Monitoria de patologia nos tempos de pandemia: um relato de experiência / Pathology monitoring in times of pandemic: an experience report

Introdução: A Patologia Humana é uma disciplina teórico-prática que estuda os mecanismos de desenvolvimento das doenças. Na área da medicina, sua importância justifica-se pela possibilidade de realizar diagnósticos de diversas doenças a partir da comparação entre tecidos saudáveis e doentes. Nesse contexto, ressalta-se o desafio de auxiliar no ensino de uma disciplina teórico-prática durante a pandemia de COVID-19. Objetivos: Relatar as experiências da monitoria virtual no ensino da disciplina de Patologia. Metodologia: Para auxiliar no ensino do componente de Patologia foram desenvolvidos objetivos de aprendizagem semanais e roteiros com questões. A cada semana procuramos utilizar uma estratégia diferente de ensino, onde a gameficação é uma ferramenta bastante utilizada. Em alguns objetivos foram elaborados casos clínicos, jogos e quizzes intencionando-se maior fixação do conteúdo, interatividade, engajamento e motivação por parte dos discentes nesse semestre atípico. Alternando com essa ferramenta, utilizamos o site www.kahoot.it, o qual possui um quizz de perguntas e respostas que faz um ranking de acordo com o índice de acertos e tempo de resposta, estimulando uma competição saudável entre os participantes. Resultados: Após a utilização da estratégia de gameficação, observou-se maior estimulação no estudo prévio, maior interatividade dos alunos durante as monitorias e consequentemente maior desempenho dos mesmos nas dinâmicas propostas nas monitorias e atividade avaliativas da disciplina. Além disso, a monitoria propiciou à equipe de monitores a oportunidade aprender, explorar novas ferramentas e auxiliar os professores nesse mundo virtual. Conclusões: Observou-se, portanto, que mesmo à distância e utilizando ferramentas virtuais não habituais, a monitoria foi efetiva e cumpriu seu objetivo de auxiliar no aprendizado dos discentes, dar suporte ao docente e aproximar a teoria da prática

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

Tuberculose pulmonar: perfil epidemiológico do sertão Pernambucano, Brasil / Pulmonary tuberculosis: epidemiological profile of sertão Pernambucano, Brazil

Atualmente, observa-se que a tuberculose pulmonar constitui um importante problema de Saúde Pública no mundo, uma vez que esse agravo apresentou, em 2015, 10,4 milhões de casos, dos quais, mais de um milhão de pessoas vieram a óbito. Sob essa perspectiva, o presente artigo tem como objetivo traçar um perfil epidemiológico dos casos de Tuberculose Pulmonar notificados no município de Serra Talhada, entre os anos de 2007 a 2017. Foi realizado um estudo de série histórica observacional do tipo transversal, no intervalo de tempo de 2007 a 2017.  No período investigado o número de casos de tuberculose pulmonar foi de 246 casos, o local que teve a maior prevalência foi Serra Talhada, 287 por 100 mil habitantes. Diante dos dados apresentados, é imprescindível concluir, portanto, que esse estudo corrobora o perfil epidemiológico brasileiro para a Tuberculose Pulmonar, o qual indica variabilidade nos índices de acometimento durante o período analisado

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

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Temas relevantes sobre o Estatuto da Pessoa com Deficiência: reflexos no ordenamento jurídico brasileiro

- Divulgação dos SUMÁRIOS das obras recentemente incorporadas ao acervo da Biblioteca Ministro Oscar Saraiva do STJ. Em respeito à Lei de Direitos Autorais, não disponibilizamos a obra na íntegra.- Localização na estante: 34-056.2(81) T278r- Cézar Fiuza é organizador da obra.- Marcelo Rodrigues da Silva e Roberto Alves de Oliveira Filho são os coordenadores da obra