Cross-ORD Post-Doctoral. Fellowship Program

Haluk Ozkaynak and Bruce Jones

USEPA Office of Research and Development, National Exposure Research Laboratory, RTP, NC



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The EPA's Office of Research and Development (ORD) is comprised of several different laboratories and centers whic
share the common goal of providing research that can be applied to better protect the environment and human health
Partnerships and collaboration between labs and centers serve as an effective mechanism for the exchange of ideas
and the understanding of research perspectives between related scientific disciplines. In the summer of 2005, EPA-
ORD initiated a new cross-ORD post-doctoral fellowship program, which is designed to promote greater collaboration
between ORD's labs and centers. After a nation-wide search, the cross-ORD post-doctoral fellows were selected in both
the human health and ecosystems research areas and assigned primary, secondary, and tertiary mentors based upon
the interdisciplinary nature of their specific research focus. Each cross-ORD post-doctoral fellow developed a detailed
research plan jointly with his or her mentors. These research plans outlined collaborative research projects to be
conducted during the four year fellowship, along with the anticipated impact that each project would have on supporting
the mission of the EPA. Research topics of the nine cross-ORD fellows include: 1) Computational systems biology
modeling to predict toxicological mechanisms (Michael Breen), 2) Characterization of environmental exposures and
associated health risks in aging populations (Doug Johns), 3) Applications of exposure analysis tools in environmental
epidemiology (Mary Johnson), 4) Building realistic biologically based pharmacokinetic models for predicting
susceptibility in aging populations (Janice Lee), 5), Molecular modeling of the interaction between environmental
chemicals and targets for chemical toxicity (Melissa Pasquinelli), 6) Predictive ecological niche modeling in aquatic
systems (Kristina McNyset), 7) Quantifying key drivers of change in the built environment and their interaction with
changes in the natural environment (Johns Thomas), 8) Biotic responses to hydrologic alteration in suburban headwater
streams and potential for storm water mitigation (Allison Roy), and 9) Effectiveness of best management practices in
mitigating storm water runoff and water quality (Yu Zhang). In addition to providing excellent interdisciplinary scientific
training for the post-doctoral fellows, it is anticipated that the findings of each of these projects will result in the
publication of several peer-reviewed journal articles. EPA envisions that this program will foster further collaboration
between the different ORD labs and centers, thereby leading to more focused research strategies and a better
understanding of the relationships between environmental pollution, exposure, and human and ecological health.

4*



Disclaimer: although this work was reviewed by EPA
and approved for publication, it may not necessarily
reflect official Agency policy.

NCEA

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Doug Johns1

Janice S. Lee1

Mentors: Bob Sonawane1, Jackie Moya1,
Tom McCurdy2, Vernon Benignus3
'NCEA, Washington, DC;

2NERL 3NHEERL, Research Triangle Park, NC

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Environmental Exposures and Health Implications in Older Adults

Mentors: Chris Corton1, Mike Devito1, Mike Tornero2
1NHEERL, 2NERL, Research Triangle Park, NC

Building realistic biologically-based pharmacokinetic models
for predicting susceptibility in aged populations

Research Goal: Provide a more complete understanding of
environmental exposures and the associated health risks in aging
populations

Research Goal: Improve pharmacokinetic models of the aged by
incorporating genomic information on the differences in xenobiotic
metabolism gene expression between young and old populations

Projects

•	Organize a workshop to discuss the aging as a susceptible
population in conducting risk assessments

•	Develop an Exposure Factors Handbook for the aging

•	Conduct a large scale review and analysis of age-related
changes in phase I, phase II, and antioxidant enzyme activities

•	Develop a PBPK model to predict the kinetic behavior of specific
neurotoxicants in older adults

Anticipated Outcome

This research will provide information that can be used by risk
assessors to characterize age-related changes in exposures to
environmental chemicals, and understand how the aging body
responds to toxic stressors

Hazard Identification *

Exposure Assessment

Risk Characterization

Risk Assessment Paradigm

Example of a physiologically
based toxicokinetic model for
an inhaled VOC.

Projects

•	Generate gene expression profiles for xenobiotic metabolizing
enzymes (XMEs) in the aging rat, mouse & human

•	Generate gene expression profiles in the aging rat, mouse & human
after exposure to toluene & other chemicals to determine changes in
XMEs

•	Incorporate genomic information in the construction and improvement
of a rodent & human PB-PK model for the aged

Anticipated Outcomes

•	Identification of common and disparate changes in XMEs during aging
between tissues and across species

•	Integration of XME gene expression behavior in PB-PK models of
different life stages that help to predict toxicity in different
subpopulations

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Cluster analysis

Pathway analysis (KEGG)


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John Thomas1

/ Mentors: Mike Slimak, Anne Grambsch1, Jim Wickham2'
/	Hale Thurston3:

1NCEA, Washington, DC; 2NERL, Research Triangle Park, NC;
3NRMRL, Cincinnati, OH

Quantifying key drivers of change in the built environment and
their interaction with changes in the natural environment

Research Goals

•	Improve the treatment of socioeconomic factors in ecological
analyses.

