Evidence map›Paper›PMID 31965587›Full record

ArticleEnvironmental toxicology and chemistry2020

Adverse Outcome Pathway Network-Based Assessment of the Interactive Effects of an Androgen Receptor Agonist and an Aromatase Inhibitor on Fish Endocrine Function.

Gerald T Ankley, Brett R Blackwell, Jenna E Cavallin, Jon A Doering, David J Feifarek, Kathleen M Jensen, Michael D Kahl, Carlie A LaLone, Shane T Poole, Eric C Randolph and 2 more

Open access · greenAbstract read
In one paragraph

Article in Environmental toxicology and chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 36% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Gerald T AnkleyGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Brett R BlackwellGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Jenna E CavallinBadger Technical Services, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.ORCID 0000-0001-7883-4740
Jon A DoeringNational Research Council, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.
David J FeifarekStudent Services Contract, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.
Kathleen M JensenGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Michael D KahlGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Carlie A LaLoneGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.ORCID 0000-0003-3174-1314
Shane T PooleStudent Services Contract, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.
Eric C RandolphOak Ridge Institute for Science and Education, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.
Travis W SaariStudent Services Contract, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.
Daniel L VilleneuveGreat Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.ORCID 0000-0003-2801-0203
Environmental Protection Agency · USNational Academies of Sciences, Engineering, and Medicine · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Predictive approaches to assessing the toxicity of contaminant mixtures have been largely limited to chemicals that exert effects through the same biological molecular initiating event. However, by understanding specific pathways through which chemicals exert effects, it may be possible to identify shared "downstream" nodes as the basis for forecasting interactive effects of chemicals with different molecular initiating events. Adverse outcome pathway (AOP) networks conceptually support this type of analysis. We assessed the utility of a simple AOP network for predicting the effects of mixtures of an aromatase inhibitor (fadrozole) and an androgen receptor agonist (17β-trenbolone) on aspects of reproductive endocrine function in female fathead minnows. The fish were exposed to multiple concentrations of fadrozole and 17β-trenbolone individually or in combination for 48 or 96 h. Effects on 2 shared nodes in the AOP network, plasma 17β-estradiol (E2) concentration and vitellogenin (VTG) production (measured as hepatic vtg transcripts) responded as anticipated to fadrozole alone but were minimally impacted by 17β-trenbolone alone. Overall, there were indications that 17β-trenbolone enhanced decreases in E2 and vtg in fadrozole-exposed fish, as anticipated, but the results often were not statistically significant. Failure to consistently observe hypothesized interactions between fadrozole and 17β-trenbolone could be due to several factors, including lack of impact of 17β-trenbolone, inherent biological variability in the endpoints assessed, and/or an incomplete understanding of interactions (including feedback) between different pathways within the hypothalamic-pituitary-gonadal axis. Environ Toxicol Chem 2020;39:913-922. © 2020 SETAC.

Indexed as

Adverse Outcome PathwaysAndrogensAnimalsAromatase InhibitorsCyprinidaeDrug SynergismEndocrine SystemEstradiolFadrozoleFemaleHypothalamo-Hypophyseal SystemMaleOvaryReproductionTrenbolone AcetateVitellogeninsAndrogensAromatase InhibitorsEstradiolFadrozoleTrenbolone AcetateVitellogeninsAdverse outcome pathwayEndocrineFishMechanismToxicity

Identifiers

PMID31965587
PMCPMC7357796
OpenAlexW3002075839

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.