Síndrome de Allgrove e amiotrofia: uma associação rara

A Síndrome de Allgrove é uma doença rara hereditária, causada por mutações no gene AAAS, que possui uma tríade clássica de sintomas caracterizada por alacrimia, acalasia e insuficiência adrenal. Além da tríade, sinais neurológicos como disfunção autonômica, microcefalia, disfunção cognitiva ou demência leve, doença do neurônio motor/amiotrofia e outros podem ser mencionados em até 70% dos casos. Nessa perspectiva, o objetivo desse trabalho é a realização de um estudo observacional e exploratório sobre os artigos publicados nos últimos 5 anos sobre associação rara entre a síndrome de allgrove e amiotrofia, uma vez que essa é uma comorbidade rara da síndrome. Dos 140 resultados obtidos na pesquisa, apenas 9 abordaram de forma objetiva sobre o tema, sendo utilizados na confecção do estudo. Segundo a literatura, a amiotrofia é uma comorbidade rara da síndrome de Allgrove, que possui grande relevância devido ao seu curso rápido e progressivo

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

Poder legislativo e política externa na América Latina

De uma maneira geral, a ciência política moderna informa que as regras eleitorais são fatores centrais na geração de incentivos para aqueles que buscam se eleger; ou seja, uma das características mais essenciais do sistema político. Dessa forma, a literatura associa o funcionamento dessas instituições com uma série de fenômenos, sejam eles políticos ou não: grau de participação; accountability; violência e instabilidade; gastos governamentais e déficits fiscais; gastos sociais; e distribuição de renda, entre outros. Sobre a relação entre as regras eleitorais e seus resultados econômicos, os achados da literatura comparada e as predições de seus modelos teóricos fornecem explicações que podem ser utilizadas para se pensar a lógica da proteção comercial, especialmente no que diz respeito aos mecanismos causais atribuídos às instituições.Introdução; Poder Legislativo e Política Externa nos EUA; Poder Legislativo e Política Externa na América Latina; Considerações teóricas para a construção de hipóteses: Poder Legislativo e política externa sob uma lógica de dois níveis; Apresentação das hipóteses; Estrutura institucional dos países em análise; Argentina; Brasil; Chile; México; Avaliação final sobre a estrutura institucional; O Poder Legislativo e a Política Comercial Negociada na Argentina, no Brasil, no Chile e México; Conclusão; Bibliografia

Maternal depression and anxiety associated with dental fear in children: a cohort of adolescent mothers in Southern Brazil

<div><p>Abstract Exposure to maternal symptoms of depression/anxiety has long-term negative consequences for child development, regardless of the contextual risk. The objective of this study was to investigate the relationship of the symptomatology of persistent maternal depression and anxiety with child dental fear. This study was nested in a cohort of adolescent mothers in southern Brazil. Symptomatology of maternal depression and anxiety was assessed during pregnancy and postpartum, when the mothers’ children were 24-36 months old, using Beck Depression Inventory and Beck Anxiety Inventory. The mothers answered a questionnaire to assess dental fear in their children, and to obtain socioeconomic and demographic data. Both mothers and their children were submitted to clinical oral examination (n= 540 dyads) to obtain oral health data. Multivariate hierarchical Poisson regression analysis was used to determine associations (p < 0.05). At data collection, the prevalence of maternal depressive symptoms was 39.1%, and anxiety was observed in 27.8% of the mothers, whereas 21.6% of the children presented dental fear. In the adjusted analysis, children’s dental fear was positively associated with mothers’ presenting depressive symptomatology and caries experience. The depression symptomatology trajectory was not associated with dental fear, whereas mothers with persistent symptoms of anxiety reported higher prevalence of dental fear toward their offspring. The findings of symptomatology of maternal depression observed at data collection and persistence of anxiety may negatively impact the child’s perception of dental fear. Mothers are the main caregivers and primary models responsible for transmitting health-related behaviors; consequently, mental disorders affecting mothers may negatively impact their children.</p></div