Synthesis and Phytotoxicity of 4,5 Functionalized Tetrahydrofuran-2-ones

In this work we report a versatile synthesis of fourteen γ-lactones all structurally related, nine of which are novel compounds, accomplished from the readily available furfural. The phytotoxic activity of the synthesized compounds was evaluated in vitro by the influence on the growth of wheat coleoptiles. The percentages of inhibition were mostly small and not statistically different from control after the third dilution (100 μmol L-1). In general, α,β-unsaturated lactones presented better activities than the saturated ones. The most active compounds presented 51, 68 and 76% of inhibition in 1000 µmol L-1. The results indicate that regardless of saturation, the presence of the γ-lactone moiety is important for the bioactivity, but their presence has no implications with potency

Toxicity and sublethal effects of phthalides analogs to Rhyzopertha dominica

Phthalides and their precursors have demonstrated a large variety of biological activities. Eighteen phthalides were synthesized and tested on the stored grain pest Rhyzopertha dominica. In the screening bioassay, compounds rac‐(2R,2aS,4R,4aS,6aR,6bS,7R)‐7‐bromohexahydro‐2,4‐methano‐1,6‐dioxacyclopenta[cd]pentalen‐5(2H)‐one (15) and rac‐(3R,3aR,4R,7S,7aS)‐3‐(propan‐2‐yloxy)hexahydro‐4,7‐methano‐2‐benzofuran‐1(3H)‐one (17) showed mortality similar to the commercial insecticide, Bifenthrin® (≥90 %). The time (LT50) and dose (LD50) necessary to kill 50 % of the R. dominica population were determined for the most efficacious phthalides 15 and 17. Compound 15 presented the lowest LD50 (1.97 μg g−1), being four times more toxic than Bifenthrin® (LD50=9.11 μg g−1). Both compounds presented an LT50 value equal to 24 h. When applied at a sublethal dose, both phthalides (especially compound 15), reduced the emergence of the first progeny of R. dominica. These findings highlight the potential of phthalides 15 and 17 as precursors for the development of insecticides for R. dominica control

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

Toxicity to Diaphania hyalinata, selectivity to non-target species and phytotoxicity of furanones and phthalide analogues

Despite being of great importance to crop protection, the disadvantages of intensive and inappropriate use of pesticides have stimulated the search for more selective and less harmful agrochemicals. Thus, we have evaluated the effectiveness of 16 synthetic molecules (phthalides and precursors) to control the melonworm Diaphania hyalinata, a key pest in cucurbit crops of economic importance in Brazil. The selectivity to beneficial organisms Solenopsis saevissima and Tetragonisca angustula and the phytotoxicity to Cucumis sativus of the promising insecticides were also assessed. In the screening assay, compounds 1 and 6 provided 91 and 88% mortality of the melonworm. Compound 1 presented higher toxicity (median lethal dose LD50 = 15.99 µmol g^−1) and higher speed on pest control (median survival time LT50 = 420 min) than compound 6 (LD50 = 44.51 µmol g^−1 and LT50 = 840 min). Both compounds inhibited less than 11% of host‐plant growth and caused ≤36 and ≥93% mortality of predator and pollinator respectively.Among the tested compounds, only compounds 1 and 6 were effective in melonworm control. Both compounds presented no considerable phytotoxicity and were selective to predator but non‐selective to pollinator, which enables their application for pest control if the exposure of the bees is minimised

Attenuation of Autism-like Behaviors by an Anthocyanin-Rich Extract from Portuguese Blueberries via Microbiota–Gut–Brain Axis Modulation in a Valproic Acid Mouse Model

Autism Spectrum Disorders (ASDs) are a group of neurodevelopmental pathologies whose current treatment is neither curative nor effective. Anthocyanins are naturally occurring compounds abundant in blueberries and in other red fruits which have been shown to be successful in the treatment of several neurological diseases, at least in in vitro and in vivo disease models. The aim of the present work was to study the ability of an anthocyanin-rich extract (ARE) obtained from Portuguese blueberries to alleviate autism-like symptoms in a valproic acid (VPA) mouse model of ASD and to get insights into the underlying molecular mechanisms of such benefits. Therefore, pregnant BALB/c females were treated subcutaneously with a single dose of VPA (500 mg/kg) or saline on gestational day 12.5. Male offspring mice were orally treated with the ARE from Portuguese blueberries (30 mg/kg/day) or the vehicle for three weeks, and further subjected to behavioral tests and biochemical analysis. Our data suggested that the ARE treatment alleviated autism-like behaviors in in utero VPA-exposed mice and, at the same time, decreased both neuroinflammation and gut inflammation, modulated the gut microbiota composition, increased serotonin levels in cerebral prefrontal cortex and gut, and reduced the synaptic dysfunction verified in autistic mice. Overall, our work suggests that anthocyanins extracted from Portuguese blueberries could constitute an effective strategy to ameliorate typical autistic behaviors through modulation of the microbiota–gut–brain axis

Chemical composition and decomposition rate of plants used as green manure Composição química e velocidade de decomposição de plantas visando a adubação verde

Productive systems in which green manure is the source of nutrients must develop more efficient ways to improve soil nutrient dynamics. A well-synchronized balance must be established between specific crop demands and supply of nutrients from decomposition. However, scientific data and information to help improve green manure management in Brazil is still insufficient. For that reason, a number of arboreal species was first chemically characterized and then subjected to decomposition analysis in order to establish a correlation between some parameters. Species were grouped together based on the similarity of chemical composition and decomposition rate. The lignin:N and (lignin+polyphenol):N ratios were found to have the greatest correlation coefficient with the dry matter decomposition rate and nitrogen release.<br>Sistemas produtivos que utilizam a adubação verde prezam por uma dinâmica mais eficiente de nutrientes no solo. Nesse sentido, é importante buscar a sincronia entre a demanda nutricional da cultura e a disponibilidade de nutrientes provenientes da decomposição. Esse estudo objetivou estabelecer uma correlação entre a composição química e a velocidade de decomposição de espécies em um sistema agroflorestal. Para tanto, realizou-se a caracterização química de espécies arbóreas, seguida de estudos de decomposição e busca de correlação entre os parâmetros analisados. De posse dos resultados, foi possível agrupar espécies com composição química e taxas de decomposição semelhantes. As relações lignina:N e (lignina+polifenol):N apresentaram os maiores coeficientes de correlação com a velocidade de decomposição de massa seca e liberação de nitrogênio