Caracterização química e atividade antibacteriana de óleos essenciais de plantas condimentares e medicinais contra Staphylococcus aureus e Escherichia coli

Os óleos essenciais são metabólitos secundários dos vegetais com propriedades biológicas diferenciadas, dentre elas, a atividade contra microrganismos, sendo de interesse da indústria de alimentos as concentrações mínimas inibitórias (CMI) desses óleos para diversas bactérias. As CMI variam em função dos compostos majoritários e da espécie de bactéria. Nesta pesquisa, os óleos essenciais das plantas Satureja montana L., Cymbopogon nardus L. e Citrus limonia Osbeck foram caracterizados quimicamente e se determinou a CMI sobre as bactérias Staphylococcus aureus ATCC 2592 e Escherichia coli ATCC 25922. A CMI dos óleos testados contra E. coli e S. aureus foi de 1,5%, exceto para o óleo essencial de S. montana sobre S. aureus, a qual foi sensível a este óleo a partir da concentração de 5,0%. Sobre a constituição química, os componentes majoritários dos óleos de S. montana, C. narduse C. limonia Osbeck foram respectivamente o timol, citronelal e limoneno

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press