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

Fate of nanoplastics in the environment: Implication of the cigarette butts

International audienceFate, transport and accumulation of nanoplastics have attracted considerable attention in the past few years. While actual researches have been focused on nanoplastics dispersed or aggregated in different environmental system, no study have been focused on the possibility that nanoplastics are co-transported with other natural or anthropogenic materials. Therefore, the large quantity of debris released in the environment, such as cigarette butts (CGB), could be part of the nanoplastics fate and behavior. Here we show the considerable sorption capacities of cigarette filters for nanoplastics. To address this topic, we chose polystyrene-based nanoplastics with similar state of charge (according to the physico-chemical characteristic of the zeta potential −45 to −40 mV) but with different sizes (50–800 nm) and morphologies. A kinetic approach to sorption in fresh water (pH = 8.05; 179.5 μS cm−1) at room temperature was carried out by means of the flow field flow analysis method (AF4) to determine the partition coefficients and water sampling rates between nanoplastics and cigarette butts. Using different models of, more or less environmentally relevant, nanoplastics (NPTs) and adequate analytical strategies, we found partition coefficients between the NPTs and CGBs ranged from 102 to 104 in freshwater conditions. We demonstrated that the physical features of the NPTs (size and morphology) have an influence on the sorption behaviour. Asymmetrical shaped NPTs with broader size distribution seems to be mostly retained in the CGBs after longer equilibration time. This result shows the importance of the NPTs features on the mechanisms governing their transfer and fate in the environment through environmental matrices, especially when other materials are involved. We anticipate our work to be a starting point for investigating the co-transport of NPTs with other materials present in the environment (natural and anthropogenic)

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