Toxicity of human pharmaceuticals and personal care products to benthic invertebrates
Bibliographic record
Abstract
Despite concerns about potential risks associated with the presence of pharmaceuticals and personal care products (PPCPs) in the environment, few toxicological data address the effects of these compounds. In aquatic systems, which often represent the final repository for PPCPs, increasing toxicological information regarding aquatic biota is improving our capacity to assess potential risks. However, responses of key biota, such as benthic invertebrates, have not been investigated as widely. In the present study, we examined the toxicity of four PPCPs -- the lipid regulator atorvastatin (ATO), the antiepileptic drug carbamazepine (CBZ), the synthetic hormone 17alpha-ethinylestradiol (EE(2)), and the antimicrobial triclosan (TCS) -- to the midge Chironomus tentans and the freshwater amphipod Hyalella azteca in 10-d waterborne exposures. The toxicity of the four compounds varied between 0.20 and 47.3 mg/L (median lethal concentration), with a relative toxicity ranking of TCS > EE(2) > ATO > CBZ. Hyalella azteca was more sensitive than C. tentans to these compounds. The toxicity data were used in a hazard quotient approach to evaluate the risk posed by the four PPCPs to benthic invertebrates and other aquatic organisms. For each compound, a hazard quotient was calculated by dividing the lowest toxicity value by the highest exposure value found in the literature, to which an uncertainty factor was applied. With hazard quotients of 3.55 to 11.5, we conclude that potential risks exist toward benthic invertebrates for the toxicity of TCS and CBZ and that further investigations of these compounds are required to characterize more completely the risks to benthic organisms. In contrast, our data also indicate that considering the low concentrations currently detected in the environment, ATO and EE(2) pose negligible risks to benthic invertebrates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".