Hypertension Is Associated With Intestinal Microbiota Dysbiosis and Inflammation in a Brazilian Population

Hypertension is a major global health challenge, as it represents the main risk factor for stroke and cardiovascular disease. It is a multifactorial clinical condition characterized by high and sustained levels of blood pressure, likely resulting from a complex interplay of endogenous and environmental factors. The gut microbiota has been strongly supposed to be involved but its role in hypertension is still poorly understood. In an attempt to fill this gap, here we characterized the microbial composition of fecal samples from 48 hypertensive and 32 normotensive Brazilian individuals by next-generation sequencing of the 16S rRNA gene. In addition, the cytokine production of peripheral blood samples was investigated to build an immunological profile of these individuals. We identified a dysbiosis of the intestinal microbiota in hypertensive subjects, featured by reduced biodiversity and distinct bacterial signatures compared with the normotensive counterpart. Along with a reduction in Bacteroidetes members, hypertensive individuals were indeed mainly characterized by increased proportions of Lactobacillus and Akkermansia while decreased relative abundances of well-known butyrate-producing commensals, including Roseburia and Faecalibacterium within the Lachnospiraceae and Ruminococcaceae families. We also observed an inflamed immune profile in hypertensive individuals with an increase in TNF/IFN-\u3b3 ratio, and in TNF and IL-6 production when compared to normotensive ones. Our work provides the first evidence of association of hypertension with altered gut microbiota and inflammation in a Brazilian population. While lending support to the existence of potential microbial signatures of hypertension, likely to be robust to age and geography, our findings point to largely neglected bacteria as potential contributors to intestinal homeostasis loss and emphasize the high vulnerability of hypertensive individuals to inflammation-related disorders

Relação entre as variáveis morfométricas extraídas de dados SRTM (Shuttle Radar Topography Mission) e a vegetação do Parque Nacional de Brasília

Este trabalho visa ao estudo da relação entre a distribuição de fitofisionomias do Parque Nacional de Brasília (PNB) e variáveis topográficas, para avaliar o potencial de dados SRTM isoladamente, como complemento aos dados tradicionalmente aplicados no sensoriamento remoto da vegetação. Esta relação foi verificada através de análises discriminantes entre o mapa de vegetação referência do PNB e as seguintes variáveis morfométricas: elevação, declividade, orientação de vertente, curvatura vertical e curvatura horizontal. Tais análises indicaram as classes de vegetação que podem ser separadas com base nas condições topográficas do terreno. As variáveis morfométricas mais importantes na distinção entre os tipos vegetacionais foram a elevação, a declividade e a orientação de vertente. Apesar de os dados morfométricos mostrarem potencial indicativo das classes de vegetação, as análises resultaram em discriminação em um nível aquém do detalhamento temático do mapa referência. Tal desempenho pode ser explicado pela incompatibilidade das escalas de variação exibidas entre os dados morfométricos em relação ao tamanho das unidades de mapeamento da vegetação. Além disso, a variação de tipos de vegetação do cerrado pode ser explicada por uma série de outros fatores além da topografia. Com base nas análises discriminantes das variáveis morfométricas, foi possível o mapeamento experimental da vegetação ao nível de subfisionomias.This paper aims to study the relationship between the distribution of vegetation in Brasilia National Park and topographic variables, to evaluate the potential of SRTM data alone, in addition to data traditionally used in remote sensing of vegetation. A map of vegetation of the area was used as a reference and the morphometric variables (elevation, slope, aspect and profile and plane curvatures) were compared to the mapped units. Analyses indicated vegetation types easily discriminated depending on topographic position. The variables elevation, slope and aspect were shown to be the most important for their high discrimination power of the vegetation types. Although morphometric data are recognized as having strong potential for characterizing vegetation, this was not shown in the results, due to the mismatching of variability scales between the two sources of data, where large units tend to exhibit similar distribution patterns of morphometry, and comprise classes with different responses for morphometric constraints. Discriminant analyses of morphometric variables allowed vegetation mapping up to sub-physiognomy levels