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用于发现式浏览的语义医学文献数据库:利用语义断言和基于文献的发现范式阐明肥胖悖论的机制

Semantic MEDLINE for discovery browsing: using semantic predications and the literature-based discovery paradigm to elucidate a mechanism for the obesity paradox.

作者信息

Cairelli Michael J, Miller Christopher M, Fiszman Marcelo, Workman T Elizabeth, Rindflesch Thomas C

机构信息

National Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.

出版信息

AMIA Annu Symp Proc. 2013 Nov 16;2013:164-73. eCollection 2013.

Abstract

Applying the principles of literature-based discovery (LBD), we elucidate the paradox that obesity is beneficial in critical care despite contributing to disease generally. Our approach enhances a previous extension to LBD, called "discovery browsing," and is implemented using Semantic MEDLINE, which summarizes the results of a PubMed search into an interactive graph of semantic predications. The methodology allows a user to construct argumentation underpinning an answer to a biomedical question by engaging the user in an iterative process between system output and user knowledge. Components of the Semantic MEDLINE output graph identified as "interesting" by the user both contribute to subsequent searches and are constructed into a logical chain of relationships constituting an explanatory network in answer to the initial question. Based on this methodology we suggest that phthalates leached from plastic in critical care interventions activate PPAR gamma, which is anti-inflammatory and abundant in obese patients.

摘要

应用基于文献的发现(LBD)原理,我们阐释了一个悖论:尽管肥胖通常会引发疾病,但在重症监护中它却有益。我们的方法改进了之前对LBD的扩展,即“发现浏览”,并使用语义医学文献数据库(Semantic MEDLINE)来实施,该数据库将PubMed搜索结果总结为一个语义断言的交互式图。这种方法允许用户通过在系统输出和用户知识之间进行迭代过程,构建支持生物医学问题答案的论证。被用户识别为“有趣”的语义医学文献数据库输出图的组件,既有助于后续搜索,又被构建成一个逻辑关系链,形成一个解释性网络来回答最初的问题。基于这种方法,我们认为重症监护干预中从塑料中浸出的邻苯二甲酸盐会激活PPARγ,PPARγ具有抗炎作用且在肥胖患者中含量丰富。

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