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

Targeted epigenetic silencing of UCHL1 expression suppresses collagen-1 production in human lung epithelial cells

Ubiquitin carboxyl-terminal hydrolase L1 (UCHL1) is highly expressed in smokers, but little is known about the molecular mechanism of UCHL1 in airway epithelium and its possible role in affecting extracellular matrix (ECM) remodelling in the underlying submucosa. Since cigarette smoking is a major cause of lung diseases, we studied its effect on UCHL1 expression and DNA methylation patterns in human bronchial epithelial cells, obtained after laser capture micro-dissection (LCM) or isolated from residual tracheal/main stem bronchial tissue. Targeted regulation of UCHL1 expression via CRISPR/dCas9 based-epigenetic editing was used to explore the function of UCHL1 in lung epithelium. Our results show that cigarette smoke extract (CSE) stimulated the expression of UCHL1 in vitro. The methylation status of the UCHL1 gene was negatively associated with UCHL1 transcription in LCM-obtained airway epithelium at specific sites. Treatment with a UCHL1 inhibitor showed that the TGF-β1-induced upregulation of the ECM gene COL1A1 can be prevented by the inhibition of UCHL1 activity in cell lines. Furthermore, upon downregulation of UCHL1 by epigenetic editing using CRISPR/dCas-EZH2, mRNA expression of COL1A1 and fibronectin was reduced. In conclusion, we confirmed higher UCHL1 expression in current smokers compared to non- and ex-smokers, and induced downregulation of UCHL1 by epigenetic editing. The subsequent repression of genes encoding ECM proteins suggest a role for UCHL1 as a therapeutic target in fibrosis-related disease