Evidence map›Paper›PMID 28671818›Full record

ArticleEnvironmental science & technology2017

An "EAR" on Environmental Surveillance and Monitoring: A Case Study on the Use of Exposure-Activity Ratios (EARs) to Prioritize Sites, Chemicals, and Bioactivities of Concern in Great Lakes Waters.

Brett R Blackwell, Gerald T Ankley, Steven R Corsi, Laura A DeCicco, Keith A Houck, Richard S Judson, Shibin Li, Matthew T Martin, Elizabeth Murphy, Anthony L Schroeder and 3 more

Abstract read
In one paragraph

Article in Environmental science & technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Brett R BlackwellMid-Continent Ecology Division, U.S. Environmental Protection Agency , 6201 Congdon Blvd., Duluth, Minnesota 55804, United States.ORCID http://orcid.org/0000-0003-1296-4539
Gerald T AnkleyMid-Continent Ecology Division, U.S. Environmental Protection Agency , 6201 Congdon Blvd., Duluth, Minnesota 55804, United States.ORCID http://orcid.org/0000-0002-9937-615X
Steven R CorsiWisconsin Water Science Center, U.S. Geological Survey , 8505 Research Way, Middleton, Wisconsin 53562, United States.
Laura A DeCiccoWisconsin Water Science Center, U.S. Geological Survey , 8505 Research Way, Middleton, Wisconsin 53562, United States.
Keith A HouckNational Center for Computational Toxicology, U.S. Environmental Protection Agency , 109 T.W. Alexander Drive, Research Triangle Park, North Carolina 27711, United States.
Richard S JudsonNational Center for Computational Toxicology, U.S. Environmental Protection Agency , 109 T.W. Alexander Drive, Research Triangle Park, North Carolina 27711, United States.
Shibin LiMid-Continent Ecology Division, U.S. Environmental Protection Agency , 6201 Congdon Blvd., Duluth, Minnesota 55804, United States.
Matthew T MartinNational Center for Computational Toxicology, U.S. Environmental Protection Agency , 109 T.W. Alexander Drive, Research Triangle Park, North Carolina 27711, United States.
Elizabeth MurphyGreat Lakes National Program Office, U.S. Environmental Protection Agency , 77 West Jackson Blvd., Chicago, Illinois 60604, United States.
Anthony L SchroederMath, Science, and Technology Department, University of Minnesota Crookston , 2900 University Avenue, Crookston, Minnesota 56716, United States.
Edwin R SmithGreat Lakes National Program Office, U.S. Environmental Protection Agency , 77 West Jackson Blvd., Chicago, Illinois 60604, United States.
Joe SwintekBadger Technical Services , 6201 Congdon Blvd., Duluth, Minnesota 55804, United States.
Daniel L VilleneuveMid-Continent Ecology Division, U.S. Environmental Protection Agency , 6201 Congdon Blvd., Duluth, Minnesota 55804, United States.ORCID http://orcid.org/0000-0003-2801-0203

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.

Indexed as

Biological AssayEnvironmental MonitoringHigh-Throughput Screening AssaysToxicity TestsBiomarkersGreat Lakes RegionHumansLakesBiomarkers

Identifiers

PMID28671818
PMCPMC6132252

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.