Pharmaceuticals and personal care products: A critical review of the impacts on fish reproduction
Bibliographic record
Abstract
Research in environmental toxicology involving pharmaceuticals and personal care products (PPCPs) has increased greatly over the last 10-15 years. Much research has been focused on the endocrine-disrupting potential of PPCPs, as they relate to negative population impacts of aquatic organisms. This review assesses the current data on the reported effects of PPCPs on fish reproduction with an emphasis on fecundity, a predictor of population effects. Studies of both individual PPCPs and PPCP mixtures are presented. As the majority of individual PPCP studies reviewed demonstrate negative effects on fish fecundity, we relate these findings to detected surface water concentrations of these compounds. Very few studies involving PPCP mixtures have been conducted; however, the need for these types of studies is warranted as fish are most likely exposed to mixtures of PPCPs in the wild. In addition, laboratory and field assessments of wastewater treatment plant (WWTP) effluents, a major source of PPCPs, are reviewed. Much of the data provided from these assessments are variable and do not generally demonstrate negative impacts on reproduction, or the studies are unable to directly associate observed effects with WWTP effluents. Finally, future research considerations are outlined to provide an avenue into understanding how wild populations of fish are affected by PPCPs. These considerations are aimed at determining the adaptation potential of fish exposed to mixtures of PPCPs over multiple generations. As global use of PPCPs continually rises, the need to discern the effects of chronic exposure to PPCPs is greatly increased.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".