Evidence map›Paper›PMID 23611293›Full record

ArticleChemical research in toxicology2013

Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays.

Nisha S Sipes, Matthew T Martin, Parth Kothiya, David M Reif, Richard S Judson, Ann M Richard, Keith A Houck, David J Dix, Robert J Kavlock, Thomas B Knudsen

Abstract read
In one paragraph

Article in Chemical research in toxicology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed
–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

91 citing papers in PubMed.

  1. Article
  2. Article
  3. TheToxicology reports · 2025
    Article
  4. Review
  5. Personal air sampling for pesticides in the California San Joaquin Valley.Journal of exposure science & environmental epidemiology · 2025
    Article
  6. Review
  7. Article
  8. Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping.Toxicological sciences : an official journal of the Society of Toxicology · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. VenomPred 2.0: A NovelJournal of chemical information and modeling · 2024
    Article
  14. Review
  15. Computational Construction of Toxicant Signaling Networks.Chemical research in toxicology · 2023
    Article
  16. Article
  17. Principles and Procedures for Assessment of Acute Toxicity IncorporatingComputational toxicology (Amsterdam, Netherlands) · 2022
    Article
  18. Article
  19. Article
  20. Acetylcholinesterase Inhibition Assays for High-Throughput Screening.Methods in molecular biology (Clifton, N.J.) · 2022
    Article

31 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

10 authors.

Nisha S SipesNational Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA. sipes.nisha@epa.gov
Matthew T Martin
Parth Kothiya
David M Reif
Richard S Judson
Ann M Richard
Keith A Houck
David J Dix
Robert J Kavlock
Thomas B Knudsen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA's ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical-assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical-assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical-target combinations clustered with known chemical-target interactions. Results from this large inventory of chemical-biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.

Indexed as

High-Throughput Screening AssaysAnimalsEnzymesGuinea PigsHumansMembrane Transport ProteinsOrganic ChemicalsRatsReceptors, G-Protein-CoupledSignal TransductionEnzymesMembrane Transport ProteinsOrganic ChemicalsReceptors, G-Protein-Coupled

Identifiers

PMID23611293
PMCPMC3685188

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.