Sequence and In Vitro Function of Chicken, Ring-Necked Pheasant, and Japanese Quail AHR1 Predict In Vivo Sensitivity to Dioxins
Bibliographic record
Abstract
There are large differences in sensitivity to the toxic and biochemical effects of dioxins and dioxin-like compounds (DLCs) among vertebrates. Previously, we demonstrated that the difference in sensitivity between domestic chicken (Gallus gallus domesticus) and common tern (Sterna hirundo) to aryl hydrocarbon receptor 1 (AHR1)-dependent changes in gene expression following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is based upon the identities of the amino acids at two sites within the ligand binding domain of AHR1 (chicken--highly sensitive; Ile324_Ser380 vs common tern--250-fold less sensitive than chicken; Val325_Ala381). Here, we tested the hypotheses that (i) the sensitivity of other avian species to TCDD, 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), and 2,3,7,8-tetrachlorodibenzofuran (TCDF) is also determined by the amino acids at sites that are equivalent to sites 324 and 380 in chicken, and (ii) Ile324_Ala380 and Val324_Ser380 genotypes confer intermediate sensitivity to DLCs in birds. We compared ligand-induced transactivation function of full-length AHR1s from chicken, common tern, ring-necked pheasant (Phasianus colchicus; Ile324_Ala380) and Japanese quail (Coturnix japonica; Val324_Ala380), and three Japanese quail AHR1 mutants. The results support our hypothesis that avian species can be grouped into three general classes of sensitivity to DLCs. Both AHR1 genotype and in vitro transactivation assays predict in vivo sensitivity. Contrary to the assumption that TCDD is the most potent DLC, PeCDF was more potent than TCDD at activating Japanese quail (13- to 26-fold) and common tern (23- to 30-fold) AHR1. Our results support and expand previous in vitro and in vivo work that demonstrated ligand-dependent species differences in AHR1 affinity. The findings and methods will be of use for DLC risk assessments.
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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".