Evidence map›Paper›PMID 35262228›Full record

ArticleEnvironmental toxicology and chemistry2022

The ECOTOXicology Knowledgebase: A Curated Database of Ecologically Relevant Toxicity Tests to Support Environmental Research and Risk Assessment.

Jennifer H Olker, Colleen M Elonen, Anne Pilli, Arne Anderson, Brian Kinziger, Stephen Erickson, Michael Skopinski, Anita Pomplun, Carlie A LaLone, Christine L Russom and 1 more

Open access · greenAbstract read
In one paragraph

Article in Environmental toxicology and chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 1 pooled it
24.8field-weighted citation impact, top 1% of its field
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

77 citing papers in PubMed, 1 synthesis or guideline pooled it, 251 citations in OpenAlex.

  1. Weight of evidence for cross-species conservation of androgen receptor-based biological activity.Toxicological sciences : an official journal of the Society of Toxicology · 2023
    Pooled it
  2. Article
  3. AI/ML-based computational models for toxicity prediction.Environmental science and pollution research international · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Natural variation suggests candidate genes underlying Caenorhabditis elegans susceptibility to diverse toxicants.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Natural variation suggests candidate genes underlyingbioRxiv : the preprint server for biology · 2025
    Article
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

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

11 authors at 2 institutions in 1 country.

Jennifer H OlkerOffice of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota.ORCID 0000-0002-7877-4773
Colleen M ElonenOffice of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota.
Anne PilliGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Arne AndersonGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Brian KinzigerGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Stephen EricksonGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Michael SkopinskiGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Anita PomplunGeneral Dynamics Information Technology, Duluth, Minnesota, USA.
Carlie A LaLoneOffice of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota.ORCID 0000-0003-3174-1314
Christine L RussomOffice of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota.
Dale HoffOffice of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota.
General Dynamics (United States) · USEnvironmental Protection Agency · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

The need for assembled existing and new toxicity data has accelerated as the amount of chemicals introduced into commerce continues to grow and regulatory mandates require safety assessments for a greater number of chemicals. To address this evolving need, the ECOTOXicology Knowledgebase (ECOTOX) was developed starting in the 1980s and is currently the world's largest compilation of curated ecotoxicity data, providing support for assessments of chemical safety and ecological research through systematic and transparent literature review procedures. The recently released version of ECOTOX (Ver 5, www.epa.gov/ecotox) provides single-chemical ecotoxicity data for over 12,000 chemicals and ecological species with over one million test results from over 50,000 references. Presented is an overview of ECOTOX, detailing the literature review and data curation processes within the context of current systematic review practices and discussing how recent updates improve the accessibility and reusability of data to support the assessment, management, and research of environmental chemicals. Relevant and acceptable toxicity results are identified from studies in the scientific literature, with pertinent methodological details and results extracted following well-established controlled vocabularies and newly extracted toxicity data added quarterly to the public website. Release of ECOTOX, Ver 5, included an entirely redesigned user interface with enhanced data queries and retrieval options, visualizations to aid in data exploration, customizable outputs for export and use in external applications, and interoperability with chemical and toxicity databases and tools. This is a reliable source of curated ecological toxicity data for chemical assessments and research and continues to evolve with accessible and transparent state-of-the-art practices in literature data curation and increased interoperability to other relevant resources. Environ Toxicol Chem 2022;41:1520-1539. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Indexed as

EcotoxicologyToxicity TestsDatabases, FactualHumansKnowledge BasesRisk AssessmentChemical assessmentControlled vocabularyDatabaseEcotoxicologyEnvironmental toxicologyInteroperabilityNew approach methodologiesSystematic review

Identifiers

PMID35262228
PMCPMC9408435
OpenAlexW4220724626

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.