VIVÊNCIAS NO ESTÁGIO SUPERVISIONADO EM SETOR CLÍNICO DE ENDOSCOPIA E COLONOSCOPIA – RELATO DE EXPERIÊNCIA.

Introduction: The study of upper digestive endoscopy (EDA) and colonoscopy are exams that have improved with advances in global technologies. They serve as a basis for diagnosing basic diseases of the digestive system, with high prevalence and mortality in the world. The non-mandatory internship chosen in this area of knowledge aims to learn and develop clinical skills with the aim of improving the medical academic curriculum and exposing the activity as an experience report to the scientific community. Method: descriptive, longitudinal study, carried out in the first half of 2023 in a private clinic in Belém do Pará, where the intern presents its advantages and difficulties when carrying out the procedure. Results: the confluence between the curriculum and practical internship activities proved to be productive, in accordance with the objectives of the study and a new clinical experience for the academic. Conclusion: the active methodology of the medical course was passed on to the scientific community, where placing students in direct contact with care in an uncontrolled environment is essential to their training.  Introdução: O estudo da endoscopia digestiva alta (EDA) e colonoscopia, são exames que se aprimoraram com os avanços das tecnologias mundiais. Servem de base ao diagnóstico de doenças bases do sistema digestório, de alta prevalência e mortalidade no mundo. O estágio não obrigatório escolhido nesta área do conhecimento visa aprender e desenvolver habilidades clínicas com o intuito melhor o currículo acadêmico médico e expor a atividade como relato de experiência a comunidade científica. Método: estudo descritivo, longitudinal, realizado no primeiro semestre de 2023 em uma clínica particular em Belém do Pará, onde o estagiário apresenta suas vantagens e dificuldades ao realiza-lo. Resultados: a confluência entre grade curricular e atividades prática em estágio mostraram-se produtiva, de acordo com os objetivos do estudo e uma nova experiência clínica ao acadêmico. Conclusão: repassado a comunidade científica a metodologia ativa do curso de medicina onde colocar os alunos em contato direto com o atendimento em um ambiente não controlado é essencial a sua formação.   &nbsp

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

Atualização do tratamento da Rinossinusite Aguda Bacteriana: Uma revisão integrativa / Acute Rhinosinusitis Treatment Update: An Integrative Review

Objetivo: Descrever o tratamento da rinossinusite aguda bacteriana por meio de publicações científicas que abordam o tema. Métodos: Trata-se de uma Revisão Integrativa da Literatura (RIL), que visa analisar a Atualização do Tratamento da Rinossinusite Aguda através de análise bibliográfica em 20 estudos científicos que retratam o tema no período de 2001 a 2020. Os estudos foram selecionados por meio do motor de busca Biblioteca Virtual em saúde, que apresenta documentos sobre a temática. Por conseguinte, foram utilizados descritores como: tratamento de rinossinusite, rinossinusite aguda e rinossinusite bacteriana. Os critérios de inclusão foram: artigos completos, os quais tinham relação direta com o tema. Os critérios de exclusão foram: artigos incompletos, os quais não estavam relacionados diretamente com o tema central. Os dados obtidos foram analisados através de quadro de informações dos artigos selecionado. Resultados: os resultados dos artigos analisados demonstram que na maioria dos casos de acometimento por rinossinusite aguda bacteriana o tratamento se dá com auxílio de medicamentos antibióticos, que devem ser ministrados, principalmente, quando houver um quadro grave ou a presença de comorbidades. Conclusão: Conclui-se que o principal mecanismo utilizado pelos especialistas da área da saúde para tratamento da rinossinusite aguda bacteriana são os antibióticos. Sendo que os medicamentos mais utilizados são: amoxicilina, sulfametoxazol e trimetropim em casos leves e moderados por 7 a 10 dias