TCDD dysregulation of 13 AHR-target genes in rat liver
Bibliographic record
Abstract
Despite several decades of research, the complete mechanism by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other xenobiotic agonists of the aryl hydrocarbon receptor (AHR) cause toxicity remains unclear. While it has been shown that the AHR is required for all major manifestations of toxicity, the specific downstream changes involved in the development of toxic phenotypes remain unknown. Here we examine a panel of 13 genes that are AHR-regulated in many species and tissues. We profiled their hepatic mRNA abundances in two rat strains with very different sensitivities to TCDD: the TCDD-sensitive Long-Evans (Turku/AB; L-E) and the TCDD-resistant Han/Wistar (Kuopio; H/W). We evaluated doses ranging from 0 to 3000μg/kg at 19h after TCDD exposure and time points ranging from 1.5 to 384h after exposure to 100μg/kg TCDD. Twelve of 13 genes responded to TCDD in at least one strain, and seven of these showed statistically significant inter-strain differences in the time course analysis (Aldh3a1, Cyp1a2, Cyp1b1, Cyp2a1, Fmo1, Nfe2l2 and Nqo1). Cyp2s1 did not respond to TCDD in either rat strain. Five genes exhibited biphasic responses to TCDD insult (Ahrr, Aldh3a1, Cyp1b1, Nfe2l2 and Nqo1), suggesting a secondary event, such as association with additional transcriptional modulators. Of the 12 genes that responded to TCDD during the dose-response analysis, none had an ED50 equivalent to that of Cyp1a1, the most sensitive gene in this study, while nine genes responded to doses at least 10-100 fold higher, in at least one strain (Ahrr (L-E), Aldh3a1 (both), Cyp1a2 (both), Cyp1b1 (both), Cyp2a1 (L-E), Inmt (both), Nfe2l2 (L-E), Nqo1 (L-E) and Tiparp (both)). These data shed new light on the association of the AHR target genes with TCDD toxicity, and in particular the seven genes exhibiting strain-specific differences represent strong candidate mediators of Type-II toxicities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.029 | 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 teacher head, 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".