Effects of in ovo exposure of white leghorn chicken, common pheasant, and Japanese quail to 2,3,7,8-tetrachlorodibenzo-<i>p</i>-dioxin and two chlorinated dibenzofurans on CYP1A induction
Bibliographic record
Abstract
In birds, activation of the aryl hydrocarbon receptor (AhR) by some polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) results in induction of cytochrome P4501A (CYP1A) expression. This response has been useful for predicting relative sensitivity of birds to dioxin-like compounds. To further investigate species-sensitivity to dioxins and dioxin-like compounds induction of cytochrome P450 1A4 and 1A5 (CYP1A4 and CYP1A5) mRNA and ethoxyresorufin O-deethylase (EROD) activity were quantified in liver of posthatch white leghorn chicken, common pheasant, and Japanese quail exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), or 2,3,7,8-tetrachlorodibenzofuran (TCDF) via air cell injection. The rank-order of sensitivity of TCDD- and TCDF-exposed birds, based on CYP1A, was chicken>pheasant>quail. Based on CYP1A5 mRNA expression and EROD induction, the order of sensitivity of PeCDF-exposed birds was identical to that for TCDD and TCDF. However, based on CYP1A4 mRNA expression the rank-order was pheasant>chicken>quail. When comparing the potency of the three compounds in each species, based on CYP1A4 mRNA expression, TCDD was the most potent compound in chicken. However, PeCDF was equally potent to TCDD in quail and was more potent than TCDD in pheasant. These results suggest that quantitative real-time polymerase chain reaction (Q-PCR) analysis of CYP1A expression, particularly CYP1A4 mRNA expression, may be a more sensitive biomarker of exposure than analysis of EROD induction, especially in less responsive avian species. Based on these findings future risk assessments should consider the sensitivity of the species inhabiting a site and the congeners of concern that are present.
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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".