Antidepressants and their metabolites in municipal wastewater, and downstream exposure in an urban watershed
Bibliographic record
Abstract
Antidepressants are a widely prescribed group of pharmaceuticals that can be biotransformed in humans to biologically active metabolites. In the present study, the distribution of six antidepressants (venlafaxine, bupropion, fluoxetine, sertraline, citalopram, and paroxetine) and five of their metabolites was determined in a municipal wastewater treatment plant (WWTP) and at sites downstream of two WWTPs in the Grand River watershed in southern Ontario, Canada. Fathead minnows (Pimephales promelas) caged in the Grand River downstream of a WWTP were also evaluated for accumulated antidepressants. Finally, drinking water was analyzed from a treatment plant that takes its water from the Grand River 17 km downstream of a WWTP. In municipal wastewater, the antidepressant compounds present in the highest concentrations (i.e., >0.5 microg/L) were venlafaxine and its two demethylation products, O- and N-desmethyl venlafaxine. Removal rates of the target analytes in a WWTP were approximately 40%. These compounds persisted in river water samples collected at sites up to several kilometers downstream of discharges from WWTPs. Venlafaxine, citalopram, and sertraline, and demethylated metabolites were detected in fathead minnows caged 10 m below the discharge from a WWTP, but concentrations were all < microg/kg wet weight. Venlafaxine and bupropion were detected at very low (<0.005 microg/L) concentrations in untreated drinking water, but these compounds were not detected in treated drinking water. The present study illustrates that data are needed on the distribution in the aquatic environment of both the parent compound and the biologically active metabolites of pharmaceuticals.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".