•	Quantify the value of environmental amenities in property markets.

Projects

•	Socioeconomic Evaluation of Watershed Recovery

•	Valuation of Climate Sensitive Natural Amenities

•	Integrated Climate Land Use Scenarios

Socioeconomic Evaluation of Watershed Recovery

Basic Approach

Cities and Villages

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Watersheds

•	Aggregation of key
demographic, public
finance and
construction activity
data to a watershed
level.

•	Cluster analysis to
define the socioeconomic
profiles of watersheds.

Anticipated Outcomes

•	A decision support tool for evaluating stakeholder characteristics by
watershed.

Based on a methodology that can be replicated in any US state or
region.

Allison Roy1

Mentors: Bill Shuster1, Ken Fritz2, Tony Olsen3, David Walters2
1NRMRL, 2NERL. Cincinnati, OH; 3NHEERL, Corvallis, OR

Biotic responses to hydrologic alteration in suburban headwater
streams and potential for storm water mitigation

Research Goal 1: Characterize the hydrological and ecological
effects of urbanization on headwater streams

Relating stormflow and base-
flow hydrology, watershed
urbanization, & stream biota.

Anticipated Outcomes

Stormwater best management practices
(BMPs) distributed in residential watershed
using a voluntary, economic auction.

•	Refine NERL protocol for
sampling headwater streams

•	Identify indicators of disturb-
ance for protecting water
resources & ecosystem health

•	Provide baseline for restoring headwater streams

Research Goal 2: Evaluate the potential for stream ecosystem

restoration via stormwater management

Photo: Clear
Water Con-
servancy
http://www.urb
anwaterqualitv.
orq/rairiGardens
/rqindexl .htm

Anticipated Outcomes

•	Establish feasibility of stream
restoration using an auction

•	Determine benefits of BMPs
and potential for ecosystem
recovery

Photo: Urban Resources & Borderland Alliance Network
http://www.urbanwaterquality.org/RainGardens/rqindex1.htm


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Michael Breen1

Mentors: Rory Conolly1, Haluk Ozkaynak2
1NCCT, 2NERL, Research Triangle Park, NC

Computational Systems Biology Modeling to Predict
Toxicological Mechanisms

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Melissa Pasquinelli1

Mentors: Jim Rabinowitz1, Susan Laws2,

Mike Tornero3
1NCCT, 2NHERL, 3NERL, Research Triangle Park, NC

Molecular Modeling as a Tool for Assessing Chemical Toxicity

Research Goal; Develop and apply mechanistic mathematical

models to predict the biological effects of environmental chemical

exposures

Projects

•	Develop a mechanistic mathematical model of intratesticular and
intraovarian metabolic network that mediates steroid synthesis to
describe dose-response for endocrine disruptors

•	Develop visualization and analysis tools to compare computational
systems biology model predictions of protein concentrations with
western blot data

Anticipated Outcomes

•	Improve our understanding of the dynamic dose-response behavior
at the molecular level for risk assessments with endocrine disruptors

•	identity and link new molecular biomarkers that are indicative of the
ultimate adverse effects from endocrine disruptors

Mathematical Modeling of Steroidogenesis in Fish Gonads

Rate-limiting reaction

Conceptual model of the intratesticular steroidogenic pathway in fish for the
conversion of cholesterol (CHOL) to the secreted steroid hormones
ketotestosterone (KT), testosterone (T), and estradiol (E2). The first reaction
rate (v1) with the P450scc enzyme is the rate limiting step.

Research Goal; Develop and apply molecular modeling tools in order to

facilitate the assessment of mechanisms for chemical toxicity

Projects

•	Use the macromoiecular target-toxicant

paradigm to develop a computational	His23i

approach for the evaluation of potential
toxicological effects of environmental
chemicals, and then utilize this approach
study potential endocrine disrupting
chemicals (EDCs)	Qln60	v daidzein

•	Use molecular modeling to decipher the
mechanism of metabolism and other
toxicologically relevant processes

Anticipated Outcomes

•	Improve the predictive ability of screen
tools for chemical toxicity by integrating
molecular modeling with complementary '(Ihi60 17p-estradiol
experimental and computational
approaches, which will then be used to
categorize and prioritize chemicals for
further testing

•	Improve systems biology models by
integrating quantities that are calculated
with molecular modeling methods, such t
the rates of metabolism of pyrethroid
chemicals

The pictures to the above right show calculated poses of the Estrogen Receptor with
its natural ligand, 17b-estradiol, and two weak environmental estrogenic compounds,
daidzein and morin. The hydrogen bonds formed between the chemical and the
protein receptor (indicated by gray dotted lines) differ for each chemical and
hence impact its binding properties.


