Reduced anxiety is associated with the accumulation of six serotonin reuptake inhibitors in wastewater treatment effluent exposed goldfish Carassius auratus
Bibliographic record
Abstract
Pharmaceuticals and personal care products (PPCPs) have been found in wastewater treatment plant (WWTP) effluents and their recipient watersheds. To assess the potential of WWTP effluents to alter fish behaviour, we caged male goldfish (Carassius auratus) for 21-days at three sites along a contamination gradient downstream from a WWTP which discharges into Cootes Paradise Marsh, on the western tip of Lake Ontario. We also included a fourth caging site as an external reference site within Lake Ontario at the Jordan Harbour Conservation Area. We then measured concentrations of PPCPs and monoamine neurotransmitters in caged goldfish plasma, and conducted behavioural assays measuring activity, startle response, and feeding. We detected fifteen different PPCPs in goldfish plasma including six serotonin reuptake inhibitors (amitriptyline, citalopram, fluoxetine/norfluoxetine, sertraline, venlafaxine, and diphenhydramine). Plasma concentrations of serotonin were significantly greater in plasma of fish caged closer to the WWTP effluent outfall site. The fish caged near and downstream of the WWTP effluent were bolder, more exploratory, and more active overall than fish caged at the reference site. Taken together, our results suggest that fish downstream of WWTPs are accumulating PPCPs at levels sufficient to alter neurotransmitter concentrations and to also impair ecologically-relevant behaviours.
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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".