LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 5 of total 5

Search options

  1. Article ; Online: Low-calorie sweeteners and health outcomes

    Juleen Lam / Brian E. Howard / Kristina Thayer / Ruchir R. Shah

    Environment International, Vol 123, Iss , Pp 451-

    A demonstration of rapid evidence mapping (rEM)

    2019  Volume 458

    Abstract: Background: “Evidence Mapping” is an emerging tool that is increasingly being used to systematically identify, review, organize, quantify, and summarize the literature. It can be used as an effective method for identifying well-studied topic areas ... ...

    Abstract Background: “Evidence Mapping” is an emerging tool that is increasingly being used to systematically identify, review, organize, quantify, and summarize the literature. It can be used as an effective method for identifying well-studied topic areas relevant to a broad research question along with any important literature gaps. However, because the procedure can be significantly resource-intensive, approaches that can increase the speed and reproducibility of evidence mapping are in great demand. Methods: We propose an alternative process called “rapid Evidence Mapping” (rEM) to map the scientific evidence in a time-efficient manner, while still utilizing rigorous, transparent and explicit methodological approaches. To illustrate its application, we have conducted a proof-of-concept case study on the topic of low-calorie sweeteners (LCS) with respect to human dietary exposures and health outcomes. During this process, we developed and made publicly available our study protocol, established a PECO (Participants, Exposure, Comparator, and Outcomes) statement, searched the literature, screened titles and abstracts to identify potentially relevant studies, and applied semi-automated machine learning approaches to tag and categorize the included articles. We created various visualizations including bubble plots and frequency tables to map the evidence and research gaps according to comparison type, population baseline health status, outcome group, and study sample size. We compared our results with a traditional evidence mapping of the same topic published in 2016 (Wang et al., 2016). Results: We conducted an rEM of LCS, for which we identified 8122 records from a PubMed search (January 1, 1946–May 1, 2014) and then utilized machine learning (SWIFT-Active Screener) to prioritize relevant records. After screening 2267 (28%) of the total set of titles and abstracts to achieve 95% estimated recall, we ultimately included 297 relevant studies. Overall, our findings corroborated those of Wang et al. (2016) and identified ...
    Keywords Environmental sciences ; GE1-350
    Subject code 306
    Language English
    Publishing date 2019-02-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Article ; Online: Risk and Protective Factors in the COVID-19 Pandemic

    Rebecca Elmore / Lena Schmidt / Juleen Lam / Brian E. Howard / Arpit Tandon / Christopher Norman / Jason Phillips / Mihir Shah / Shyam Patel / Tyler Albert / Debra J. Taxman / Ruchir R. Shah

    Frontiers in Public Health, Vol

    A Rapid Evidence Map

    2020  Volume 8

    Abstract: Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are ... ...

    Abstract Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public.Methods: We developed a protocol that includes a study goal, study questions, a PECO statement, and a process for screening literature by combining semi-automated machine learning with the expertise of our review team. We applied this protocol to reports within the COVID-19 Open Research Dataset (CORD-19) that were published in early 2020. SWIFT-Active Screener was used to prioritize records according to pre-defined inclusion criteria. Relevant studies were categorized by risk and protective status; susceptibility category (Behavioral, Physiological, Demographic, and Environmental); and affected sub-populations. Using tagged studies, we created an rEM for COVID-19 susceptibility that reveals: (1) current lines of evidence; (2) knowledge gaps; and (3) areas that may benefit from systematic review.Results: We imported 4,330 titles and abstracts from CORD-19. After screening 3,521 of these to achieve 99% estimated recall, 217 relevant studies were identified. Most included studies concerned the impact of underlying comorbidities (Physiological); age and gender (Demographic); and social factors (Environmental) on COVID-19 outcomes. Among the relevant studies, older males with comorbidities were commonly reported to have the poorest outcomes. We noted a paucity of COVID-19 studies among children and susceptible sub-groups, including pregnant women, racial minorities, refugees/migrants, and healthcare workers, with few studies examining protective factors.Conclusion: Using rEM analysis, we ...
    Keywords rapid evidence mapping ; COVID-19 ; risk factors ; protective factors ; literature screening ; disease susceptibility ; Public aspects of medicine ; RA1-1270
    Subject code 306
    Language English
    Publishing date 2020-11-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article ; Online: SWIFT-Active Screener

    Brian E. Howard / Jason Phillips / Arpit Tandon / Adyasha Maharana / Rebecca Elmore / Deepak Mav / Alex Sedykh / Kristina Thayer / B. Alex Merrick / Vickie Walker / Andrew Rooney / Ruchir R. Shah

    Environment International, Vol 138, Iss , Pp - (2020)

    Accelerated document screening through active learning and integrated recall estimation

    2020  

    Abstract: Background: In the screening phase of systematic review, researchers use detailed inclusion/exclusion criteria to decide whether each article in a set of candidate articles is relevant to the research question under consideration. A typical review may ... ...

