Long-term Bias of Internal Markers in Sheep and Goat Digestion Trials

Two digestion trials, one with sheep and another with goats, were conducted to evaluate the long-term bias (LTB) of the indigestible dry matter (iDM), indigestible neutral detergent fiber (iNDF) and indigestible acid detergent fiber (iADF) internal markers. The study used eight Santa Inês castrated male sheep (average body weight of 16.6 kg) distributed in two 4×4 Latin squares and eight Saanen castrated male goats (average body weight of 22.6 kg) distributed in two 4×4 Latin squares. The experiments were conducted simultaneously, and the animals were housed in 1.2 m2 individual pens with wood-battened floors equipped with individual feeders and drinkers. The animals received isonitrogenous diets that were offered ad libitum and contained 14% crude protein and 70% sugar cane (with 0, 0.75, 1.5 or 2.25% CaO, in natural matter percentage), corrected with 1% urea and 30% concentrate. The experiment consisted of four experimental periods of 14 d each, with the feed, leftovers and feces sampled on the last four days of each period. The marker concentrations in the feed, leftovers and fecal samples were estimated by an in situ ruminal incubation procedure with a duration 240 h. The relationship between the intake and excretion of the markers was obtained by adjusting a simple linear regression model, independently from the treatment (diets) fixed effects and Latin squares. For both the sheep and goats, a complete recovery of the iDM and iNDF markers was observed (p>0.05), indicating the absence of LTB for these markers. However, the iADF was not completely recovered, exhibiting an LTB of −9.12% (p<0.05) in the sheep evaluation and −3.02% (p<0.05) in the goat evaluation

Os principais tipos e manifestações da Cirrose Hepática: uma atualização clínica

Introdução: A cirrose hepática é um processo patológica crônico, considerado a hepatopatia mais comum, definido como a conversão difusa morfoestrutural por nódulos de arquitetura anômalo envoltos por fibrose. Objetivou-se&nbsp;descrever os tipos mais relevantes de cirrose e suas devidas manifestações. Metodologia: Trata-se de uma revisão bibliográfica, fundamentada nas plataformas do SciELO, PubMed, Scopus, utilizando os termos “hepatical cirrhosis”, “liver disease” e “hepatocellular insufficiency” a qual através da revisão narrativa, abordou amplamente a respeito da contextualização da cirrose e as principais etiologias. Resultados e Discussão: Foi analisado que tal condição afeta qualquer faixa etária, sexo, etnia e independe da classe socioeconômica, mas as diversas etiologias impõem um perfil epidemiológico específico conforme a aparição. As principais origens abordam o tipo alcoólico, hepatite, aplicação crônica de alguns fármacos e esteatose gordurosa ou não. Ademais, estima-se que estas afetam a anatomofuncionalidade do órgão responsável por grande parte da homeostase, culminando em diversas manifestações clínicas.&nbsp; Conclusão: A cirrose é uma consequência grave de fatores de base em estágio avançado, a qual devido ao seu curso geralmente silencioso culmina no desenvolvimento e progressão clínica. Neste contexto, a atenção aos fatores predisponentes como alimentação rica em lipídios, estilismo, negligência a exames de rotina, sedentarismo e obesidade contribuem constituem medidas eficazes de prevenção primária.&nbsp

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