164 research outputs found

    Mining document, concept, and term associations for effective biomedical retrieval - Introducing MeSH-enhanced retrieval models

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    Manually assigned subject terms, such as Medical Subject Headings (MeSH) in the health domain, describe the concepts or topics of a document. Existing information retrieval models do not take full advantage of such information. In this paper, we propose two MeSH-enhanced (ME) retrieval models that integrate the concept layer (i.e. MeSH) into the language modeling framework to improve retrieval performance. The new models quantify associations between documents and their assigned concepts to construct conceptual representations for the documents, and mine associations between concepts and terms to construct generative concept models. The two ME models reconstruct two essential estimation processes of the relevance model (Lavrenko and Croft 2001) by incorporating the document-concept and the concept-term associations. More specifically, in Model 1, language models of the pseudo-feedback documents are enriched by their assigned concepts. In Model 2, concepts that are related to users’ queries are first identified, and then used to reweight the pseudo-feedback documents according to the document-concept associations. Experiments carried out on two standard test collections show that the ME models outperformed the query likelihood model, the relevance model (RM3), and an earlier ME model. A detailed case analysis provides insight into how and why the new models improve/worsen retrieval performance. Implications and limitations of the study are discussed. This study provides new ways to formally incorporate semantic annotations, such as subject terms, into retrieval models. The findings of this study suggest that integrating the concept layer into retrieval models can further improve the performance over the current state-of-the-art models.Ye

    Clinical narrative analytics challenges

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    Precision medicine or evidence based medicine is based on the extraction of knowledge from medical records to provide individuals with the appropriate treatment in the appropriate moment according to the patient features. Despite the efforts of using clinical narratives for clinical decision support, many challenges have to be faced still today such as multilinguarity, diversity of terms and formats in different services, acronyms, negation, to name but a few. The same problems exist when one wants to analyze narratives in literature whose analysis would provide physicians and researchers with highlights. In this talk we will analyze challenges, solutions and open problems and will analyze several frameworks and tools that are able to perform NLP over free text to extract medical entities by means of Named Entity Recognition process. We will also analyze a framework we have developed to extract and validate medical terms. In particular we present two uses cases: (i) medical entities extraction of a set of infectious diseases description texts provided by MedlinePlus and (ii) scales of stroke identification in clinical narratives written in Spanish

    Vomiting and wasting disease associated with hemagglutinating encephalomyelitis viruses infection in piglets in jilin, china

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    One coronavirus strain was isolated from brain tissues of ten piglets with evident clinical manifestations of vomiting, diarrhea and dyskinesia in Jilin province in China. Antigenic and genomic characterizations of the virus (isolate PHEV-JLsp09) were based on multiplex PCR and negative staining electron microscopy and sequence analysis of the Hemagglutinin-esterase (HE) gene. These piglets were diagnosed with Porcine hemagglutinating encephalomyelitis virus (PHEV)

    Feature engineering and a proposed decision-support system for systematic reviewers of medical evidence

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    Objectives: Evidence-based medicine depends on the timely synthesis of research findings. An important source of synthesized evidence resides in systematic reviews. However, a bottleneck in review production involves dual screening of citations with titles and abstracts to find eligible studies. For this research, we tested the effect of various kinds of textual information (features) on performance of a machine learning classifier. Based on our findings, we propose an automated system to reduce screeing burden, as well as offer quality assurance. Methods: We built a database of citations from 5 systematic reviews that varied with respect to domain, topic, and sponsor. Consensus judgments regarding eligibility were inferred from published reports. We extracted 5 feature sets from citations: alphabetic, alphanumeric +, indexing, features mapped to concepts in systematic reviews, and topic models. To simulate a two-person team, we divided the data into random halves. We optimized the parameters of a Bayesian classifier, then trained and tested models on alternate data halves. Overall, we conducted 50 independent tests. Results: All tests of summary performance (mean F3) surpassed the corresponding baseline, P<0.0001. The ranks for mean F3, precision, and classification error were statistically different across feature sets averaged over reviews; P-values for Friedman's test were .045, .002, and .002, respectively. Differences in ranks for mean recall were not statistically significant. Alphanumeric+ features were associated with best performance; mean reduction in screening burden for this feature type ranged from 88% to 98% for the second pass through citations and from 38% to 48% overall. Conclusions: A computer-assisted, decision support system based on our methods could substantially reduce the burden of screening citations for systematic review teams and solo reviewers. Additionally, such a system could deliver quality assurance both by confirming concordant decisions and by naming studies associated with discordant decisions for further consideration. © 2014 Bekhuis et al

    Aqueous extracts from dietary supplements influence the production of inflammatory cytokines in immortalized and primary T lymphocytes

