EFEITO DO Schinus terebinthifolius NA INIBIÇÃO DE CRESCIMENTO BACTERIANO E QUEBRA DE BIOFILME IN VITRO: RESULTADOS PRELIMINARES

Endometritis is considered as one of the main causes of subfertility and infertility in mares, having a great economic impact on equine industry. Chronic uterine infections resistant to antimicrobial agents can be caused due to the production of biofilm. Phytoterapy products provide a great potential for the production of new drugs due to their structural diversity. Schinus terebinthifolius, is a plant with antiseptic and anti-inflammatory. In clinical studies, its therapeutic action has been proven in cervicitis and chronic cervical-vaginitis in women. Thus, the objective of this work was to evaluate in vitro the growth in clinical bacterial isolates, production of biofilm and its breakdown against different concentrations of a medication based on Schinus terebinthifolius (Kronel®). As a result, a numeric reduction in bacterial growth was observed, as well as a partial break in the biofilm directly proportional to the concentration of Schinus terebinthifolius used. Different activities were also found according to bacteria tested. Despite being preliminary data, it was possible to observe a positive action both in the inhibition of growth and in the partial breakdown of a natural commercial product obtained from Schinus terebinthifolius in the bacterial treatment in vitro.A endometrite é considerada uma das principais causas de subfertilidade e infertilidade em éguas, tendo grande impacto econômico na equinocultura. Infecções uterinas crônicas resistentes a agentes antimicrobianos podem ser causadas devido à produção de biofilme. Os produtos fitoterápicos apresentam grande potencial para a produção de novos fármacos devido à sua diversidade estrutural. Schinus terebinthifolius, é uma planta com propriedades antissépticas e anti-inflamatórias. Em estudos clínicos, sua ação terapêutica foi comprovada em cervicite e cervical-vaginite crônica em mulheres. Assim, o objetivo deste trabalho foi avaliar in vitro o crescimento de isolados bacterianos clínicos, produção de biofilme e sua degradação frente a diferentes concentrações de um medicamento à base de Schinus terebinthifolius (Kronel®). Como resultado, observou-se uma redução numérica no crescimento bacteriano, bem como uma quebra parcial no biofilme diretamente proporcional à concentração de Schinus terebinthifolius utilizada. Diferentes atividades também foram encontradas de acordo com as bactérias testadas. Apesar de serem dados preliminares, foi possível observar uma ação positiva tanto na inibição do crescimento quanto na quebra parcial de um produto comercial natural obtido de Schinus terebinthifolius no tratamento bacteriano in vitro

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