    Abstract Background: In the screening phase of systematic review, researchers use detailed inclusion/exclusion criteria to decide whether each article in a set of candidate articles is relevant to the research question under consideration. A typical review may require screening thousands or tens of thousands of articles in and can utilize hundreds of person-hours of labor. Methods: Here we introduce SWIFT-Active Screener, a web-based, collaborative systematic review software application, designed to reduce the overall screening burden required during this resource-intensive phase of the review process. To prioritize articles for review, SWIFT-Active Screener uses active learning, a type of machine learning that incorporates user feedback during screening. Meanwhile, a negative binomial model is employed to estimate the number of relevant articles remaining in the unscreened document list. Using a simulation involving 26 diverse systematic review datasets that were previously screened by reviewers, we evaluated both the document prioritization and recall estimation methods. Results: On average, 95% of the relevant articles were identified after screening only 40% of the total reference list. In the 5 document sets with 5,000 or more references, 95% recall was achieved after screening only 34% of the available references, on average. Furthermore, the recall estimator we have proposed provides a useful, conservative estimate of the percentage of relevant documents identified during the screening process. Conclusion: SWIFT-Active Screener can result in significant time savings compared to traditional screening and the savings are increased for larger project sizes. Moreover, the integration of explicit recall estimation during screening solves an important challenge faced by all machine learning systems for document screening: when to stop screening a prioritized reference list. The software is currently available in the form of a multi-user, collaborative, online web application. Keywords: Systematic review, Evidence ...
    Keywords Environmental sciences ; GE1-350
    Subject code 004
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Article ; Online: A hybrid gene selection approach to create the S1500+ targeted gene sets for use in high-throughput transcriptomics.

    Deepak Mav / Ruchir R Shah / Brian E Howard / Scott S Auerbach / Pierre R Bushel / Jennifer B Collins / David L Gerhold / Richard S Judson / Agnes L Karmaus / Elizabeth A Maull / Donna L Mendrick / B Alex Merrick / Nisha S Sipes / Daniel Svoboda / Richard S Paules

    PLoS ONE, Vol 13, Iss 2, p e

    2018  Volume 0191105

    Abstract: Changes in gene expression can help reveal the mechanisms of disease processes and the mode of action for toxicities and adverse effects on cellular responses induced by exposures to chemicals, drugs and environment agents. The U.S. Tox21 Federal ... ...

    Abstract Changes in gene expression can help reveal the mechanisms of disease processes and the mode of action for toxicities and adverse effects on cellular responses induced by exposures to chemicals, drugs and environment agents. The U.S. Tox21 Federal collaboration, which currently quantifies the biological effects of nearly 10,000 chemicals via quantitative high-throughput screening(qHTS) in in vitro model systems, is now making an effort to incorporate gene expression profiling into the existing battery of assays. Whole transcriptome analyses performed on large numbers of samples using microarrays or RNA-Seq is currently cost-prohibitive. Accordingly, the Tox21 Program is pursuing a high-throughput transcriptomics (HTT) method that focuses on the targeted detection of gene expression for a carefully selected subset of the transcriptome that potentially can reduce the cost by a factor of 10-fold, allowing for the analysis of larger numbers of samples. To identify the optimal transcriptome subset, genes were sought that are (1) representative of the highly diverse biological space, (2) capable of serving as a proxy for expression changes in unmeasured genes, and (3) sufficient to provide coverage of well described biological pathways. A hybrid method for gene selection is presented herein that combines data-driven and knowledge-driven concepts into one cohesive method. Our approach is modular, applicable to any species, and facilitates a robust, quantitative evaluation of performance. In particular, we were able to perform gene selection such that the resulting set of "sentinel genes" adequately represents all known canonical pathways from Molecular Signature Database (MSigDB v4.0) and can be used to infer expression changes for the remainder of the transcriptome. The resulting computational model allowed us to choose a purely data-driven subset of 1500 sentinel genes, referred to as the S1500 set, which was then augmented using a knowledge-driven selection of additional genes to create the final S1500+ gene set. Our ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 612
    Language English
    Publishing date 2018-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article ; Online: High-throughput RNA sequencing of pseudomonas-infected Arabidopsis reveals hidden transcriptome complexity and novel splice variants.

    Brian E Howard / Qiwen Hu / Ahmet Can Babaoglu / Manan Chandra / Monica Borghi / Xiaoping Tan / Luyan He / Heike Winter-Sederoff / Walter Gassmann / Paola Veronese / Steffen Heber

    PLoS ONE, Vol 8, Iss 10, p e

    2013  Volume 74183

    Abstract: We report the results of a genome-wide analysis of transcription in Arabidopsis thaliana after treatment with Pseudomonas syringae pathovar tomato. Our time course RNA-Seq experiment uses over 500 million read pairs to provide a detailed characterization ...

    Abstract We report the results of a genome-wide analysis of transcription in Arabidopsis thaliana after treatment with Pseudomonas syringae pathovar tomato. Our time course RNA-Seq experiment uses over 500 million read pairs to provide a detailed characterization of the response to infection in both susceptible and resistant hosts. The set of observed differentially expressed genes is consistent with previous studies, confirming and extending existing findings about genes likely to play an important role in the defense response to Pseudomonas syringae. The high coverage of the Arabidopsis transcriptome resulted in the discovery of a surprisingly large number of alternative splicing (AS) events--more than 44% of multi-exon genes showed evidence for novel AS in at least one of the probed conditions. This demonstrates that the Arabidopsis transcriptome annotation is still highly incomplete, and that AS events are more abundant than expected. To further refine our predictions, we identified genes with statistically significant changes in the ratios of alternative isoforms between treatments. This set includes several genes previously known to be alternatively spliced or expressed during the defense response, and it may serve as a pool of candidate genes for regulated alternative splicing with possible biological relevance for the defense response against invasive pathogens.
    Keywords Medicine ; R ; Science ; Q
    Subject code 572
    Language English
    Publishing date 2013-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top