Effects of fluoxetine on the reproductive axis of female goldfish (<i>Carassius auratus</i>)
Bibliographic record
Abstract
We investigated the effects of fluoxetine, a selective serotonin reuptake inhibitor, on neuroendocrine function and the reproductive axis in female goldfish. Fish were given intraperitoneal injections of fluoxetine twice a week for 14 days, resulting in five injections of 5 microg fluoxetine/g body wt. We measured the monoamine neurotransmitters serotonin, dopamine, and norepinephrine in addition to their metabolites with HPLC. Homovanillic acid, a metabolite in the dopaminergic pathway, increased significantly in the hypothalamus. Plasma estradiol levels were measured by radioimmunoassay and were significantly reduced approximately threefold after fluoxetine treatment. We found that fluoxetine also significantly reduced the expression of estrogen receptor (ER)beta1 mRNA by 4-fold in both the hypothalamus and the telencephalon and ERalpha mRNA by 1.7-fold in the telencephalon. Fluoxetine had no effect on the expression of ERbeta2 mRNA in the hypothalamus or telencephalon. Microarray analysis identified isotocin, a neuropeptide that stimulates reproductive behavior in fish, as a candidate gene affected by fluoxetine treatment. Real-time RT-PCR verified that isotocin mRNA was downregulated approximately sixfold in the hypothalamus and fivefold in the telencephalon. Intraperitoneal injection of isotocin (1 microg/g) increased plasma estradiol, providing a potential link between changes in isotocin gene expression and decreased circulating estrogen in fluoxetine-injected fish. Our results reveal targets of serotonergic modulation in the neuroendocrine brain and indicate that fluoxetine has the potential to affect sex hormones and modulate genes involved in reproductive function and behavior in the brain of female goldfish. We discuss these findings in the context of endocrine disruption because fluoxetine has been detected in the environment.
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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".