The CEINT Informatics Knowledge Commons DBI

The CEINT Informatics Knowledge Commons
Christine Ogilvie Hendren1, Yuan Tian1, Sandra Karcher2, Jeanne VanBriessen2, Gregory V. Lowry2, Mark R. Wiesner1
NSF Grantees Meeting w Arlington, VA w December 9-10, 2014
1 Duke University, Department of Civil and Environmental Engineering
2 Carnegie Mellon University, Department of Civil and Environmental Engineering
The CEINT Informatics Knowledge Commons design reflects the analytical needs defined by the dual aspects of the CEINT Mission:
CEINT IKC must support fundamental mechanistic investigations
•  To elucidate general principles that determine nanomaterial behavior in the environment
•  To translate this knowledge into models to forecast risk and to provide guidance in assessing existing
and future concerns surrounding the environmental implications of engineered nanomaterials.
Supports Detailed
Mechanistic Meta-Analysis
CEINT Informatics Knowledge Commons Objectives
Facilitate direct researcher interactions with the system
•  System designed and data curated by CEINT Data Integration Team
(DIT) in close conjunction with CEINT experimentalists to focus on
an initial pilot scope to design a modular curation process that can
flexibly analyze data at various levels of granularity (Sample papers
1-20)
• 
• 
½ the curated papers come from CEINT work, ½ from non-CEINT
published literature
Currently capture consistently curated data either at the calculated
value level or can accommodate direct measurement and
observation level, in support of deeper data-mining and metaanalyses
Acknowledgements
Nanoparticle
Properties
bandgap
Shape
Social and Engineered
Properties
ENM
Quantity
Electrical
Conductivity
Human behavior
Release
Fraction
NOM/
Macromol
Composition
strength
Coating
pH
Availability
charge
Redox
Developmental
Inhibition
Neurotoxicty
Community
composition
Mutagenicity
Deposition
Transport
Environmental
Stressors
Surfaces
(bacteria,
clay…)
Oxidative stress
Settling
Bio-Geo-Chemical
Transformations
Exposure Bioactivity
Collision
Rate
Aggregation
Geochemical
Transformations
Light
Attachment
ROS
Dissolution
Biodegredation
Fluid
Flow
Ionic
Composition
Size
Precipitation
System
Properties
Genotoxicity
Distribution in
the System
Biouptake /
System Transfer
Mortality
•  The CEINT IKC is designed to support
queries at a higher altitude to interrogate
how Functional Assays can be used as a
realistic categorization strategy for
nanomaterials
•  Functional Assay Parameters are
aggregated, empirical measurements of NM
behaviors in specific systems
•  We query relationships between FA
Parameters and
1.  Effects of interest, including ecological
effects, toxicological effects, and
possibly performance of ENMs.
2.  Core material and system properties, to
ultimately work toward enabling QSAR
approaches.
Nanoparticle
Properties
Social &
Engineered
Properties
System
Properties
• 
• 
• 
• 
Functiona
l Assays
Exposure
Aggregation rate
Attachment efficiency
Distribution coefficient
Dissolution rate
Hazard
RISK
Reproduction
Cellular and Organismal Hazards Ecosystem Hazard Parameter
or Process
LEGEND
Material and System
Properties
Material and System
Interactions
The current CEINT IKC is designed to support curation of data and
development of queries at a variety of detail levels in pursuit of targeted
research questions for the nanoAg pilot effort. The hypothesis being
tested for the pilot study is that functional assay parameters can be
utilized to predict nanomaterial exposure, bioaccumulation, and/or toxic
effects in complex systems (mesocosms) and in laboratory studies:
Questions:
•  Specific functional assays being investigated: attachment,
dissolution, biouptake and transformation
•  Are results of exposure, bioaccumulation, and/or toxic effects
experiments in laboratory studies with limited independent variables
predictive of results in mesocosms?
•  Working backwards from endpoints of interest (exposure
concentrations, bioaccumulation, and toxic effects), are there
commonalities between materials that impart the same results?
(primary particle size, coating, etc.)
Supports Functional Assay Testing
for Forecasting of ENM Impacts
Collect and organize data and meta-data at a
level that captures detailed experiments in
complex systems to a reproducible level.
Material Impacts
Develop an integrated database and associated visualization tools that
are accessible to CEINT researchers, who can analyze their collective
data and utilize tools to visualize their own results integrated with the
work of their colleagues and with relevant literature.
CEINT IKC must support near-term risk-based decisions
Risk Framing Realistic Scenarios with Integrated Model Estimates
Mechanism
Example of
Mechanism
Discovered Via
Integrated
Research
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REFERENCES
This Poster
To access the list of references in this poster, please
scan this QR code or visit us at:
http://ceint.duke.edu/2014_nsf_nsec_grantees_poster:
All of CEINT
To access a full list of references published by
CEINT, please scan this QR code or visit us at:
www.ceint.duke.edu
The CEINT IKC is designed to
incorporate experimental data and
model estimates of scenario parameters
important for forecasting behavior and
risks of nanomaterials.
•  Estimated material release rates
•  Estimated material transformation
rates
•  Estimated bioaccumulation rates
and factors
•  Estimated mobility and persistence
This material is based upon work supported by the National Science Foundation (NSF) and the Environmental Protection Agency (EPA) under NSF Cooperative Agreement DBI-1266252, Center for the
Environmental Implications of NanoTechnology (CEINT). It was previously funded under NSF Cooperative Agreement EF-0830093. Any opinions, findings, conclusions or recommendations expressed in
this material are those of the author(s) and do not necessarily reflect the views of the NSF or the EPA. This work has not been subjected to EPA review and no official endorsement should be inferred.
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