The evaluation of in vitro antichagasic and anti-SARS-CoV-2 potential of inclusion complexes of β- and methyl-β-cyclodextrin with naphthoquinone

Funding Information: The authors thank the Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Council for Scientific and Technological Development (CNPq) for their financial support. This study was supported by the CAPES — number 88887.505029/2020–00 . Cecilia Gomes Barbosa receives a scholarship funded by CAPES — number 88887.643352/2021–00 . Publisher Copyright: © 2023 Elsevier B.V.The compound 3a,10b-dihydro-1H-cyclopenta[b]naphtho[2,3-d]furan-5,10-dione (IVS320) is a naphthoquinone with antifungal and antichagasic potential, which however has low aqueous solubility. To increase bioavailability, inclusion complexes with β-cyclodextrin (βCD) and methyl-β-cyclodextrin (MβCD) were prepared by physical mixture (PM), kneading (KN) and rotary evaporation (RE), and their in vitro anti-SARS-CoV-2 and antichagasic potential was assessed. The formation of inclusion complexes led to a change in the physicochemical characteristics compared to IVS320 alone as well as a decrease in crystallinity degree that reached 74.44% for the IVS320-MβCD one prepared by RE. The IVS320 and IVS320-MβCD/RE system exhibited anti-SARS-CoV-2 activity, showing half maximal effective concentrations (EC50) of 0.47 and 1.22 μg/mL, respectively. Molecular docking simulation suggested IVS320 ability to interact with the SARS-CoV-2 viral protein. Finally, the highest antichagasic activity, expressed as percentage of Tripanosoma cruzi growth inhibition, was observed with IVS320-βCD/KN (70%) and IVS320-MβCD/PM (72%), while IVS320 alone exhibited only approximately 48% inhibition at the highest concentration (100 μg/mL).publishersversionpublishe

The inventory of geological heritage of the state of São Paulo, Brazil: Methodological basis, results and perspectives

An inventory of geological sites based on solid and clear criteria is a first step for any geoconservation strategy. This paper describes the method used in the geoheritage inventory of the State of São Paulo, Brazil, and presents its main results. This inventory developed by the geoscientific community aimed to identify geosites with scientific value in the whole state, using a systematic approach. All 142 geosites representative of 11 geological frameworks were characterised and quantitatively evaluated according to their scientific value and risk of degradation, in order to establish priorities for their future management. An online database of the inventory is under construction, which will be available to be easily consulted and updated by the geoscientific community. All data were made available to the State Geological Institute as the backbone for the implementation of a future state geoconservation strategy.The authors acknowledge the Science Without Borders Programme, Process 075/2012, which supported this study and the São Paulo Research Foundation (FAPESP), Process 2011/17261-6. We also thanks C. Mazoca for his help with maps and figures.info:eu-repo/semantics/acceptedVersio

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

Avaliação agronômica de parentais e híbridos de maracujazeiro- amarelo Agronomic evalution of parental and hybrid of yellow passion fruit

O presente trabalho objetiva determinar o potencial agronômico de genótipos de maracujazeiro-amarelo, visando a identificar e selecionar híbridos promissores. O experimento foi conduzido em área de produção no município de Cruz das Almas (BA), em delineamento de blocos casualizados, com três repetições, 41 genótipos (30 híbridos e 11 parentais), com parcela de 4 plantas. As características avaliadas foram: produtividade; número de frutos; massa média de frutos; espessura de casca; rendimento de suco; produtividade de suco e teor de sólidos solúveis totais. Houve diferença significativa entre os genótipos a 1% de probabilidade pelo teste F, para todas as variáveis em estudo, exceto para a característica rendimento de suco (p<0,06). Os genótipos avaliados apresentaram altas amplitudes para todas as características, o que indica situação favorável para a seleção dos melhores para recomendação. Contudo, observou-se que a maioria das características adequadas para uma boa cultivar de maracujazeiro está presente em diferentes genótipos, com existência de algumas correlações indesejáveis. Dentre as correlações genotípicas positivas de maior importância, estão PROD x NF (0,78) e PROD x PRSUC (0,81). Entretanto, a utilização de índices de seleção de Mulamba & Mock e a distância genótipo-ideótipo possibilitou a indicação de três híbridos (H09-10, H09-14 e H09-20) que apresentaram médias elevadas e equilibradas para as sete características avaliadas, devendo ser validados em outras regiões de produção do maracujazeiro-amarelo.<br>The present study aims to determine the agronomic potential of genotypes of yellow passion fruit, to identify and select promising hybrid. The experiment was conducted in the production area in Cruz das Almas (BA) in a randomized block design with three replications, 41 genotypes (30 hybrids and 11 parents), in a share of four plants. The characteristics evaluated were: yield, number of fruits, average mass fruit, peel thickness, juice yield, and total soluble solids. There were significant differences between genotypes for the F test for all variables studied, except for juice yield (p<0.06). High amplitudes for all traits were observed, showing favorable situation to select the best genotypes for recommendation. However, it was observed that the most suitable traits for a good yellow passion fruit cultivar are presented in different genotypes, with existence of some undesirable correlations. Among the positive genotypic correlation of greater importance are yield x number of fruits (0.78) and yield x juice productivity (0.81). However, the use of the selection indexes of Mulamba & Mock (MM) and genotype-ideotype distance, allowed the appointment of three hybrids (H09-10, H09-14 and H09-20) with high average and balanced averages to the seven traits evaluated and should be validated in other regions of production of yellow passion fruit

Genetic parameters in agronomic characters for selection of superior lineages of Ricinus communis L

ABSTRACT: Knowledge on the variability and heritability of agronomic characters of interest aid the selection of superior materials. Thus, the objective of this study was to evaluate the genetic parameters of agronomic traits in castor bean plant lineages and to quantify the genetic correlations between them. The study was performed in the experimental area of the Federal University of the Recôncavo da Bahia, Cruz das Almas, Bahia. Seed oil content, vegetative cycle, plant height, and the number and weight of seeds per plant were evaluated in 47 lineages of castor bean seedlings. The coefficient of genetic variation was higher for weight of seeds per plant, revealing greater variability. The broad-sense heritability of individual plots presented a higher value for oil content and a lower value for seed number per plant. Selection precision was moderate for plant height, number and weight of seeds per plant, high for vegetative cycle, and very high for oil content. The genetic parameters allowed superior genotypes to be ranked and selected. Positive correlations between vegetative cycle and plant height, associated with negative correlations for number and weight of seeds, and oil content, allow significant gains for crop productivity