Associação entre a espessura do músculo adutor do polegar e parâmetros nutricionais em idosos hospitalizados / Association between adductor pollicis muscle thickness and nutritional parameters in hospitalized elderly patients

INTRODUÇÃO: O processo de senescência é caracterizado por diversas alterações fisiológicas, psicológicas, sociais e funcionais que repercutem no estado nutricional dos indivíduos idosos, podendo contribuir de forma expressiva para a morbimortalidade dessa população. A medida da espessura do músculo adutor do polegar vem sendo utilizada como um parâmetro preditor do estado nutricional, visto que, como todos os músculos periféricos, é atrofiado por inatividade e consumido durante o catabolismo, além de sua espessura ser uma medida de fácil obtenção. Em idosos, observam-se poucos estudos que avaliem a espessura do músculo adutor do polegar como preditor do estado nutricional. OBJETIVOS: Avaliar a associação da espessura do músculo adutor do polegar com outros métodos de avaliação do estado nutricional em idosos hospitalizados. MÉTODO: Trata-se de um estudo observacional e transversal, realizado com 51 idosos a partir de 60 anos, de ambos os sexos, admitidos na clínica médica do Hospital Universitário Lauro Wanderley em João Pessoa, Paraíba, entre os meses de março a julho de 2019. Para avaliação do estado nutricional utilizou-se como parâmetros a espessura do músculo adutor do polegar (EMAP), a mini avaliação nutricional (MAN), o índice de massa corporal (IMC), a circunferência da panturrilha (CP), circunferência do braço (CB) e circunferência muscular do braço (CMB). Os dados coletados foram inseridos em banco de dados e avaliados pelo programa estatístico Statistical Package for Social Science 13.0. Os resultados foram considerados estatisticamente significantes para um valor de p < 0,05. RESULTADOS: A amostra foi composta por idosos com média de idade de 70,12 ± 6,87 anos, dos quais 56,9% possuíam idade entre 60 e 69 anos e 54,9% do sexo feminino. Na análise de associação entre a EMAP e a MAN obteve-se diferença significativa (p=0,036) entre os valores médios da EMAP dos pacientes eutróficos (13,15 ± 4,0) e os em risco de desnutrição (10,43±3,4) ou desnutridos (9,62 ± 2,3). Houve também diferença significativa (p=0,045) entre as médias de EMAP dos pacientes classificados, através da CP, como eutróficos (11,61 ± 4,1) e como depletados (9,80 ± 2,1). CONCLUSÃO: Os achados da presente análise demonstram que houve associação entre EMAP e MAN e EMAP e CP, podendo assim ser considerada um bom indicador do estado nutricional de idosos hospitalizados. O uso da EMAP deve ser associado a outros métodos antropométricos para uma avaliação mais completa. 

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

Genomic imbalances defining novel intellectual disability associated loci

High resolution genome-wide copy number analysis, routinely used in clinical diagnosis for several years, retrieves new and extremely rare copy number variations (CNVs) that provide novel candidate genes contributing to disease etiology. The aim of this work was to identify novel genetic causes of neurodevelopmental disease, inferred from CNVs detected by array comparative hybridization (aCGH), in a cohort of 325 Portuguese patients with intellectual disability (ID).This work has been funded by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE), and by National funds, through the Foundation for Science and Technology (FCT), under the scope of the projects: PIC/IC/83026/2007, PIC/IC/83013/2007 and POCI-01-0145-FEDER-007038. This work has also been funded by the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). FL was supported by Foundation for Science and Technology (FCT) through the fellowship SFRH/BD/90167/2012

Resumos concluídos - Neurociências

Resumos concluídos - Neurociência