Heritability of motor skills: Study with monozygotic and dizygotic twins

El objetivo del estudio fue evaluar el poder relativo de contribución genética y ambiental de la variación de capacidades motoras en gemelos monocigóticos y dicigóticos. Método: participado 88 sujetos divididos en 56 monocigóticos y 32 dicigóticos de ambos sexos. Para la evaluación de la flexibilidad fue realizado el test de flexión de cadera; para la potencia de miembros inferiores fue aplicado el test contra movimiento y para la velocidad de desplazamiento, el test de carrera de 30m. Para determinar el índice de heredabilidad, utilizamos la ecuación: (h²) = (S²DZ–S²MZ)/S²DZx100. Fue utilizado tratamiento descriptivo y el test Shapiro-Wilk. Con la varianza de datos fueron calculados valores de tendencia central. Los datos fueron categorizados en percentiles de 25%. Resultados: flexibilidad 16%, velocidad de desplazamiento 83% y potencia de los miembros inferiores 70%.Conclusión: Fue evidenciado mayor heredabilidad para las variables de potencia y velocidad, y mayor influencia ambiental para la flexibilidadThe aim of the study was to assess the relative power of genetic and environmental contributions to the variation of motor skills in monozygotic and dizygotic twins. Method: For this study, participated 88 people divided in 56 monozygotic and 32 dizygotic twins of both sexes. For the assessment the flexibility, was performed hip flexion test, for assessment the lower limb power, was applied the test against movement and the speed of movement, the 30m running test. To determine the index of heritability, was used an equation: (h ²) = (S ²MZ- S²DZ) / S²DZx100. For the statistic, was used the descriptive treatment and Shapiro-Wilk test. The variance values were calculated, through the tendency central values. Data were categorized into percentiles of 25%. Results: Flexibility was 16% by heritability influence, speed of movement 83% of influence and for the lower limbs power were 70%. Conclusion: In this study was demonstrated higher heritability for the variables of lower limbs power and the speed of movement, and for the flexibility, a greater influence was linked for environmental factor

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence.

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor

Recomendações para o tratamento da crise migranosa - um consenso brasileiro

In this article, a group of experts in headache management of the Brazilian Headache Society developed through a consensus strategic measurements to treat a migraine attack in both the child and the adult. Particular emphasis was laid on the treatment of migraine in women, including at pregnancy, lactation and perimenstrual period743262271Neste artigo um grupo de especialistas no tratamento de cefaleia da Sociedade Brasileira de Cefaleia através de um consenso elaborou medidas estratérgicas para tratar uma crise de migrânea tanto na criança como no adulto. Uma enfase particular foi dada no tratamento da migranea na mulher, incluindo gravidez, lactação e período perimenstrua

Abundância de gavião-real e gavião-real falso numa área sob impacto de reservatório no Baixo e Médio rio Xingu

In the Brazilian Amazon, two monospecific genera, the Harpy Eagle and Crested Eagle have low densities and are classified by IUCN as Near Threatened due to habitat loss, deforestation, habitat degradation and hunting. In this study, we evaluate occurrence of these large raptors using the environmental surveys database from Belo Monte Hydroelectric Power Plant. Integrating the dataset from two methods, we plotted a distribution map along the Xingu River, including records over a 276-km stretch of river. Terrestrial surveys (RAPELD method) were more efficient for detecting large raptors than standardized aquatic surveys, although the latter were complementary in areas without modules. About 53% of the records were obtained during activities of wildlife rescue/flushing, vegetation suppression or in transit. Between 2012 and 2014, four Harpy Eagles were removed from the wild; two shooting victims, one injured by collision with power lines and one hit by a vehicle. Also, seven nests were mapped. The mean distance between Harpy Eagle records was 15 km along the river channel, with a mean of 20 km between nests near the channel, which allowed us to estimate 20 possible pairs using the alluvial forest, riverine forest and forest fragments. Territories of another ten pairs will probably be affected by inundation of the Volta Grande channel, which is far from the main river. The average distance between Crested Eagle records was 16 km along the river channel. The only nest found was 1.3 km away from a Harpy Eagle nest. The remnant forests are under threat of being replaced by cattle pastures, so we recommend that permanently protected riparian vegetation borders (APP) be guaranteed, and that forest fragments within 5 km of the river be conserved to maintain eagle populations. © 2015, Instituto Internacional de Ecologia. All rights reserved

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