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Elaine A. Cohen Hubal  - - - 
Top co-authors See all
J. Michael White

302 shared publications

Connecticut Agricultural Experiment Station, 5758, New Haven, Connecticut, United States

Ee-Hua Wong

283 shared publications

Physics and Astronomy, Western University

Catherine J. Murphy

281 shared publications

Department of Chemistry, University of Illinois at Urbana—Champaign, 600 South Mathews Avenue, Urbana, Illinois 61801, United States

Judith A. Blake

259 shared publications

The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609 USA

Mark R. Wiesner

244 shared publications

Center for the Environmental Implications of Nanotechnology, Duke University, Durham, North Carolina 27708, United States

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Publication Record
Distribution of Articles published per year 
(2000 - 2017)
Publications See all
Article 0 Reads 3 Citations A comprehensive framework for evaluating the environmental health and safety implications of engineered nanomaterials William K. Boyes, Brittany Lila M. Thornton, Souhail R. Al-A... Published: 29 June 2017
Critical Reviews in Toxicology, doi: 10.1080/10408444.2017.1328400
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Article 0 Reads 29 Citations Considerations of Environmentally Relevant Test Conditions for Improved Evaluation of Ecological Hazards of Engineered N... Patricia A. Holden, Jorge L. Gardea-Torresdey, Fred Klaessig... Published: 03 June 2016
Environmental Science & Technology, doi: 10.1021/acs.est.6b00608
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Article 0 Reads 5 Citations Data-Driven Asthma Endotypes Defined from Blood Biomarker and Gene Expression Data Barbara Jane George, Jane E. Gallagher, ClarLynda R. William... Published: 02 February 2015
PLOS ONE, doi: 10.1371/journal.pone.0117445
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The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.
Article 0 Reads 11 Citations Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential Jade Mitchell, Jon A. Arnot, Sastry Isukapalli, Muhilan Pand... Published: 01 August 2013
Science of The Total Environment, doi: 10.1016/j.scitotenv.2013.04.051
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Article 3 Reads 3 Citations Incorporating exposure information into the toxicological prioritization index decision support framework Sumit Gangwal, David M. Reif, Shad Mosher, Peter P. Egeghy, ... Published: 01 October 2012
Science of The Total Environment, doi: 10.1016/j.scitotenv.2012.06.086
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Article 0 Reads 22 Citations Providing the missing link: the exposure science ontology ExO. Carolyn J. Mattingly, Thomas E. McKone, Michael A. Callahan,... Published: 12 March 2012
Environmental Science & Technology, doi: 10.1021/es2033857
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Environmental health information resources lack exposure data required to translate molecular insights, elucidate environmental contributions to diseases, and assess human health and ecological risks. We report development of an Exposure Ontology, ExO, designed to address this information gap by facilitating centralization and integration of exposure data. Major concepts were defined and the ontology drafted and evaluated by a working group of exposure scientists and other ontology and database experts. The resulting major concepts forming the basis for the ontology are "exposure stressor", "exposure receptor", "exposure event", and "exposure outcome". Although design of the first version of ExO focused on human exposure to chemicals, we anticipate expansion by the scientific community to address exposures of human and ecological receptors to the full suite of environmental stressors. Like other widely used ontologies, ExO is intended to link exposure science and diverse environmental health disciplines including toxicology, epidemiology, disease surveillance, and epigenetics.
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