Estrogen-like Effects in Male Goldfish Co-exposed to Fluoxetine and 17 Alpha-Ethinylestradiol
Bibliographic record
Abstract
The antidepressant fluoxetine (FLX) and the synthetic estrogen, 17 alpha-ethinylestradiol (EE2), are present in municipal sewage discharges. To better understand possible interactions between them, male goldfish were exposed to an ethanol control or to nominal concentrations of FLX (0.54 μg/L) and EE2 (5 ng/L) alone and in combination for 14 days. Real-time reverse-transcription polymerase chain reaction was used to assess effects on hepatic gene expression and liquid chromatography tandem mass spectrometry to analyze the plasma proteome. The results showed an increase in estrogen receptor alpha (esr1) and vitellogenin (vtg) gene expression by 1.9-2.4-fold in the FLX and EE2 groups, but this did not reach statistical significance. In contrast, co-exposure up regulated esr1 and vtg gene expression by 5.5- and 5.3-fold, respectively. Fluoxetine and EE2 alone did not affect estrogen receptor beta (esr2), but the co-exposure down regulated esr2 expression by 50%. There was a significant increase in the number of plasma proteins that were related to endocrine system disorders in the FLX and FLX plus EE2 groups. The level of VTG protein was increased in the plasma from goldfish exposed to EE2, FLX, and FLX plus EE2. Our study demonstrates that low concentrations of FLX and EE2 in a simple mixture produce strong estrogen-like effects in the male goldfish.
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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".