Extranodal NK/T-cell lymphoma, nasal type with extensive cardiopulmonary involvement

Extranodal NK/T-cell lymphoma, nasal type (ENKTL-NT) is a rare type of Non-Hodgkin’s lymphoma, which usually presents with extranodal involvement and affects the nasal/upper aerodigestive tract in the classical presentation. Herein, we report the case of a 31-year-old, previously healthy, male patient diagnosed with ENKTL-NT with the involvement of the lung parenchyma and heart. Unfortunately, due to the rapid disease progression, the diagnosis was performed only at the autopsy. The authors highlight the rare clinical presentation of this type of lymphoma, as well as the challenging anatomopathological diagnosis in necrotic samples

Uso indiscriminado de psicotrópicos por estudantes do curso de medicina

Substâncias psicoativas são capazes de modificar funções biológicas do organismo, podendo provocar reações depressoras, estimulantes ou alucinógenas. São encontradas na forma de fármacos, drogas lícitas e drogas ilícitas. Estudos mostram que geralmente o primeiro contato com esses químicos acontece entre a faixa etária dos 12 aos 24 anos, período no qual ocorre maior ingresso de pessoas nas universidades. Diante disso, a seguinte análise trata-se de uma mini revisão integrativa de literatura que tem como objetivo elucidar acerca do uso de psicotrópicos por estudantes do curso de graduação em Medicina. Como base para o estudo, foram utilizados cinco artigos originais retirados das bases de dados PUBMED, Scientific Eletronic Library Online (SciELO), Google acadêmico e da Revista Científica Multidisciplinar Núcleo do Conhecimento. Constatou-se, então, que a grande maioria de estudantes universitários fazem o uso de alguma substância estimulante, sendo possível identificar entre os resultados das pesquisas que o ambiente social da universidade, principalmente do curso de medicina, é um fator atenuante para o uso de substâncias psicoativas, devido a estímulos e pressões psíquicas, além da influência social. Assim, buscando efeitos sedativos e tranquilizantes, substâncias como antipsicóticos, cannabis, tabaco, são utilizados com finalidade recreativa ou para desestressar. Além disso, considerando que a maioria dos estudantes entrevistados são do curso de medicina, chama a atenção a falta de conhecimento e responsabilidade a respeito dos vários aspectos relacionados ao uso dos psicotrópicos, principalmente antidepressivos e aqueles utilizados para concentração. Diante do apresentado, conclui-se que a quantidade de estudantes usuários de substâncias estimulantes, dentro das universidades, é preocupante; ratificando a relevância do tema, além da necessidade da realização de mais estudos acerca do consumo de psicotrópicos na medicina, visando conhecer melhor as consequências a longo prazo

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