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

Isolation of a lipase-producing Trichosporon spp and enzyme extraction by two-phase aqueous system Isolamento de Trichosporon spp produtor de lipase e extração enzimática pelo sistema bifásico aquoso

A lipase-producing yeast strain isolated from crude cheese and identified as Trichosporon spp produced 7.3 U/mL (59.3 U/µg) after 72h of cultivation. Lipase showed optimum activity at pH 7.0-8.0 and 45-50ºC. Extraction by the two-phase aqueous system (PEG-phosphate salts) showed an elevated recuperation (99.8%) of enzymatic activity in the PEG phase.<br>Uma levedura produtora de lipase isolada de queijo coalho e identificada como Trichosporon spp produziu 7,3 U/mL (59,3 U/µg) após 72h de cultivo. A lipase mostrou atividade ótima em pH 7,0-8,0 e temperatura ótima entre 45-50ºC. Extração pelo sistema PEG - sais de fosfato apresentou 99,8% de recuperação da atividade enzimática na fase PEG

Acute Toxicity and Cytotoxicity Effect of Ethanolic Extract of Spondias tuberosa Arruda Bark: Hematological, Biochemical and Histopathological Evaluation

ABSTRACT Spondias tuberosa Arruda, popularly named as umbu, is native from savanna-like vegetation and widely used for medicinal purposes, however, the toxicological profile is not available yet. This study evaluated the phytochemical profile and acute toxicity and citoxicity of Ethanolic Extract of Spondias tuberosa Arruda Bark (EEStb) in hematological, biochemical and histopathological parameters. Female Wistar rats were divided into: control (C) and animal treated single doses of 300mg/Kg (EEStb300) or 2.000mg/kg body weight (ESStb2.000) of the EEStb. After 24 hours and 14 days from gavage, the behavior, hematological, biochemical and histopathological parameters were assayed. Cytotoxicity effect was evaluated on HEp-2 cell lines. Neither EEStb300 nor EEStb2.000 produced mortality nor changes in body weight during the 14-days of observation, but EEStb2.000 reduced quietly the food and water intake as well as locomotor activity at first day. There were no changes in macroscopic, histopathological, biochemical and hematological parameters. EEStb in concentrations of 6.25- 50μg ml−1 on HEp-2 cell did not produce cytotoxic effect. These results suggest that EEStb did not cause acute toxicity and cytotoxic, suggesting a good safety rate for Spondias tuberosa Arruda