Modulation of the Hepatic CYP1A1 System in the Marine Fish <i>Gobius niger,</i> Exposed to Xenobiotic Compounds
Bibliographic record
Abstract
Anthropogenic chemicals in the aquatic environment are known to cause reproductive disturbances in vertebrate and invertebrate organisms by interfering with the endocrine systems. Large efforts have recently been devoted to dissect the mechanisms of action of xenobiotics in aquatic species, with the ultimate aim of detecting and controlling the effects of chemical exposure on the aquatic ecosystem and humans. In the present paper, males of a marine species, the black goby (Gobius niger), were treated with estrogenic and dioxin-like compounds commonly discharged into the environment from industry, agriculture, and urban waste such as nonylphenol (NP) and beta-naphthoflavone (beta-NF). Their effects were compared with those induced by estradiol (E2), analyzing the expression of biomarkers commonly used in ecotoxicological studies such as vitellogenin (VTG) and cytochrome P4501A1. The treatment with NP induced the synthesis of the female specific protein VTG in males, showing its estrogenic activity. NP and E2 lowered cytochrome P4501A1 basal levels while beta-NF determined a significant rise of its expression. The detoxification pathway was investigated, and the most relevant finding of this paper was the evidence that cytochrome P4501A1 inhibition by estrogen and estrogen-like compounds is mediated through the activation of the aryl hydrocarbon receptor repressor.
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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".