APENDICITE AGUDA: ABORDAGEM DIAGNÓSTICA E AVANÇOS NO TRATAMENTO CIRÚRGICO.

Acute appendicitis is an inflammation of the cecal appendix, a frequent surgical emergency. Early diagnosis is vital to avoid serious complications. Migratory abdominal pain and associated symptoms help in the diagnosis. Imaging techniques, especially ultrasound and tomography, confirm the condition. The treatment is mainly surgical, with preferably laparoscopic appendectomy. Methodology: The research reviewed literature from 2015 to 2024 on "Acute Appendicitis: Diagnostic Approaches and Advances in Surgical Treatment", using scientific bases such as PubMed and SciELO. He selected original articles with full access, focused on clinical manifestations, imaging diagnoses and surgical advances, excluding studies out of scope or more than 10 years old. Results and discussions: The cecal appendix, located in the right iliac fossa, measures about 8 to 10 cm and may have an immunological role in childhood. Acute appendicitis usually results from appendicular obstruction, causing migratory abdominal pain and symptoms such as fever and nausea. The diagnosis involves clinical history, physical, laboratory and imaging techniques, with ultrasound and tomography being crucial. The use of low-dose CT and new scoring systems improve diagnostic accuracy and reduce negative appendectomy. Final considerations: Acute appendicitis is a common surgical emergency, requiring early diagnosis and treatment to avoid complications. Advanced techniques such as ultrasound and CT, especially low-dose, improve diagnostic accuracy. Appendictomy, preferably laparoscopic, is the standard treatment. Studies highlight the importance of combined diagnostic methods and surgical advances for better management.A apendicite aguda é uma inflamação do apêndice cecal, uma emergência cirúrgica frequente. O diagnóstico precoce é vital para evitar complicações graves. A dor abdominal migratória e sintomas associados ajudam no diagnóstico. Técnicas de imagem, especialmente ultrassonografia e tomografia, confirmam a condição. O tratamento é principalmente cirúrgico, com apendicectomia preferencialmente laparoscópica. Metodologia: A pesquisa revisou literatura de 2015 a 2024 sobre "Apendicite Aguda: Abordagens Diagnósticas e Avanços no Tratamento Cirúrgico", usando bases científicas como PubMed e SciELO. Selecionou artigos originais com acesso integral, focados em manifestações clínicas, diagnósticos por imagem e avanços cirúrgicos, excluindo estudos fora do escopo ou com mais de 10 anos. Resultados e discussões: O apêndice cecal, localizado na fossa ilíaca direita, mede cerca de 8 a 10 cm e pode ter um papel imunológico na infância. A apendicite aguda geralmente resulta de obstrução apendicular, causando dor abdominal migratória e sintomas como febre e náuseas. O diagnóstico envolve história clínica, exame físico, laboratoriais e técnicas de imagem, com ultrassonografia e tomografia sendo cruciais. O uso de TC de baixa dose e novos sistemas de pontuação melhoram a precisão diagnóstica e reduzem apendicectomias negativas. Considerações Finais: A apendicite aguda é uma emergência cirúrgica comum, necessitando de diagnóstico precoce e tratamento para evitar complicações. Técnicas avançadas como ultrassonografia e TC, especialmente de baixa dose, melhoram a precisão diagnóstica. A apendicectomia, preferencialmente laparoscópica, é o tratamento padrão. Estudos destacam a importância de métodos diagnósticos combinados e avanços cirúrgicos para melhor manejo

COMPARAÇÃO ENTRE DOENÇA DE PLUMMER E DOENÇA DE GRAVES: DIFERENÇAS CLÍNICAS, DIAGNÓSTICAS E TERAPÊUTICAS.

Plummer's Disease and Graves' Disease are prevalent hyperthyroid conditions with distinct pathophysiological mechanisms. While Plummer's Disease is characterized by autonomous nodules that produce hormones independently of TSH, Graves' Disease is an autoimmune condition with diffuse thyroid stimulation due to antibodies against the TSH receptor. Methodology: The research was conducted through online access to scientific databases such as Google Scholar, National Library of Medicine (PubMed), Virtual Health Library (BVS), and Scientific Electronic Library Online (SCIELO) for article selection, using keywords present in the descriptors: Plummer's Disease, Hyperthyroidism, Thyroid Ultrasonography, Graves' Disease, TSH Receptor Antibodies, and Exophthalmos. Results: Patients with Plummer's Disease present insidious hyperthyroid symptoms associated with palpable thyroid nodules, diagnosed by scintigraphy showing heterogeneous uptake. In Graves' Disease, in addition to the classic signs of hyperthyroidism, exophthalmos and other autoimmune symptoms are common, with diagnosis confirmed by TSH receptor antibodies and scintigraphy with diffuse uptake. Treatments for Plummer's Disease include radioactive iodine therapy and surgery, while for Graves' Disease, the initial approach is with antithyroid medications, followed by radioactive iodine therapy or surgery in refractory cases. Final considerations: Differentiating between Plummer's Disease and Graves' Disease is essential for effective treatment. Plummer's Disease requires interventions focused on hyperfunctioning nodules, while Graves' Disease necessitates a comprehensive approach that includes managing autoimmune manifestations. Personalized treatment based on the specific etiology of hyperthyroidism is crucial to optimizing therapeutic outcomes and patient quality of life. Keywords: Hyperthyroidism, Plummer's Disease, Graves' Disease, Differential Diagnosis, Thyroid Therapies, AutoimmunityA Doença de Plummer e a Doença de Graves são condições prevalentes de hipertireoidismo com distintos mecanismos patofisiológicos. Enquanto a Doença de Plummer é caracterizada por nódulos autônomos que produzem hormônios independentemente do TSH, a Doença de Graves é uma condição autoimune com estimulação difusa da tireoide devido a anticorpos contra o receptor de TSH. Metodologia:A pesquisa foi realizada através do acesso online nas bases de dados científicos como: Google Scholar, National Library  of Medicine(PubMed), Biblioteca Virtual em Saúde (BVS) e Scientific  Electronic  Library  Online(SCIELO) para seleção dos artigos, através de palavras-chave presentes nos descritoresPlummer's Disease, Hyperthyroidism, Thyroid Ultrasonography, Graves' Disease, TSH Receptor Antibodies e Exophthalmos. Resultados:  Pacientes com Doença de Plummer apresentam sintomas insidiosos de hipertireoidismo associados a nódulos tireoidianos palpáveis, diagnosticados por cintilografia mostrando captação heterogênea. Na Doença de Graves, além dos sinais clássicos de hipertireoidismo, são comuns exoftalmia e outros sintomas autoimunes, com diagnóstico confirmado por anticorpos antirreceptor de TSH e cintilografia com captação difusa. Tratamentos para Doença de Plummer incluem iodoterapia radioativa e cirurgia, enquanto para Doença de Graves, a abordagem inicial é com medicamentos antitireoidianos, seguidos de iodoterapia ou cirurgia em casos refratários.Considerações Finais: A diferenciação entre Doença de Plummer e Doença de Graves é essencial para um tratamento eficaz. A Doença de Plummer requer intervenções focadas nos nódulos hiperfuncionantes, enquanto a Doença de Graves necessita de uma abordagem ampla que inclui o manejo das manifestações autoimunes. A personalização do tratamento baseada na etiologia específica do hipertireoidismo é fundamental para otimizar os resultados terapêuticos e a qualidade de vida dos pacientes

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