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

ADAM33 polymorphism: association with bronchial hyper-responsiveness in Korean asthmatics

Background A disintegrin and metalloprotease 33 (ADAM33) is expressed in the lung by fibroblasts and bronchial smooth muscle cells. Given its structure and cellular provenance, ADAM33 may be associated with airway remodelling and bronchial hyper-responsiveness. Single nucleotide polymorphisms (SNPs) and haplotypes of the ADAM33 gene have previously been associated with asthma susceptibility in the Caucasian population.Objective and Methods To assess whether genetic variants of ADAM33 are related to asthma in a Korean population, we conducted an association study of the ADAM33 gene with asthma susceptibility, bronchial hyper-reactivity and serum IgE in Korean asthmatics (n=326) and normal controls (n=151). Five of the 14 polymorphisms originally reported to be associated with asthma development (S1 G>A, T1 T>C, V-1 C>A, V1 T>A, V4 C>G) were genotyped using single base extension and electrophoresis. Haplotypes and their frequencies were inferred using the algorithm implemented by the software Arlequin. Allele frequencies of each SNP and haplotypes were compared between the patients and the normal controls using logistic regression analysis.Results There was no significant difference in the distribution of SNPs and the six haplotypes between asthmatics and normal controls. All single SNPs and six haplotypes in ADAM33 were also analysed for the association with level of PC20 using general linear models. The distribution of the T1 T>C SNP and one haplotype (ht4: GCGG) showed significant association with log-transformed PC20 methacholine level in the asthma patients (P=0.03 and 0.0007, respectively, using a co-dominant model).Conclusion Polymorphism of ADAM33 may contribute to development of BHR in asthma