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

Electrokinetic salt removal from porous building materials using ion exchange membranes

The removal of salt from porous building materials under the influence of an applied voltage gradient normally results in high pH gradients due to the formation of protons and hydroxyl ions at the electrodes. The formed acidic and alkaline regions not only lead to disintegration of the porous material, but also affect the salt transport. In this work we use ion exchange membranes between the electrodes and the porous material to prevent the protons and hydroxyl ions from intruding into the material. The porous material used in this study is fired clay brick, which has been saturated with a 4 mol/l sodium chloride solution prior to the desalination treatment. In order to experimentally determine the salt removal, we monitored the sodium ion concentration profiles across the material with nuclear magnetic resonance (NMR). In addition, we present theoretical predictions for the salt removal according to a model based on the Poisson–Nernst–Planck theory for ion transport. From the work reported here, we can conclude that the use of ion exchange membranes to desalinate porous building materials is not useful since it reduces the salt removal rate to such an extent that desalination with poultices, which is driven by diffusion only, is more efficient. The reason behind this is twofold. First, the ion exchange membranes provide a penalty for the ions to leave the material. Second, in the absence of acidic and alkaline regions, the salt concentration at the edges of the porous material will reduce to almost zero, which leads to a locally increased electrical resistance, and thus a reduction of the electrical field in the bulk of the material. Due to this reduction the effect of the applied voltage gradient across the material vanishes, and the salt removal is limited by diffusion.Materials Innovation InstituteMechanical, Maritime and Materials Engineerin

Once-per-week selinexor, bortezomib, and dexamethasone versus twice-per-week bortezomib and dexamethasone in patients with multiple myeloma (BOSTON): a randomised, open-label, phase 3 trial

Background: Selinexor combined with dexamethasone has shown activity in patients with heavily pre-treated multiple myeloma. In a phase 1b/2 study, the combination of oral selinexor with bortezomib (a proteasome inhibitor) and dexamethasone induced high response rates with low rates of peripheral neuropathy, the main dose-limiting toxicity of bortezomib. We aimed to evaluate the clinical benefit of weekly selinexor, bortezomib, and dexamethasone versus standard bortezomib and dexamethasone in patients with previously treated multiple myeloma. Methods: This phase 3, randomised, open-label trial was done at 123 sites in 21 countries. Patients aged 18 years or older, who had multiple myeloma, and who had previously been treated with one to three lines of therapy, including proteasome inhibitors, were randomly allocated (1:1) to receive selinexor (100 mg once per week), bortezomib (1·3 mg/m2 once per week), and dexamethasone (20 mg twice per week), or bortezomib (1·3 mg/m2 twice per week for the first 24 weeks and once per week thereafter) and dexamethasone (20 mg four times per week for the first 24 weeks and twice per week thereafter). Randomisation was done using interactive response technology and stratified by previous proteasome inhibitor therapy, lines of treatment, and multiple myeloma stage. The primary endpoint was progression-free survival in the intention-to-treat population. Patients who received at least one dose of study treatment were included in the safety population. This trial is registered at ClinicalTrials.gov, NCT03110562. The trial is ongoing, with 55 patients remaining on randomised therapy as of Feb 20, 2020. Findings: Of 457 patients screened for eligibility, 402 were randomly allocated—195 (49%) to the selinexor, bortezomib, and dexamethasone group and 207 (51%) to the bortezomib and dexamethasone group—and the first dose of study medication was given between June 6, 2017, and Feb 5, 2019. Median follow-up durations were 13·2 months [IQR 6·2–19·8] for the selinexor, bortezomib, and dexamethasone group and 16·5 months [9·4–19·8] for the bortezomib and dexamethasone group. Median progression-free survival was 13·93 months (95% CI 11·73–not evaluable) with selinexor, bortezomib, and dexamethasone and 9·46 months (8·11–10·78) with bortezomib and dexamethasone (hazard ratio 0·70 [95% CI 0·53–0·93], p=0·0075). The most frequent grade 3–4 adverse events were thrombocytopenia (77 [39%] of 195 patients in the selinexor, bortezomib, and dexamethasone group vs 35 [17%] of 204 in the bortezomib and dexamethasone group), fatigue (26 [13%] vs two [1%]), anaemia (31 [16%] vs 20 [10%]), and pneumonia (22 [11%] vs 22 [11%]). Peripheral neuropathy of grade 2 or above was less frequent with selinexor, bortezomib, and dexamethasone (41 [21%] patients) than with bortezomib and dexamethasone (70 [34%] patients; odds ratio 0·50 [95% CI 0·32–0·79], p=0·0013). 47 (24%) patients in the selinexor, bortezomib, and dexamethasone group and 62 (30%) in the bortezomib and dexamethasone group died. Interpretation: A once-per-week regimen of selinexor, bortezomib, and dexamethasone is a novel, effective, and convenient treatment option for patients with multiple myeloma who have received one to three previous lines of therapy. Funding: Karyopharm Therapeutics. © 2020 Elsevier Lt

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