STRUMA OVARII COM PADRÃO BORDERLINE ENTRE BENIGNIDADE E CARCINOMA

Introdução: O Struma ovarii é um tumor extremamente raro, sendo um dos subtipos de teratomas do ovário. Geralmente de acometimento benigno em mulheres que estão entre a terceira e a quinta década de vida. Com sintomatologia discreta como massa abdominal palpável, aumento do volume abdominal e dor abdominal, podendo se apresentar de forma assintomática em alguns casos. Desenvolvimento: O estudo tem como objetivo demonstrar um relato de caso de uma paciente 38 anos com diagnóstico de Struma ovarii que foi tratada cirurgicamente e mantém acompanhamento ambulatorial. A imuno-histoquímica evidenciou Struma ovarii, histologicamente maligno e compatível com Struma ovarii associado a carcinoma papilífero de tipo clássico. Considerações finais: Por ser uma patologia de baixa incidência e prevalência, não há um consenso acerca do tratamento e acompanhamento pós-cirúrgico, por isso, a importância de relatos de casos para trazer à luz discussões para uma melhor terapêutica e seguimento

Tumor miofibroblástico inflamatório do pulmão : Inflammatory myofibroblastic tumor of the lung

Introdução: Os tumores miofibroblásticos inflamatórios pulmonares são achados patológicos, de apresentação clínica, evolução e prognósticos controversos. Representam de 0,04% -1,2% de todos os tumores pulmonares, sendo mais comuns em crianças e rara sua forma primária em adultos. Possui diagnóstico difícil, pois é fundamentalmente anátomo-patológico. A apresentação clínica e radiográfica são muito variáveis.  Apresentação do caso: sexo masculino, 49 anos de idade, admitido no hospital das clínicas da UFG (Go) com história cronica de 6 meses de dispnea progressiva, com tosse produtiva e sibilos, paciente tinha história de tabagismo (1 maço por dia há 20 anos) hipertensão e asma. Discussão: O tumor miofibroblasto inflamatório de pulmão geralmente é assintomático e descoberto incidentalmente ou apresenta sintomas respiratórios inespecíficos, como tosse, dor torácica , dispneia, hemoptise e sintomas sistêmicos inespecíficos, como febre, mal-estar e perda de peso. Podem estar associados a distúrbios imunológicos e infecções crônicas e podem ocorrer em cicatrizes pulmonares cirúrgicas.  Conclusão: É uma causa rara de tumor primário em adultos, em contrapartida, frequente na população pediátrica e, tem no anatomopatológico seu melhor diagnóstico e tratamento após ressecção cirúrgica completa, o qual indica, de forma usual, um bom prognóstico

Proteinose alveolar pulmonar: Pulmonary alveolar proteinosis

INTRODUÇÃO: A Proteinose Alveolar Pulmonar (PAP) é uma síndrome rara causada pelo acúmulo de surfactante no espaço alveolar, mais comumente encontrada em homens com idade média de 20 a 50 anos. É uma patologia com apresentação clínica variável e de difícil diagnóstico, que pode cursar com dispneia, tosse e dor torácica. APRESENTAÇÃO DO CASO: RSM, sexo masculino, 39 anos,  ex-tabagista de um maço por dia, durante 8 anos, com queixa de dispneia, dor torácica, ventilatório dependente, febre não aferida esporadicamente, tosse seca, raramente produtiva durante a manhã, e cianose de extremidades aos esforços há 4 meses. Após 6 meses, evoluiu com piora do quadro. Prosseguiu a investigação de pneumopatia extensa bilateral, com realização de biópsia pulmonar, confirmando o diagnóstico de PAP. DISCUSSÃO: A tomografia de tórax é o exame inicial a ser solicitado na investigação de PAP, seguido da confirmação com líquido do lavado broncoalveolar. Embora não seja um exame obrigatório, o padrão-ouro é a biópsia pulmonar cirúrgica. O principal tratamento é a lavagem pulmonar, além de fisioterapia e suporte pulmonar. CONCLUSÃO: Ainda que seja uma doença rara, é essencial o diagnóstico diferencial de PAP com quadros de dispneia crônica e progressiva, não explicadas por outras patologias mais prevalentes

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

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

Hepatitis B Virus Infection among Japanese Immigrants and Descendants: The Need to Strengthen Preventive and Control Measures

This cross-sectional study aimed to investigate the prevalence and risk factors of Hepatitis B virus infection among Japanese immigrants and their descendants from São Paulo (SP), and to verify the occurrence of occult hepatitis B and coinfection with HCV, Delta, and HTLV. All samples (n = 2.127) were tested for HBV serological markers by electrochemiluminescence. HBsAg and/or total anti-HBc positive samples were tested for HBV DNA by real-time PCR, and genotyped by sequencing using the Sanger methodology. The prevalence rate of HBV exposure was 13.4% (CI 95%: 11.9–14.9%), and 22 (1.1%) were HBsAg positive. A high rate of susceptibility to HBV infection was found (67.4%; CI 95%: 65.4–69.4%). In contrast, only 19.2% (CI 95%: 17.6–20.9%) presented a serological profile analogous to that elicited by Hepatitis B vaccination. HBV isolates (n = 8) were classified as genotypes HBV/B1 (62.5%), HBV/C2 (12.5%), HBV/F1b (12.5%), and HBV/A1 (12.5%). Hepatitis B vaccination strategies and educational measures to control this infection should be considered