Please login first
Elaine A Cohen Hubal  - - - 
Top co-authors See all
Mark R. Wiesner

169 shared publications

Thomas E. McKone

157 shared publications

Roger M. Nisbet

119 shared publications

Catherine J. Murphy

112 shared publications

22
Publications
0
Reads
0
Downloads
230
Citations
Publication Record
Distribution of Articles published per year 
(2000 - 2017)
Total number of journals
published in
 
14
 
Publications See all
Article 0 Reads 1 Citation A comprehensive framework for evaluating the environmental health and safety implications of engineered nanomaterials Sheau-Fung Thai, William K. Boyes, Brittany Lila M. Thornton... Published: 29 June 2017
Critical Reviews in Toxicology, doi: 10.1080/10408444.2017.1328400
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
Engineered nanomaterials (ENM) are a growing aspect of the global economy, and their safe and sustainable development, use, and eventual disposal requires the capability to forecast and avoid potential problems. This review provides a framework to evaluate the health and safety implications of ENM releases into the environment, including purposeful releases such as for antimicrobial sprays or nano-enabled pesticides, and inadvertent releases as a consequence of other intended applications. Considerations encompass product life cycles, environmental media, exposed populations, and possible adverse outcomes. This framework is presented as a series of compartmental flow diagrams that serve as a basis to help derive future quantitative predictive models, guide research, and support development of tools for making risk-based decisions. After use, ENM are not expected to remain in their original form due to reactivity and/or propensity for hetero-agglomeration in environmental media. Therefore, emphasis is placed on characterizing ENM as they occur in environmental or biological matrices. In addition, predicting the activity of ENM in the environment is difficult due to the multiple dynamic interactions between the physical/chemical aspects of ENM and similarly complex environmental conditions. Others have proposed the use of simple predictive functional assays as an intermediate step to address the challenge of using physical/chemical properties to predict environmental fate and behavior of ENM. The nodes and interactions of the framework presented here reflect phase transitions that could be targets for development of such assays to estimate kinetic reaction rates and simplify model predictions. Application, refinement, and demonstration of this framework, along with an associated knowledgebase that includes targeted functional assay data, will allow better de novo predictions of potential exposures and adverse outcomes.
Article 0 Reads 19 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
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.
Article 0 Reads 4 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
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
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 9 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
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
Highlights•Exposure models are compared to prioritize chemicals on the basis of exposure.•Ranking results are most sensitive to the initial emission rate assumptions.•Key knowledge gaps are identified for high throughput exposure based prioritization. AbstractWhile only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA's need to develop novel approaches and tools for rapidly prioritizing chemicals, a “Challenge” was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA's effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches.
Article 0 Reads 3 Citations Incorporating exposure information into the toxicological prioritization index decision support framework David M. Reif, Richard Judson, Elaine A. Cohen Hubal, Sumit ... Published: 01 October 2012
Science of The Total Environment, doi: 10.1016/j.scitotenv.2012.06.086
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to potential for endocrine disruption. However, exposure information is required along with hazard information to prioritize chemicals for further testing. The goal of this analysis is to demonstrate the utility of the ToxPi framework for incorporating exposure information to rank chemicals and improve understanding of key exposure surrogates. The ToxPi tool was applied to common exposure surrogates (i.e., fate parameters, manufacturing volume, and occurrence measurements) and the relationship between resulting rankings and higher-tiered exposure estimates was investigated. As information more directly relevant to human exposure potential is incorporated, relative rank of chemicals changes. Binned ToxPi results are shown to be consistent with chemical priorities based on crude measures of population-level exposure for a limited set of chemicals. However, these bins are not predictive of higher tiered estimates of exposure such as those developed for pesticide registration. Although rankings based on exposure surrogates are used in a variety of contexts, analysis of the relevance of these tools is challenging. The ToxPi framework can be used to gain insight into the factors driving these rankings and aid identification of key exposure metrics. Additional exposure data is required to build confidence in exposure-based chemical prioritization. Highlights► We apply a decision support tool to incorporate exposure surrogates and prioritize chemicals based on exposure potentials. ► The ranking scheme is qualitatively compared with NHANES biomonitoring data and with chronic dietary exposure estimates. ► The ToxPi tool facilitates a high level view of large amount of exposure information. ► This knowledge-driven approach allows for the key drivers of exposure potential to be identified efficiently. ► Studies are needed to understand relationship between exposure surrogates, screening assessment, biomonitoring data.
Article 0 Reads 14 Citations Providing the Missing Link: the Exposure Science Ontology ExO Carolyn J. Mattingly, Thomas E. McKone, Michael A. Callahan,... Published: 20 March 2012
Environmental Science & Technology, doi: 10.1021/es2033857
DOI See at publisher website
PubMed View at PubMed
ABS Show/hide abstract
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.