61 research outputs found
Schinopsis brasiliensis engl. to combat the biofilm-dependents diseases in vitro
Dental caries and periodontal disease are the most prevalent of the biofilm-dependent diseases. With numerous side effects on the use of chlorhexidine, the search for new safe therapeutic alternatives for microorganisms involved with these diseases increases every day. This study aimed to evaluate the antimicrobial activity and cytotoxicity of extracts made from the bark of Schinopsis brasiliensis Engl. against five oral microorganisms and analyze their phytochemical and thermal degradation profile. The liquid-liquid partition was performed with hexane, chloroform and ethyl acetate. The identification and quantification of the chemical marker was done. Antimicrobial activity was evaluated based on the minimum inhibitory concentration. The cytotoxicity was analyzed based on the hemolysing potential of the samples. The thermal degradation profile was performed by two different methods. Gallic acid was identified as the main compound of the samples and showed the highest amount in the chloroform fraction. All samples were able to inhibit the growth of the microorganisms tested and showed no cytotoxicity. The ethanol extract absorbs less heat than the fractions. All samples exhibited exothermic peak consistent with degradation of gallic acid. Based on the results, the samples used are potential candidates for use in dental formulations for biofilm control924CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQSem informaçã
Seasonal variation in the production of secondary metabolites and antimicrobial activity of two plant species used in Brazilian traditional medicine
Guapira graciliflora and Pseudobombax marginatum are two species used in the treatment of various diseases in traditional medicine of the Brazilian semiarid region, but no studies assessing their phytochemical and pharmacological properties have been reported. This study aimed to evaluate seasonal variation in the production of secondary metabolites and antimicrobial activity of these plants. The broth microdilution test was used against pathogenic microorganisms to evaluate the antimicrobial activity. The content of total polyphenols and flavonoids was determined by ultra violet (UV) spectrophotometry using gallic acid and quercetin as standards respectively. The concentration of polyphenols was higher in winter for P. marginatum and in summer for G. graciliflora, while for flavonoids the opposite occurred. Regarding the antimicrobial activity, only P. marginatum showed inhibition against seven tested strains and antibiosis against four, with variation in the minimum inhibitory concentration (MIC) and minimum microbicide concentration (MMC) between the two seasons. G. graciliflora showed no activity. The results show that the chemical composition of the extracts from P. marginatum and G. gracilliflora exhibits seasonal variation, with the first plant showing moderate antimicrobial activity.Keywords: Seasonal variation, phenolic compounds, medicinal plants, Gapira graciliflora, Pseudobombax marginatumAfrican Journal of Biotechnology Vol. 12(8), pp. 847-85
Study Bioprospecting of Medicinal Plant Extracts of the Semiarid Northeast: Contribution to the Control of Oral Microorganisms
Dental pathologies can be caused by plaque-forming bacteria and yeast, which reside in the oral cavity. The bacteria growing in dental plaque, a naturally occurring biofilm, display increased resistance to antimicrobial agents. The objective was the evaluation of a preclinical assay of medicinal plants of the semiarid region from the northeast against oral pathogenic microorganism, aiming at bioprospecting a new product. The selection of plant material for this study was based on the ethnobotanical data on the traditional use of plants from the semiarid region. The thirty extracts were subjected to the determination of antibiofilm activity against gram-positive, gram-negative bacteria and yeast. The hydroalcoholic extract which showed positive antibiofilm activity against most of the microorganisms tested in agar diffusion assay was further tested for the determination of minimum inhibitory concentration (MIC) and Bioassay with Artemia salina. Plant samples tested in this study exhibited good antibiofilm activity for the treatment of oral problems. The Schinopsis brasiliensis showed greater activity for Pseudomonas aeruginosa and Staphylococcus aureus, but toxicity against Artemia salina
Richness and abundance of the cardini group of Drosophila (Diptera, Drosophilidae) in the Caatinga and Atlantic Forest biomes in northeastern Brazil
Densidade de um planossolo sob sistemas de cultivo avaliada por meio da tomografia computadorizada de raios gama
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
Consistent patterns of common species across tropical tree communities
Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe
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
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