Desafio em Estimulação Cardíaca Artificial

Paciente do sexo feminino, com 54 anos de idade, com hipertensão arterial e febre reumática prévia apresentou bloqueio atrioventricular total após troca de valva mitral (prótese biológica) e plastia de valva mitral. Foi submetida a implante de marcapasso bicameral atrioventricular (Figura 1) havia três anos quando retornou para uma avaliação eletrônica do marcapasso queixando-se de palpitações taquicárdicas de início súbito associadas à sensação pulsátil em fúrcula esternal e fadiga durante esforços de rotina. Na admissão, foi realizado o  eletrocardiograma de repouso (Figura 2). Com o objetivo de avaliar melhor o ritmo para os átrios, foi realizado o registro eletrocardiográfico com velocidade = 50 mm/s (Figura 3). Esta manobra permitiu a visualização de um entalhe no final da onda T, correspondente à ativação elétrica dos átrios. Assim, o médico plantonista iniciou terapia com amiodarona endovenosa e solicitou uma avaliação da equipe de estimulação cardíaca artificial

Productive and economic performance of feedlot young Nellore bulls fed whole oilseeds

ABSTRACT The effects of diets containing oilseeds were measured to evaluate the productive and economic parameters in the finishing of young, feedlot Nellore bulls. Twenty-four young Nellore bulls were used, with an initial body weight (BW) of 311.46±0.37 kg and 24 months of age, distributed into individual stalls ( 4 × 20 m) in a completely randomized design, totaling four treatments with six repetitions per treatment. Four diets (control, based on corn and soybean meal, and three diets containing cottonseed, soybean, and sunflower) were evaluated. Feed and orts were measured daily to calculate intake and costs. The dry matter intake of the control group was higher than soybean (10.64 kg/day), cotton (9.88 kg/day), and sunflower (9.30 kg/day) treatments, respectively. The cottonseed treatment showed the highest average neutral detergent fiber intake. There was a dietary effect of diets on average daily gain, total weight gain, and final weight. The soybean treatment showed the highest performance, total gain (232.55 kg), and final weight (544.38 kg). Oilseed intake can modify the fatty acids profile in the meat, decreasing its saturated fatty acid content. Whole soybean seed favors performance, improves feed efficiency, fatty acid profile, and fat distribution in the carcass, and can reduce production costs

Métodos diagnósticos de Toxoplasmose Congênita: revisão de literatura

 This article aims to evaluate the diagnostic methods for congenital toxoplasmosis. This is an integrative review using the VHL, SciELO, LILACS and PubMed as databases over the last 5 years. 272 articles on the topic were evaluated with an emphasis on a synthesis of the most recent knowledge and greater scientific consistency. We found that, despite the performance of real-time PCR, it is relevant to consider less invasive methods, as it depends on amniocentesis.Este artigo tem por objetivo avaliar os métodos diagnósticos de toxoplasmose congênita. Trata-se de uma revisão integrativa utilizando como base de dados a BVS, a SciELO, o LILACS e o PubMed, nos últimos 5 anos. Foram avaliados 272 artigos sobre o tema com ênfase em uma síntese dos conhecimentos mais recentes e de maior consistência científica. Verificamos que, apesar do desempenho da PCR em tempo real, é relevante considerar métodos menos invasivos, visto que depende de amniocentese

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states

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