UM RELATO DE EXPERIÊNCIA EM EDUCAÇÃO MÉDICA: MÓDULO DE DESENVOLVIMENTO PESSOAL – PSICOPATOLOGIA NA FACULDADE DE MEDICINA DA UNIVERSIDADE FEDERAL DO CEARÁ EM SOBRAL

A semiologia é a base para uma prática médica de excelência: observar com cuidado, enxergar, ouvir e interpretar o que se diz, pensar, desenvolver um raciocínio clínico crítico e acurado são capacidades essenciais do profissional. Partindo dessas considerações, apresentamos este relato de nossa experiência com o módulo Desenvolvimento Pessoal – Psicopatologia do Curso de Medicina da UFC – Sobral, no qual os estudantes foram apresentados a uma semiologia com foco diferenciado na escuta e atenção, no cuidado com a avaliação e interpretação dos fenômenos observados. Por ser uma área cujo objeto é a descrição dos fenômenos psíquicos anormais exatamente como se apresentam à experiência humana, a psicopatologia demanda do profissional concentrar-se na vivência subjetiva. Assim, os alunos foram inseridos em um universo complexo e delicado, no qual a mente humana é o grande palco de análise e surgimento de incertezas. Frente a este desafio, o módulo foi estruturado contemplando, além do conhecimento cognitivo e desenvolvimento de habilidades, a aquisição/desenvolvimento de competências e atitudes. Ao final, o relato dos alunos demonstrou haver êxito nos objetivos elencados: provocar reflexões e estimular autocrescimento como seres humanos para além do papel de “peritos médicos”. Ao lidar com situações nas quais se evidenciam os limites da saúde mental do indivíduo e dos saberes e práticas dos profissionais em saúde, passa-se exatamente à esfera das necessidades humanas psíquicas, sociais e espirituais. Ratifica-se a necessidade de posicionar o acadêmico de medicina diante deste desafio ético que consiste, principalmente, em considerar a dignidade do sujeito para além da dimensão físico-biológica e do contexto médico-hospitalar

Is there a relationship between hippocampus-dependent memory and 5-ht2a receptors? Insights from a systematic review / Há uma relação entre a memória hipocampo-dependente e receptores 5-HT2a? Insights de uma revisão sistemática

This is a systematic review with the aim of analyzing the role of 5-HT2A receptors in hippocampal-dependent memory. In order to do this, we searched the PubMed, Science Direct, and Neuron databases between October 23 and 29, 2018, using the following descriptor combinations: memory, 5-HT2A, and hippocampus, present in the title, abstract, or keywords, with no restrictions on study date or language. Following search and selection, we analyzed risk of bias, and the results were subsequently synthesized according to the experimental model. Out of 40 articles, four were included in qualitative analysis. The data indicate that the 5-HT2A receptors in the hippocampus play an important role in the memory consolidation process, although they do not interfere in the encoding or retrieval processes of these memories. Additionally, chronic use of receptor agonists in models of Alzheimer’s disease also demonstrates better performance in the object recognition tests. The action of 5-HT2A receptors has also been shown to be important to aversive memory formation, thus attributing a prominent role to these receptors in hippocampal-dependent memory processes

Heterofucan from Sargassum filipendula Induces Apoptosis in HeLa Cells

Fucan is a term used to denominate a family of sulfated polysaccharides rich in sulfated l-fucose. Heterofucan SF-1.5v was extracted from the brown seaweed Sargassum filipendula by proteolytic digestion followed by sequential acetone precipitation. This fucan showed antiproliferative activity on Hela cells and induced apoptosis. However, SF-1.5v was not able to activate caspases. Moreover, SF-1.5v induced glycogen synthase kinase (GSK) activation, but this protein is not involved in the heterofucan SF-1.5v induced apoptosis mechanism. In addition, ERK, p38, p53, pAKT and NFκB were not affected by the presence of SF-1.5v. We determined that SF-1.5v induces apoptosis in HeLa mainly by mitochondrial release of apoptosis-inducing factor (AIF) into cytosol. In addition, SF-1.5v decreases the expression of anti-apoptotic protein Bcl-2 and increased expression of apoptogenic protein Bax. These results are significant in that they provide a mechanistic framework for further exploring the use of SF-1.5v as a novel chemotherapeutics against human cervical cancer

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

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