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    <p>Abstract</p> <p>Background</p> <p>Congaplex<sup>® </sup>and Immuplex<sup>® </sup>are dietary supplements that have been traditionally used to support immune system function. The purpose of these experiments was to determine whether Congaplex<sup>® </sup>and Immuplex<sup>® </sup>affect immune function using primary and immortalized T lymphocytes.</p> <p>Methods</p> <p>Immortalized CEM and Jurkat T lymphocytes and primary peripheral mononuclear blood cells (PBMCs) were treated with the aqueous extracts from Congaplex<sup>® </sup>and Immuplex<sup>® </sup>to determine the effects of these products on cytokine production in activated T lymphocytes.</p> <p>Results</p> <p>Congaplex<sup>® </sup>enhanced phytohemagglutinin/phorbol 12-myristate 13-acetate (PHA/PMA) stimulation of both CEM and Jurkat cells as measured by the production of cytokines, while Immuplex<sup>® </sup>suppressed PHA/PMA-induced production of cytokines, with the exception of interleukin (IL)-8 which was enhanced by Immuplex<sup>®</sup>. <it>In vitro </it>treatment of PBMCs from 10 healthy donors with Congaplex<sup>® </sup>or Immuplex<sup>® </sup>decreased PHA-stimulated production of interferon (IFN)-γ but increased the production of IL-13.</p> <p>Conclusions</p> <p>While the effects of Congaplex<sup>® </sup>and Immuplex<sup>® </sup>differed in these two models, these data demonstrate that the aqueous extracts from these two dietary supplements can affect the inflammatory response of T lymphocytes.</p

    A Novel and Critical Role for Oct4 as a Regulator of the Maternal-Embryonic Transition

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    Compared to the emerging embryonic stem cell (ESC) gene network, little is known about the dynamic gene network that directs reprogramming in the early embryo. We hypothesized that Oct4, an ESC pluripotency regulator that is also highly expressed at the 1- to 2-cell stages in embryos, may be a critical regulator of the earliest gene network in the embryo.Using antisense morpholino oligonucleotide (MO)-mediated gene knockdown, we show that Oct4 is required for development prior to the blastocyst stage. Specifically, Oct4 has a novel and critical role in regulating genes that encode transcriptional and post-transcriptional regulators as early as the 2-cell stage. Our data suggest that the key function of Oct4 may be to switch the developmental program from one that is predominantly regulated by post-transcriptional control to one that depends on the transcriptional network. Further, we propose to rank candidate genes quantitatively based on the inter-embryo variation in their differential expression in response to Oct4 knockdown. Of over 30 genes analyzed according to this proposed paradigm, Rest and Mta2, both of which have established pluripotency functions in ESCs, were found to be the most tightly regulated by Oct4 at the 2-cell stage.We show that the Oct4-regulated gene set at the 1- to 2-cell stages of early embryo development is large and distinct from its established network in ESCs. Further, our experimental approach can be applied to dissect the gene regulatory network of Oct4 and other pluripotency regulators to deconstruct the dynamic developmental program in the early embryo

    Angiogenesis gene expression in murine endothelial cells during post-pneumonectomy lung growth

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    Although blood vessel growth occurs readily in the systemic bronchial circulation, angiogenesis in the pulmonary circulation is rare. Compensatory lung growth after pneumonectomy is an experimental model with presumed alveolar capillary angiogenesis. To investigate the genes participating in murine neoalveolarization, we studied the expression of angiogenesis genes in lung endothelial cells. After left pneumonectomy, the remaining right lung was examined on days 3, 6, 14 and 21days after surgery and compared to both no surgery and sham thoracotomy controls. The lungs were enzymatically digested and CD31+ endothelial cells were isolated using flow cytometry cell sorting. The transcriptional profile of the CD31+ endothelial cells was assessed using quantitative real-time polymerase chain reaction (PCR) arrays. Focusing on 84 angiogenesis-associated genes, we identified 22 genes with greater than 4-fold regulation and significantly enhanced transcription (p <.05) within 21 days of pneumonectomy. Cluster analysis of the 22 genes indicated that changes in gene expression did not occur in a single phase, but in at least four waves of gene expression: a wave demonstrating decreased gene expression more than 3 days after pneumonectomy and 3 sequential waves of increased expression on days 6, 14, and 21 after pneumonectomy. These findings indicate that a network of gene interactions contributes to angiogenesis during compensatory lung growth

    Asthma-susceptibility variants identified using probands in case-control and family-based analyses

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    <p>Abstract</p> <p>Background</p> <p>Asthma is a chronic respiratory disease whose genetic basis has been explored for over two decades, most recently via genome-wide association studies. We sought to find asthma-susceptibility variants by using probands from a single population in both family-based and case-control association designs.</p> <p>Methods</p> <p>We used probands from the Childhood Asthma Management Program (CAMP) in two primary genome-wide association study designs: (1) probands were combined with publicly available population controls in a case-control design, and (2) probands and their parents were used in a family-based design. We followed a two-stage replication process utilizing three independent populations to validate our primary findings.</p> <p>Results</p> <p>We found that single nucleotide polymorphisms with similar case-control and family-based association results were more likely to replicate in the independent populations, than those with the smallest p-values in either the case-control or family-based design alone. The single nucleotide polymorphism that showed the strongest evidence for association to asthma was rs17572584, which replicated in 2/3 independent populations with an overall p-value among replication populations of 3.5E-05. This variant is near a gene that encodes an enzyme that has been implicated to act coordinately with modulators of Th2 cell differentiation and is expressed in human lung.</p> <p>Conclusions</p> <p>Our results suggest that using probands from family-based studies in case-control designs, and combining results of both family-based and case-control approaches, may be a way to augment our ability to find SNPs associated with asthma and other complex diseases.</p
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