Caracterização e atividade biológica de taninos condensados de leguminosas forrageiras tropicais

The objective of this work was to characterize condensed tannins (CT) from six tropical forage legumes and to determine their biological activity. The monomers propelargonidin, prodelphinidin and procyanidin were analyzed, as well as extractable condensed tannin (ECT), protein-bound CT (PBCT) and fiber-bound CT (FBCT), molecular weight, degree of polymerization, polydispersity index, and biological activity by protein precipitate by phenols (PPP) of leaves of the legumes Cajanus cajan, Gliricidia sepium, Stylosanthes capitata x Stylosanthes macrocephala (stylo), Flemingia macrophylla, Cratylia argentea, and Mimosa caesalpiniifolia, and of the bark of this latter species. Differences were observed in the concentrations of ECT, PBCT, PPP, and total condensed tannin among species, but not in that of FBCT. The highest value of PBCT occurred in F. macrophylla. Total CT varied from nondetected concentration in C. argentea to the highest concentration in M. caesalpiniifolia leaves that contain the greatest levels of PPP. No differences were observed for polymerization degree in stylo, F. macrophylla, and M. caesalpiniifolia. Leaves of stylo, C. cajan, and G. sepium, all containing between 20 and 50 g kg-1 total CT, should be beneficial CT sources, if offered as sole feeds in ruminant diets. The ratio of prodelphinidin:procyanidin varies from 10:80 (stylo) to 65:35 (F. machrophylla), and propelargonidin is only determined in C. argentea.O objetivo deste trabalho foi caracterizar taninos condensados de seis leguminosas forrageiras e determinar sua atividade biológica. Os monômeros propelargonidina, prodelfinidina e procianidina foram analisados, assim como taninos condensados extraíveis (TCE), taninos condensados ligados a proteínas (TCLP) e ligados a fibras (TCLF), massa molecular, grau de polimerização, índice de polidispersão e atividade biológica, por meio de proteínas precipitadas por fenóis (PPF), em folhas das leguminosas Cajanus cajan, Gliricidia sepium, Stylosanthes capitata x Stylosanthes macrocephala (estilosantes), Flemingia macrophylla, Cratylia argentea e Mimosa caesalpiniifolia, e na casca desta última espécie. Foram observadas diferenças nas concentrações de TCE, TCLP, PPF e total de taninos condensados entre as espécies, mas não na de TCLF. O maior valor de TCLP ocorreu em F. macrophylla. O total de TC variou de não detectável em C. argentea à maior concentração em folhas de M. caesalpiniifolia, que contêm os maiores níveis de PPF. Não se observaram diferenças quanto ao grau de polimerização em estilosantes, F. macrophylla e M. caesalpiniifolia. Folhas de estilosantes, C. cajan e G. sepium, todas com total de TC entre 20 e 50 g kg-1, poderiam ser fontes benéficas de TC, se oferecidas como única fonte de alimentos em dietas de ruminantes. A proporção prodelfinidina:procianidina variou de 10:80 (stylo) a 65:35 (F. machrophylla), e a propelargonidina é determinada somente em C. argentea

Evaluation of therapeutic drug protocol used for control of pain after dental extractions / Avaliação do protocolo terapêutico medicamentoso utilizado para o controle da dor após exodontias

Pain control after surgery is one of the factors concern of surgical specialties. Aim of this study is to evaluate and compare the efficacy of nimesulide 100 mg and dipyrone monohydrate 500 mg used after extractions performed by a maxillofacial surgery UFPI services in order to support the drug choice appropriately, prioritizing the analgesic effect needed to patients undergoing interventions. Forty patients underwent extractions in the clinic of the UFPI, in the Health Center Poty Velho and Emergency Hospital of Promorar. Patients were divided into groups: undergoing intervention with and without ostectomy. Dipyrone monohydrate 500 mg or nimesulide 100 mg produced by compounding pharmacy, were prescribed for patients randomly, featuring a blind study. The intensity of pain after the extraction was assessed by patients using a visual analogue scale, in a postoperative period of 72 hours at 24 hour intervals. There was no statistical variation between the analgesics studied during the 3 days postoperatively evaluated, considering the presence or absence of ostectomy as a modifier of the search. Analgesia effect of nimesulide was similar to dipyrone according to the present study

Desafios e dificuldades da extensão universitária multicampi: uma experiência na UFVJM

Em universidades multicampi, garantir a acessibilidade dos estudantes a projetos em outros campi é um desafio. Neste trabalho é relatada uma experiência interdisciplinar e multicampi em um projeto de extensão da UFVJM, durante os anos de 2021 e 2022. No total, estiveram envolvidos 45 alunos, de 3 campi e 10 cursos distintos, em atividades conduzidas de forma remota, tais como, a criação de conteúdo textual e material audiovisual, culminando também na realização de um workshop online, trabalhos de conclusão de curso e publicação de artigos científicos. As atividades remotas ampliaram a acessibilidade ao projeto e ofereceram flexibilidade de horários para professores e estudantes, além de permitir a interação entre discentes de diferentes cursos. No entanto, houveram desafios devido à comunicação ineficiente durante o processo de seleção de estudantes, a falta de acesso à internet e recursos computacionais de alta qualidade

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

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