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

Synthesis and biological evaluation of thiazole derivatives as LbSOD inhibitors

Leishmaniasis is considered as one of the major neglected tropical diseases due to its magnitude and wide geographic distribution. Leishmania braziliensis, responsible for cutaneous leishmaniasis, is the most prevalent species in Brazil. Superoxide dismutase (SOD) belongs to the antioxidant pathway of the parasites and human host. Despite the differences between SOD of Leishmania braziliensis and human make this enzyme a promising target for drug development efforts. No medicinal chemistry effort has been made to identify LbSOD inhibitors. Herein, we show that thermal shift assays (TSA) and fluorescent protein-labeled assays (FPLA) can be employed as primary and secondary screens to achieve this goal. Moreover, we show that thiazole derivatives bind to LbSOD with micromolar affinity

Discovery of New Inhibitors of Schistosoma mansoni PNP by Pharmacophore-Based Virtual Screening

Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma monsoni, one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 mu M. The most potent inhibitors 7, 10, and 17 with 1050 of 2, 18, and 38 mu M, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis.FAPESP (The State of Sao Paulo Research Foundation)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CNPq (The National Council for Scientific and Technological Development), BrazilConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

In Vitro and In Vivo Wound Healing and Anti-Inflammatory Activities of Babassu Oil (Attalea speciosa Mart. Ex Spreng., Arecaceae)

Babassu (Attalea speciosa Mart. ex Spreng., Arecaceae) is a palm tree endemic to Brazil and found mainly in the borders of Amazon forest, where the harvesting of its fruits is an important source of income for more than 300,000 people. Among the communities of coconut breakers women, babassu oil is used in culinary, as fuel, and mostly as medicinal oil for the treatment of skin wounds and inflammation. This study aimed to evaluate in vitro and in vivo the wound healing effects of babassu oil. In vitro, babassu oil increased the migration of L929 fibroblasts, inhibited the production of nitric oxide by LPS-stimulated peritoneal macrophages, and increased the levels of INF-γ and IL-6 cytokines production. In vivo, babassu oil accelerated the healing process in a full-thickness splinted wound model, by an increase in the fibroblasts number, blood vessels, and collagen deposition in the wounds. The babassu oil also increased the recruitment of inflammatory cells into the wound site and showed an anti-inflammatory effect in a chronic ear edema model, reducing ear thickness, epidermal hyperplasia, and myeloperoxidase activity. Thus, these data corroborate the use of babassu oil in folk medicine as a remedy to treat skin wounds