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 research.Peer reviewe

Tell Me You're Sorry

Gift of Dr. Mary Jane Esplen.Piano vocals ukulele banjulele banjo [instrumentation]Just like other sweethearts often do [first line]tell me you're sorry, So [first line of chorus]E flat major [key]Moderato [tempo]Popular song [form/genre]Couple under flowered arch [illustration]Barbelle [graphic artist]Publisher's advertisement on back cover [note

A new cytotoxic diterpenoid glycoside from the leaves of <i>Blumea lacera</i> and its effects on apoptosis and cell cycle

<p>A new diterpenoid glycoside, 6<i>E</i>,10<i>E</i>,14<i>Z</i>-(3<i>S</i>)-17-hydroxygeranyllinalool-17-<i>O</i>-<i>β</i>-d-glucopyranosyl-(1 → 2)-[<i>α</i>-l-rhamnopyranosyl-(1 → 6)]-<i>β</i>-d-glucopyranoside (<b>1</b>) together with the known diterpenoid glycoside (<b>2</b>) and two known flavonoid glycosides (<b>3</b>, <b>4</b>) were isolated from the methanol extract of <i>Blumea lacera</i> leaves. The structures were determined by the interpretation of their spectroscopic data and comparison with the literature. All compounds were isolated for the first time from <i>B. lacera</i> and evaluated for their cytotoxic activity. Only the new compound (<b>1</b>) showed strong cytotoxic activity with the lowest IC₅₀ value (8.3 μM) being displayed against MCF-7 breast cancer cells. In apoptosis and cell cycle analysis, <b>1</b> revealed strong apoptotic activity against MCF-7 cells (45.5% AV⁺/PI⁻) after 24 h, but showed no arresting of any of the cell cycle phases in MCF-7.</p

New York Communities 2007: A Year of CaRDI Publications

CaRDI Reports Issue 4. Compilation of CaRDI Rural New York Minute and the Research & Policy Brief Series from 200