Different source of commercial vegetable oils may regulate metabolic, inflammatory and redox status in healthy rats.

Our goal was to carry out a comparative study to evaluate the metabolic and inflammatory effects and the redox status of commercial vegetable oils supplementation [linseed (LO), coconut (VCO), and sunflower (SO)] in metabolically healthy rats. The results found in this study showed that the LO group decreased the HOMA-IR and hepatic cholesterol, and increased the serum levels of IL-6. Supplementation with VCO increased glucose and HOMA-IR, cholesterol concentration and serum triacylglycerol (TAG). In this group, there was also an increase in TBARS. In the SO group there was a decrease in serum concentrations of cholesterol and TAG and an increase in hepatic concentration of these lipids. In addition, in the SO group there was a decrease in hepatic and s?rum concentrations of IL-6 and hepatic levels of TNF, as well as a decrease in the GSH/GSSG ratio, suggesting changes in glutathione metabolism and inflammatory mediators

Os primórdios da organização do espaço territorial e da vila cearense: algumas notas

This paper presents, in outline, the action taken by economic agents, representatives of the Church and the Portuguese State in organizing the space of the Captaincy of Ceará in the eighteenth century. The Portuguese State founded towns in strategic locations for better capitalization of the cattle breeder economy, where first settled sesmeiros and the Church. There was no reason or justification of geopolitical nature that demanded technical and financial investments by the Portuguese in the full adequacy of the local conditions to Portuguese urban guidelines. In the face of the late occupation, the article also discusses the late cartographic representation as expressing the lack of interests of the Portuguese administration in relation to a fuller understanding of the region

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