Utility of in vitro test methods to assess the activity of xenoestrogens in fish
Bibliographic record
Abstract
The results of the present study have demonstrated the utility of an estrogen receptor (ER) competitive ligand-binding assay, a hepatocyte vitellogenin (VTG) induction bioassay, and an ER reporter gene bioassay in characterizing the activity of model estrogen agonists (17beta-estradiol [E2], ethynylestradiol, and nonylphenol) and antagonists (tamoxifen and ZM 189154) in rainbow trout (Oncorhynchus mykiss). The in vitro results were validated against in vivo trout waterborne exposures to E2 and tamoxifen. The results showed that all three in vitro assays were capable of detecting the hormonal activities of the selected model compounds in a dose-dependent manner, with the exception of nonylphenol in the ER reporter gene bioassay. However, the relative potency rankings of the model compounds were not consistent between these assays, which suggests that the relative potencies obtained within assays may have limited predictive value between assays. Discrepancies in potencies most likely can be attributed to the different levels of cellular organization in each assay. In addition to model compounds, we also evaluated the responses of the ER-binding assay and the hepatocyte VTG induction bioassay to complex mixtures associated with endocrine effects in fish, specifically extracts of pulp mill effluent. Of the 14 pulp mill effluent extracts tested, only six showed activity in both assays, whereas the remaining eight samples showed activity in only one of the two assays. The hepatocyte VTG induction bioassay consistently showed that the pulp mill effluent extracts were antiestrogenic, which to our knowledge has not been reported in previous studies. Collectively, these results suggest that a combination of in vitro assays that depend on differing endpoints is required to identify potential xenoestrogens and to characterize their modes of action.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".