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Kristina McNyset1

/	Mentors: Bruce Jones2, Tony Olsen1, Henry Walker3, James Wickham4,

Brian Hill5, Henry Lee1, Lester Yuan10
1NHEERL, Corvailis, OR; 2NERL, Las Vegas, NV; 3NHEERL, Narragansett, Rl; 4NERL,
Research Triangle Park, NC; 5NHEERL, Duluth, MN; 6NHEERL, Newport, OR; 7NCEA,

Washington, DC

Predictive ecological niche modeling in aquatic systems

Research Goal: Develop spatially explicit models of biotic conditions

in aquatic systems

Projects

•	Determine best methods for predictive modeling of species distributions in
stream systems

•	Integrate point-sampled and landscape-level data in predictive ecological
niche modeling analyses in freshwater systems

•	Develop ecological data sets for use in spatially explicit modeling in
estuarine systems

Anticipated Outcomes

A set of modeling tools, datasets, and models that will increase our

understanding of biotic conditions in aquatic systems

Predicted Distribution of the nuisance diatom species
Didvmosphenia geminata (Lvngbve) M. Schmidt

This is the 10 best-model subset from a GARP (Genetic Algorithm for Rule-set Prediction) model run of 200
models. The color gradient from pinkto dark red indicates increasing model agreement between best-subset
models. The green circles are the training data used the build the models taken from the USGS NAWQA
project, the yellow squares are the testing data taken from the EPA WEMAP project. Overall omission was
110% at a threshold of 5 models.


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Epidemiology	Mary Johnson1

Mentors: Lucas Neas1, Haluk Ozkaynak2
1NHEERL 2NERL, Research Triangle Park, NC

Applications of exposure analysis tools in environmental epidemiology

a monitoring locations for DCHS

Anticipated Outcomes

• Improve connections
between traditional
exposure assessment and
epidemiological paradigms

Environmental Health Perspectives, March
2006 cover photo: www.ehponline.org

El Paso Children's Health Study
participant performing spirometry

Generate new ideas and methodologies to
improve scientific understanding of health
effects related to near-roadway exposures
to traffic-related air pollutants.

Research Goals

Develop and refine exposure analysis tools for assessing traffic-related air
pollutants and apply these tools in epidemiologic studies of human health.

Projects

• Evaluate existing metrics for
estimating personal exposures
to traffic-related pollution using
health and exposure
assessment data from the El
Paso Children's Health Study,
the Detroit Children's Health
Study (DCHS), and
Mechanistic Indicators of
Childhood Asthma (MICA)
study, and exposure data from
the Detroit Exposure Aerosol
Research Study (DEARS).

Traffic near 12 Mile Road in Detroit:
www.core.org.cn

•	Develop advanced exposure
assessment techniques based on
indoor/outdoor/personal measurements,
housing characteristics, time-activity
data, and dietary patterns (DEARS,
MICA), as well as GIS-based variables
and household characteristics (DCHS),

•	Apply and compare advanced exposure
metrics using health outcome data from
DCHS and biological data from MICA.

Air monitoring at Detroit area schools for DCHS


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Yu Zhang

Mentors: William Shuster1, Hale Thurston1, Matthew Heberling2,

Kenneth Fritz2
1NRMRL, Cincinnati, OH; 2NERL, Cincinnati, OH

Effectiveness of best management practices in mitigating storm
Research Goals

•	Determine the processes controlling the differences in runoff response
characteristics of catchments.

•	Separate transient stream flow features due to rainfall variability from the
inherent difference in catchment physiology.

•	Develop process-based modeling framework for projecting the hydrologic
impacts of best management practices (BMPs) and the associated
uncertainties

Projects	n

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Climate variability



Runoff
Model

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•	Examine climate variability of rainfall BMP
and establish the response
characteristics of neighboring
catchments independent of rainfall

•	Incorporate BMPs in
modeling frameworks and
determine the accuracy in
the model predictions by
comparing the model
results with observed
stream flow data

•	Characterize
uncertainties in the
projected impacts of BMPs
by incorporating climate
variability

Anticipated Outcomes

•	Physically based modeling framework for projecting the impacts of
BMPs with readily available GIS data as input

Guidelines for decision making concerning the BMPs given uncertainties
stemming from the variability and trends of climate

Impacts of BMPs?


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