Toxicity of nonylphenol on the cnidarian <i>Hydra attenuata</i> and environmental risk assessment
Bibliographic record
Abstract
Alkylphenols and their derivatives, alkylphenol polyethoxylates (APEs), are synthetic chemicals of concern owing to their endocrine properties. Nonylphenol (NP) is a critical APE metabolite because of its recalcitrance to biodegradation, toxicity, and ability to bio-accumulate in aquatic organisms. Studies of NP effects in vertebrates demonstrated estrogenic disrupting properties in fish, birds, reptiles, and mammal cells in which NP displaces the natural estrogen from its receptor. Less is known on its toxicity toward invertebrates. Effects on reproduction have been reported, but toxicity on development has been poorly documented thus far. We investigated NP toxicity on survival and regeneration of the freshwater coelenterate Hydra attenuata. Hydra is known for its regenerative capacity and its sensitivity to chemical pollution. It has been used for over 20 years to screen for teratogenicity of chemicals (Johnson et al. (1982) Teratog Carcinog Mutagen 2:263-276). Our results showed that hydra appeared as one of the most sensitive species to acute and chronic toxicity of NP compared to several freshwater invertebrates. Regeneration was disrupted at NP concentrations lower than those affecting survival. Toxicity thresholds of NP for aquatic vertebrates and invertebrates are also reported and discussed in the context of environmental risk assessment and of water quality objectives recommended for surface waters in industrialized countries. NP levels have decreased during the last decade because of a voluntary agreement of surfactant producers and users. At present, concentrations of NP found in surface waters are far below 1 microg/L in Europe, but can reach several microg/L when wastewater treatment plant inefficiency occurs.
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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".