A fish bioassay to evaluate the toxicity associated with the ingestion of benzo[<i>a</i>]pyrene-contaminated benthic prey
Bibliographic record
Abstract
A bioassay was developed to assess the toxic effects of ingested prey contaminated by polycyclic aromatic hydrocarbons (PAHs) using the teleost Fundulus heteroclitus as a predator and the polychaete Nereis virens as a benthic vector. Ten groups of nine male adult Fundulus were exposed for 21 d to 10 different diets of Nereis contaminated with benzo[a]pyrene (BaP) by spiking dead Nereis with BaP (spiked Nereis [SN] diets, 0-26 microg of BaP per gram dry wt) or by exposing living Nereis to a diet, to sediments, or to both contaminated with BaP (exposed Nereis [EN] diets, 0-16 microg/g dry wt). Another group was exposed to commercial fish food, used as reference diet. Condition and prevalence of histopathological changes were not affected. Exposure to the SN diets containing at least 3.5 microg of BaP per gram dry weight caused an induction of ethoxyresorufin-O-deethylase activity in the intestine but not in the liver. In contrast, fish exposed to the highest doses (> or = 13.4 microg of BaP per gram dry wt) had increased cellular proliferation rate in the liver but not in the intestine. Quantifiable levels of free BaP tetrol-like metabolites were detected in the bile of fish exposed to diets containing more than 6.8 microg/g dry weight of BaP, and exhibited a dose-response relationship in fish exposed to SN diets. For a similar dose of BaP, EN and SN diets had similar effects. Thus, the BaP metabolic products that could have been produced in Nereis apparently did not contribute to the biomarkers responses. This bioassay can be applied to a variety of prey contaminated naturally or experimentally with PAHs. The present study supports the use of intestinal biomarkers, in addition to hepatic biomarkers, in environmental monitoring to assess the impact of dietary exposure to PAHs.
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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) | 0.001 | 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".