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

ZIKV-specific NS1 epitopes as serological markers of acute zika virus infection

Differentiate ZIKV from other cocirculating flaviviruses for accurate diagnosis remains a challenge. We investigated antibody responses in 51 acute ZIKV-infected adult patients from Campinas, Brazil, including 7 pregnant women who later delivered during the study. Using enzyme-linked immunosorbent assays, levels of antibody response were measured and specific epitopes identified. Several antibody-binding hot spots were identified in ZIKV immunogenic antigens, including membrane, envelope (E) and nonstructural protein 1 (NS1). Interestingly, specific epitopes (2 from E and 2 from NS1) strongly recognized by ZIKV-infected patients' antibodies were identified and were not cross-recognized by dengue virus (DENV)-infected patients' antibodies. Corresponding DENV peptides were not strongly recognized by ZIKV-infected patients' antibodies. Notably, ZIKV-infected pregnant women had specific epitope recognition for ZIKV NS1 (amino acid residues 17-34), which could be a potential serological marker for early ZIKV detection.This study identified 6 linear ZIKV-specific epitopes for early detection of ZIKV infections. We observed differential epitope recognition between ZIKV-infected and DENV-infected patients. This information will be useful for developing diagnostic methods that differentiate between closely related flaviviruses2202203212CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPnão tem2016/00194-8; 2013/25807-4This work is supported by the Biomedical Research Council (BMRC) core research grants to the Singapore Immunology Network and the Zika Virus Consortium Fund, led by BMRC A*Star (project number 15/1/82/27/001); Agency for Science, Technology and Research, Singapore; Fundação de Amparo à Pesquisa do Estado de São Paulo (grant numbers 2016/00194-8 and 2013/25807-4 fellowship to J. A. L.); and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (research fellowships to G. P. M. and F. T. M. C.