Achieving global biodiversity goals by 2050 requires urgent and integrated actions

Governments are negotiating actions intended to halt biodiversity loss and put it on a path to recovery by 2050. Here, we show that bending the curve for biodiversity is possible, but only if actions are implemented urgently and in an integrated manner. Connecting these actions to biodiversity outcomes and tracking progress remain a challenge

CXCR2 Inhibition – a novel approach to treating CoronAry heart DiseAse (CICADA): study protocol for a randomised controlled trial

Abstract Background There is emerging evidence of the central role of neutrophils in both atherosclerotic plaque formation and rupture. Patients with lower neutrophil counts following acute coronary syndromes tend to have a greater coronary flow reserve, which is a strong predictor of long-term cardiovascular health. But so far, no data are available regarding the impact of neutrophil inhibition on cardiovascular clinical or surrogate endpoints. Therefore, the aim of this study is to investigate the effects of AZD5069, a cysteine-X-cysteine chemokine receptor 2 (CXCR2) inhibitor, on coronary flow reserve and coronary structure and function in patients with coronary artery disease. Methods/Design Ninety subjects with coronary artery disease undergoing percutaneous coronary intervention will be included in this investigator-driven, randomised, placebo-controlled, double-blind, phase IIa, single-centre study. Participants will be randomised to receive either AZD5069 (40 mg) administered orally twice daily or placebo for 24 weeks. Change in coronary flow reserve as determined by 13N-ammonia positron emission tomography-computed tomography will be the primary outcome. Change in the inflammatory component of coronary plaque structure and the backward expansion wave, an invasive coronary physiological measure of diastolic function, will be assessed as secondary outcomes. Discussion Cardiovascular surrogate parameters, such as coronary flow reserve, may provide insights into the potential mechanisms of the cardiovascular effects of CXCR2 inhibitors. Currently, ongoing trials do not specifically focus on neutrophil function as a target of intervention, and we therefore believe that our study will contribute to a better understanding of the role of neutrophil-mediated inflammation in coronary artery disease. Trial registration EudraCT, 2016-000775-24 . Registered on 22 July 2016. International Standard Randomised Controlled Trial Number, ISRCTN48328178 . Registered on 25 February 2016

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

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