NANOINCORPORAÇÃO DE AGENTES BIOATIVOS:: UMA ABORDAGEM MOLECULAR

Nas últimas décadas, com o avanço da tecnologia, muitas formas de se inserir um determinado medicamento no homem têm sido desenvolvidas e, com isso, contribuído com o avanço no que diz respeito ao tratamento e, às vezes, a cura de muitas doenças. A incorporação de partículas por nanoestruturas é um exemplo desses avanços, os quais têm sido utilizados em diferentes áreas, inclusive na saúde. Uma das técnicas utilizadas para a formação dessas nanoestruturas é a layer-by-layer (camada-sobre-camada), que consiste em deposições sucessivas de polieletrólitos com diferentes cargas. A pesquisa teve como objetivo realizar um estudo molecular sobre a incorporação de diferentes partículas, que foi feita através de uma revisão bibliográfica. De acordo com as informações obtidas, as substâncias utilizadas para a formação das nanoestruturas têm que apresentar cargas elétricas e com sinais opostos. A formação da nanocamadas podem ser confirmadas por diferentes testes como o ângulo de contato e as imagens de microscopia eletrônica de varredura (MEV). Diante o exposto, pode-se dizer que a incorporação de agentes bioativos por nanoestruturas é um processo que tem sido realizado como sucesso e confirmado com diferentes testes moleculares

ANÁLISE MOLECULAR DA ATIVIDADE ANTIMICROBIANA DA LISOZIMA

Nos últimos anos a procura por novas moléculas vem se intensificando por isso que várias áreas vêm recebendo grandes investimentos que apoiam pesquisas e formação de recursos humanos com capacidade de extrair os mais diferentes princípios ativos de diferentes espécies existentes na flora, na fauna ou em outra parte da biosfera. Alguns princípios ativos importantes são aqueles que estão relacionados com a prevenção de alguma doença através da inibição de algum agente patogênico. O trabalho teve como objetivo uma análise molecular da atividade antimicrobiana da lisozima através de uma revisão bibliográfica. Através de estudos realizados sobre o assunto, constatou-se que A estrutura primária da lisozima consiste numa única cadeia polipeptídica constituída por 129 aminoácidos. Ao longo da cadeia existem 4 pares de cisteínas (aminoácidos hidrofóbicos que contêm um grupo tiol: -SH) ligados por uma ponte dissulfídica (ligações covalentes que unem pontos distantes da estrutura primária da proteína, e que são comuns em proteínas extracelulares). Sua ação antimicrobiana se deve ao fato dela quebras as ligações entre o ácido N- acetilglucosamina (NAM) e N– acetilglucosamina de peptidoglicano (NAG). Sendo assim, a lisozima é uma enzima vulgarmente conhecida como o antibiótico natural, normalmente encontrado em secreções, como as lágrimas, a saliva e a mucosa nasal, bem como em grânulos citoplasmáticos de granulócitos neutrófilos e ainda na clara do ovo, atuando principalmente sobre bactérias gram-positivas. A sua estrutura molecular corresponde a uma estrutura primária que consiste numa única cadeia polipeptídica constituída por 129 aminoácidos com pares cisteinas

A influência da distribuição espacial na qualidade do fuste de Euxylophora paraensis (Huber) em floresta de terra firme manejada na Amazônia Oriental / The influence of spatial distribution on the stem quality of Euxylophora paraensis (Huber) in a managed upland forest in the Eastern Amazon

A manutenção da diversidade tanto de espécies como de habitats, é fundamental para o sucesso de empreendimentos florestais na Amazônia. O objetivo desse trabalho foi avaliar a influência da distribuição espacial na qualidade do fuste de Euxylhophora paraensis (Huber), em floresta de terra firme manejada na Amazônia Oriental. A área de estudo está localizada na Fazenda Rio Capim, pertencente a CKBV Florestal Ltda., no município de Paragominas estado Pará. Para a análise da influência da distribuição espacial na qualidade do fuste das árvores utilizou a geoestatística, a partir da modelagem de semivariograma e confecção de mapas de krigagem. De acordo com os dados observou-se que todas as avaliações tiveram melhor ajuste ao modelo esférico, que apresentou o maior coeficiente de determinação em relação aos outros modelos testados. A espécie florestal E. paraensis apresentou padrão de distribuição agregada, com alcance de 570 a 840 metros formando reboleiras de árvores na floresta estudada, indicando que maiores agregações favorecem maior qualidade do fuste esse delineamento ecológico deve ser avaliado nas tomadas de decisão sobre o manejo e sobrevivência da espécie

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

Antinociceptive and edematogenic activity and chemical constituents of Talinum paniculatum Willd.

Talinum paniculatum (Portulacaceae) is popularly known in the region of Patos de Minas, Minas Gerais State, Brazil, as “Maria Gorda” or “Benção-de-Deus” and in traditional medicine it is used to treat inflammatory processes in general. After dried and fragmented, the plant was sequentially submitted to exhaustive percolation with hexane, ethyl acetate and methanol. The crude extracts were investigated for their anti-edematogenic and anti-nociceptive activities through formalin-induced paw edema model. In comparison with a non-steroidal anti-inflammatory drug (NSAID) indomethacin, the hexane and ethyl acetate extracts showed higher anti-edematogenic and anti-nociceptive activity. In addition, through phytochemical studies, from these extracts were isolated and identified potassium nitrate (1), the mixture of long chain hiodrocarbons hentriacontane (2), dotriacontane (3), tritriacontane (4) and pentatriacontane (5). heneicosanoic acid (6), the ester nonacosyl nonacosanoate (7), urea (8), 3-O-b -Dglucosyl- b -sitosterol (9); the mixture of b -sitosterol (10) and stigmasterol (11), and a pentaciclyc triterpene 3-O-acethyl-aleuritolic acid (12). X-Ray difratometry was used for the characterization of inorganic constituent. TLC, HR-CG and spectrometric methods (IR. 1H and 13C NMR) were used to identify the structures of organic compounds. To the best of our knowledge, it is the first time that compound 1 to 8 and 12 are cited as constituents of T. paniculatum

Identification of Variants (rs11571707, rs144848, and rs11571769) in the <i>BRCA2</i> Gene Associated with Hereditary Breast Cancer in Indigenous Populations of the Brazilian Amazon

Estimates show that 5–10% of breast cancer cases are hereditary, caused by genetic variants in autosomal dominant genes; of these, 16% are due to germline mutations in the BRCA1 and BRCA2 genes. The comprehension of the mutation profile of these genes in the Brazilian population, particularly in Amazonian Amerindian groups, is scarce. We investigated fifteen polymorphisms in the BRCA1 and BRCA2 genes in Amazonian Amerindians and compared the results with the findings of global populations publicly available in the 1000 Genomes Project database. Our study shows that three variants (rs11571769, rs144848, and rs11571707) of the BRCA2 gene, commonly associated with hereditary breast cancer, had a significantly higher allele frequency in the Amazonian Amerindian individuals in comparison with the African, American, European, and Asian groups analyzed. These data outline the singular genetic profiles of the indigenous population from the Brazilian Amazon region. The knowledge about BRCA1 and BRCA2 variants is critical to establish public policies for hereditary breast cancer screening in Amerindian groups and populations admixed with them, such as the Brazilian population