PERFIL ANTIBACTERIANO DE NOVOS DERIVADOS N-ACILIDRAZÔNICOS SUBSTITUÍDOS

As subunidades estruturais acilidrazona estão presentes em diversas substâncias com atividades biológicas bem relatadas. O presente estudo objetivou a avaliação in vitro do perfil antibacteriano de novos derivados N-acilidrazônicos substituídos, visando obter potenciais agentes terapêuticos mais eficazes, seguros e potentes. Os testes antibacterianos foram realizados através da técnica de microdiluição em caldo de acordo com o protocolo M7-A9 (NCCLS, 2012). As cepas testadas foram Staphylococcus aureus ATCC 25923 e Escherichia coli ATC 25922. Constatou-se que o composto AMAC01 foi o que apresentou melhor atividade frente às duas cepas testadas, o que pode ser explicado pela presença do núcleo acridínico sem substituintes. Para a série JR os compostos nitrados substituidos nas posições orto-para foram os que apresentaram melhor atividade para ambas as cepas. Baseado nos resultados se constatou que os compostos acridínicos e o grupamento nitro podem ser trabalhados posteriormente aplicando-se técnicas de modificação molecular a fim de obter um Hit promissor

DESENVOLVIMENTO ATRAVÉS DA SÍNTESE, ELUCIDAÇÃO ESTRUTURAL E AVALIAÇÃO BIOLÓGICA DE DERIVADOS 2-AMINO-TIOFÊNICOS-SUBSTITUÍDOS COMO POTENCIAIS FÁRMACOS ANTIFÚNGICOS

A resistência fúngica a agentes terapêuticos disponíveis no mercado tem aumentando significativamente, principalmente devido ao crescimento da população imunocomprometida e do uso indiscriminado de agentes Antifúngicos. O presente trabalho teve por objetivo realizar o desenvolvimento de entidades químicas sintéticas derivados do heterocíclico tiofeno associado a diferentes aldeídos substituídos diclorados, que possam ser utilizadas como potenciais agentes antifúngicos mais seguros, eficazes, potentes e menos tóxicos. O método utilizado para a obtenção dos núcleos partiu da reação de Gewald, já descrita na literatura, onde os núcleos são obtidos inicialmente depois condensados com aldeídos aromáticos em meio acido e etanólico. Os compostos tiveram suas estruturas comprovadas através de RMN1H e apresentaram rendimentos entre 55 e 83%. Os compostos serão avaliados frete a diferentes cepas fúgicas ATCC, e aqueles que se apresentarem mais ativos, serão avaliados frente a isolados clínicos

AÇÃO MODULADORA DE EXTRATOS ETANÓLICOS DE PLANTAS MEDICINAIS SOBRE ANTIBIÓTICOS EM CEPA DE Staphylococcus aureus METICILINA-RESISTENTE

É crescente o aumento de casos de micro-organismos resistentes a múltiplos fármacos, principalmente bactérias, o que tem sensibilizado pesquisadores do mundo inteiro a buscar nas plantas, recursos que possam mitigar as consequências causadas por estes micro-organismos. Uma das estratégias atuais tem sido associar plantas com antimicrobianos já licenciados e utilizados na terapêutica, na tentativa de encontrar ações sinérgicas que possam driblar os mecanismos de resistência bacteriana. O presente trabalho buscou avaliar o efeito modulador de plantas medicinais sobre a atividade de dois antibióticos betalactâmicos, ampicilina e cefriaxona, e um aminoglicosídeo, a gentamicina; através da técnica da microdiluição em placas, utilizando-se uma cepa de Staphylococcus aureus meticilina-resistente - MRSA. Os resultados apontam para um provável sinergismo entre Schinus terebinthifolius e Punica granatum com o aminoglicosídeo gentamicina, o que oferece novas oportunidades para futuros estudos em busca do composto ativo destas plantas e assim melhorar a atividade e eficácia de tratamentos terapêuticos envolvendo os aminoglicosídeos em infecções causadas por micro-organismos multirresistentes

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

ACW-02 an Acridine Triazolidine Derivative Presents Antileishmanial Activity Mediated by DNA Interaction and Immunomodulation

The present study proposed the synthesis of a novel acridine derivative not yet described in the literature, chemical characterization by NMR, MS, and IR, followed by investigations of its antileishmanial potential. In vitro assays were performed to assess its antileishmanial activity against L. amazonensis strains and cytotoxicity against macrophages through MTT assay and annexin V-FITC/PI, and the ability to perform an immunomodulatory action using CBA. To investigate possible molecular targets, its interaction with DNA in vitro and in silico targets were evaluated. As results, the compound showed good antileishmanial activity, with IC50 of 6.57 (amastigotes) and 94.97 (promastigotes) µg mL−1, associated with non-cytotoxicity to macrophages (CC50 > 256.00 µg mL−1). When assessed by flow cytometry, 99.8% of macrophages remained viable. The compound induced an antileishmanial effect in infected macrophages and altered TNF-α, IL-10 and IL-6 expression, suggesting a slight immunomodulatory activity. DNA assay showed an interaction with the minor grooves due to the hyperchromic effect of 47.53% and Kb 1.17 × 106 M−1, and was sustained by docking studies. Molecular dynamics simulations and MM-PBSA calculations propose cysteine protease B as a possible target. Therefore, this study demonstrates that the new compound is a promising molecule and contributes as a model for future works