Incidence of jaw lesions and activity and gene expression of hepatic P4501A enzymes in mink (<i>Mustela vison</i>) exposed to dietary 2,3,7,8-tetrachlorodibenzo-<i>p</i>-dioxin, 2,3,7,8-tetrachlorodibenzofuran, and 2,3,4,7,8-pentachlorodibenzofuran
Bibliographic record
Abstract
This study assessed the effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), and 2,3,7,8 tetrachlorodibenzofuran (TCDF) on the incidence of jaw lesions and on hepatic cytochrome P4501A (CYP1A) endpoints in mink (Mustela vison). Adult female mink were assigned randomly to one of 13 dietary treatments (control and four increasing doses of TCDD, PeCDF, or TCDF) and provided spiked feed for approximately 150 d (60 d prior to breeding through weaning of offspring at 42 d post-parturition). Offspring were maintained on their respective diets for an additional 150 d. Activity of hepatic CYP1A enzymes in adult and juvenile mink exposed to TCDD, PeCDF, or TCDD was generally greater compared with controls, but changes in other CYP1A endpoints were less consistent. Histopathology of the mandible and maxilla of juvenile mink suggested a dose-related increase in the incidence of jaw lesions. The dietary effective doses (ED) for jaw lesions in 50% of the population (ED50) were estimated to be 6.6, 14, and 149 ng/kg body weight (bw)/d for TCDD, PeCDF, and TCDF, respectively. The relative potencies of PeCDF and TCDF compared with TCDD based on ED10, ED20, and ED50 values ranged from 0.5 to 1.9 and 0.04 to 0.09, respectively. These values are within an order of magnitude of the World Health Organization toxic equivalency factor (TEF(WHO)) values of 0.3 and 0.1 for PeCDF and TCDF, respectively.
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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 | 0.001 |
| 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".