Amino Acid Sequence of the Ligand-Binding Domain of the Aryl Hydrocarbon Receptor 1 Predicts Sensitivity of Wild Birds to Effects of Dioxin-Like Compounds
Bibliographic record
Abstract
The sensitivity of avian species to the toxic effects of dioxin-like compounds (DLCs) varies up to 1000-fold among species, and this variability has been associated with interspecies differences in aryl hydrocarbon receptor 1 ligand-binding domain (AHR1 LBD) sequence. We previously showed that LD(50) values, based on in ovo exposures to DLCs, were significantly correlated with in vitro EC(50) values obtained with a luciferase reporter gene (LRG) assay that measures AHR1-mediated induction of cytochrome P4501A in COS-7 cells transfected with avian AHR1 constructs. Those findings suggest that the AHR1 LBD sequence and the LRG assay can be used to predict avian species sensitivity to DLCs. In the present study, the AHR1 LBD sequences of 86 avian species were studied, and differences at amino acid sites 256, 257, 297, 324, 337, and 380 were identified. Site-directed mutagenesis, the LRG assay, and homology modeling highlighted the importance of each amino acid site in AHR1 sensitivity to 2,3,7,8-tetrachlorodibenzo-p-dioxin and other DLCs. The results of the study revealed that (1) only amino acids at sites 324 and 380 affect the sensitivity of AHR1 expression constructs of the 86 avian species to DLCs and (2) in vitro luciferase activity of AHR1 constructs containing only the LBD of the species of interest is significantly correlated (r (2) = 0.93, p < 0.0001) with in ovo toxicity data for those species. These results indicate promise for the use of AHR1 LBD amino acid sequences independently, or combined with the LRG assay, to predict avian species sensitivity to DLCs.
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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".