ArticleEnvironmental science & technology2014
Bridging the gap from screening assays to estrogenic effects in fish: potential roles of multiple estrogen receptor subtypes.
Article in Environmental science & technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 42 citations in OpenAlex.
- Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA.Environmental monitoring and assessment · 2021Article
- Occurrence and In Vitro Bioactivity of Estrogen, Androgen, and Glucocorticoid Compounds in a Nationwide Screen of United States Stream Waters.Environmental science & technology · 2017Article
- Re-evaluating the Significance of Estrone as an Environmental Estrogen.Environmental science & technology · 2017Article
- Sharing the Roles: An Assessment of Japanese Medaka Estrogen Receptors in Vitellogenin Induction.Environmental science & technology · 2016Article
- Comparison of the sensitivity of four native Canadian fish species to 17-α ethinylestradiol, using an in vitro liver explant assay.Environmental science and pollution research international · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
This study seeks to delineate the ligand interactions that drive biomarker induction in fish exposed to estrogenic pollutants and provide a case study on the capacity of human (h) estrogen receptor (ER)-based in vitro screening assays to predict estrogenic effects in aquatic species. Adult male Japanese medaka (Oryzias latipes) were exposed to solutions of singular steroidal estrogens or to the estrogenic extract of an anaerobic swine waste lagoon. All exposure concentrations were calibrated to be equipotent based on the yeast estrogen screen (YES), which reports activation of hERα. These exposures elicited significantly different magnitudes of hepatic vitellogenin and choriogenin gene induction in the male medaka. Effects of the same YES-calibrated solutions in the T47D-KBluc assay, which reports activation of hERα and hERβ, generally recapitulated observations in medaka. Using competitive ligand binding assays, it was found that the magnitude of vitellogenin/choriogenin induction by different estrogenic ligands correlated positively with preferential binding affinity for medaka ERβ subtypes, which are highly expressed in male medaka liver prior to estrogen exposure. Results support emerging evidence that ERβ subtypes are critically involved in the teleost estrogenic response, with the ERα:ERβ ratio being of particular importance. Accordingly, incorporation of multiple ER subtypes into estrogen screening protocols may increase predictive value for the risk assessment of aquatic systems, including complex estrogenic mixtures.
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Identifiers
What OpenQuestion holds
Registered trials
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.