia burgdorferi sensu lato in patients in Brazilian central-western region

Abstract We aimed to detect DNA of Borrelia burgdorferi in whole blood and serum samples of patients with clinical symptoms and epidemiology compatible with Brazilian Lyme-like disease. Four patients with positive epidemiological histories were recruited for the study. Blood samples were collected, screened by serologic testing by ELISA and Western blotting and molecular identification of B. burgdorferi by amplifying a fragment of the conserved gene that synthesizes the hook flagellar flgE. The results showed positive serology and for the first time, the presence of B. burgdorferi sensu lato in humans in the Midwest region of Brazil. The resulting sequences were similar to GenBank corresponding sequences of B. burgdorferi flgE gene. By neighbor-joining the phylogenetic analysis, the flgE sequence of the Brazilian strain clustered in a monophyletic group with the sequence of B. burgdorferi sensu lato under 100% bootstrap support. This study opens up promising perspectives and reinforces the need for additional studies to determine the epidemiological characteristics of the disease, as well as the impact of the prevalence of Brazilian borreliosis in Mato Grosso do Sul State, Brazil