Dioxin-Dependent and Dioxin-Independent Gene Batteries: Comparison of Liver and Kidney in AHR-Null Mice
Bibliographic record
Abstract
The aryl hydrocarbon receptor (AHR) is a widely expressed ligand-dependent transcription factor that mediates cellular responses to dioxins and other planar aromatic hydrocarbons. Ahr-null mice are refractory to the toxic effects of dioxin exposure. Although some mechanistic aspects of AHR activity are well understood, the tissue specificity of AHR effects remains unclear, both during development and following administration of exogenous ligands. To address the latter issue, we defined and compared transcriptional responses to dioxin exposure in the liver and kidney of wild-type and Ahr-null adult C57BL/6J mice treated with either 2,3,7,8-tetrachlorodibenzo-p-dioxin or corn-oil vehicle. In both tissues, essentially all effects of dioxin on hepatic mRNA levels were mediated by the AHR. Although 297 genes were altered by dioxin exposure in the liver, only 17 were changed in the kidney, including a number of well-established AHR target genes. Ahr genotype had a large effect in both tissues, profoundly remodeling both the renal and hepatic transcriptomes. Surprisingly, a large number of genes were affected by Ahr genotype in both tissues, suggesting the presence of a basal AHR gene battery. Alterations of the renal transcriptome in Ahr-null animals were associated with perturbation of specific functional pathways and enrichment of specific DNA motifs. Our results demonstrate the importance of intertissue comparisons, highlight the basal role of the AHR in liver and kidney, and support a role in development or normal physiology.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".