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

Heme Oxygenase-1 Regulation of Matrix Metalloproteinase-1 Expression Underlies Distinct Disease Profiles in Tuberculosis

Andrade, Bruno de Bezerril; Bessa, Theolis Costa Barbosa. Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Unidade de Medicina Investigativa. Laboratório Integrado de Microbiologia e Imunorregulação. Salvador, BA, Brasil *Immunobiology Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; †Unidade de Medicina Investigativa, Laborato´rio Integrado de Microbiologia e Imunorregulação, Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador 40296-710, Brazil; ‡National Institutes of Health, International Center for Excellence in Research, Chennai 600031, India; xNational Institute for Research in Tuberculosis, Chennai 600031, India; {Microbial Pathogenesis Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; ‖Department of Medicine, Imperial College London, London SW7 2AZ, United Kingdom; #Government Stanley Medical Hospital, Chennai 600001, India; **Cardiovascular and Pulmonary Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892; ††Immunopathogenesis Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; ‡‡Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD 20892; xxClinical and Molecular Retrovirology Section, Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; {{T-Lymphocyte Biology Unit, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892; ‖‖Helminth Immunology Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2017-07-21T17:34:59Z No. of bitstreams: 1 Andrade BB Heme oxygenase-1 regulation....pdf: 3477535 bytes, checksum: 060069be6b5ca6497c330534a63ac8a0 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2017-07-21T17:57:14Z (GMT) No. of bitstreams: 1 Andrade BB Heme oxygenase-1 regulation....pdf: 3477535 bytes, checksum: 060069be6b5ca6497c330534a63ac8a0 (MD5)Made available in DSpace on 2017-07-21T17:57:14Z (GMT). No. of bitstreams: 1 Andrade BB Heme oxygenase-1 regulation....pdf: 3477535 bytes, checksum: 060069be6b5ca6497c330534a63ac8a0 (MD5) Previous issue date: 2015Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health. J.M., V.C.M., and J.R.F. were supported by the National Heart, Lung, and Blood Institute Intramural Research Program. The Brazilian study was funded by Fundação de Amparo à Pesquisa do Estado da Bahia and Conselho Nacional de Desenvolvimento Cientı´fico e Tecnológico, Brazil (Grant 028/2010).Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Unidade de Medicina Investigativa. Laboratório Integrado de Microbiologia e Imunorregulação. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Unidade de Medicina Investigativa. Laboratório Integrado de Microbiologia e Imunorregulação. Salvador, BA, BrasilMúltipla – ver em NotasPulmonary tuberculosis (TB) is characterized by oxidative stress and lung tissue destruction by matrix metalloproteinases (MMPs). The interplay between these distinct pathological processes and the implications for TB diagnosis and disease staging are poorly understood. Heme oxygenase-1 (HO-1) levels were previously shown to distinguish active from latent TB, as well as successfully treated Mycobacterium tuberculosis infection. MMP-1 expression is also associated with active TB. In this study, we measured plasma levels of these two important biomarkers in distinct TB cohorts from India and Brazil. Patients with active TB expressed either very high levels of HO-1 and low levels of MMP-1 or the converse. Moreover, TB patients with either high HO-1 or MMP-1 levels displayed distinct clinical presentations, as well as plasma inflammatory marker profiles. In contrast, in an exploratory North American study, inversely correlated expression of HO-1 and MMP-1 was not observed in patients with other nontuberculous lung diseases. To assess possible regulatory interactions in the biosynthesis of these two enzymes at the cellular level, we studied the expression of HO-1 and MMP-1 in M. tuberculosis-infected human and murine macrophages. We found that infection of macrophages with live virulent M. tuberculosis is required for robust induction of high levels of HO-1 but not MMP-1. In addition, we observed that CO, a product of M. tuberculosis-induced HO-1 activity, inhibits MMP-1 expression by suppressing c-Jun/AP-1 activation. These findings reveal a mechanistic link between oxidative stress and tissue remodeling that may find applicability in the clinical staging of TB patients

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