Equol Induces Gonadal Intersex in Japanese Medaka (<i>Oryzias latipes</i>) at Environmentally Relevant Concentrations: Comparison with 17β-Estradiol
Bibliographic record
Abstract
Equol is present in the aquatic environment via livestock waste and runoff discharge; however, it remains unclear whether it can induce gonadal intersex in fish at environmentally relevant concentrations. This study evaluated adverse effects of equol on gonadal development by exposing transgenic Japanese medaka (Oryzias latipes) from hatching for 100 days. Equol induced intersex incidence in male medaka in a dose-dependent manner, and the benchmark dose corresponding to 10% intersex incidence (BMD10) was 11.5 ng/L (95% confidence interval (CI): 5.8 ng/L, 19.8 ng/L), which was comparable to the required dose of 17β-estradiol (E2β) (9.0 ng/L, 95% CI: 6.6 ng/L, 11.0 ng/L). Equol exposure resulted in reduced plasma 11-ketotestosterone (11-KT) concentrations in male medaka at 1.3 ng/L, while reduced plasma 11-KT concentrations were observed at a relatively high concentration (6.4 ng/L) of E2β. Such antiandrogenic property could partly explain the comparable potency of equol with that of E2β to induce intersex at relatively low concentrations, although the binding affinity of equol to medaka estrogen receptor α (EC50 939.4 nM) was 230-fold lower than that (4.07 nM) of E2β. This study for the first time demonstrated that equol could induce intersex in medaka fish at environmentally relevant concentrations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".