Key Amino Acids in the Aryl Hydrocarbon Receptor Predict Dioxin Sensitivity in Avian Species
Bibliographic record
Abstract
Dioxin-like compounds are toxic to most vertebrates, but significant differences in sensitivity exist among species. A recent study suggests that the amino acid residues corresponding to Ile324 and Ser380 in the chicken aryl hydrocarbon receptor 1 (AHR1) are important determinants of differential biochemical responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in chickens and common terns. Here, we investigate whether the identity of these amino acid residues can predict embryonic sensitivity to dioxin-like compounds in a wide range of birds. AHR1 sequences were determined in species for which sensitivity data were available. Of all the species surveyed, chickens were unique in having the Ile/Ser genotype and were also the most sensitive to dioxin-like compounds. Turkeys, ring-necked pheasants, and Eastern bluebirds (intermediate Ile/Ala genotype) were less sensitive than chickens but more sensitive than American kestrels, common terns, double-crested cormorants, Japanese quail, herring gulls, or ducks (Val/ Ala genotype). Our work suggests that key amino acids in the AHR1 ligand binding domain are predictive of broad categories of dioxin sensitivity in avian species. Given the large degree of variation in species sensitivity and the paucity of species-specific toxicity data, a genetic screen based on these findings could substantially improve risk assessment for dioxin-like compounds in wild birds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".