Aryl Hydrocarbon Receptor Activation Mediates Acute Lethality and Developmental Toxicity of Polychlorinated Diphenyl Ethers in Vertebrates: Mechanistic Insights and Implications for Toxicity Equivalency Factor Frameworks
Bibliographic record
Abstract
The toxicological mechanism(s) of polychlorinated diphenyl ethers (PCDEs) in vertebrates remains unresolved. To test the hypothesis that PCDE-induced acute lethality and developmental toxicity are mediated by aryl hydrocarbon receptor (AHR) activation, wild-type, Tg(cyp1a:gfp) transgenic, and Ahr2-null zebrafish were exposed to 11 PCDE congeners commonly detected in the environment. Compared to wild-type zebrafish, where Ahr2 activation was confirmed by robust GFP induction in Tg(cyp1a:gfp) larvae, Ahr2-null larvae exhibited significantly reduced mortality and malformation percentages (e.g., 68.7–78.8% and 48.3–97.2% lower for three highly potent congeners CDE 15, 37, and 118, respectively), demonstrating Ahr2 as the primary mediator of PCDE-induced toxicity. Furthermore, complementary in vitro species-specific luciferase reporter gene (LRG) assays revealed significant dioxin-like activities of PCDEs in zebrafish, avian (chicken, pheasant, quail), and rat models, with interspecies potency variations of up to 27,000-fold. Notably, some PCDEs exhibited relative potencies comparable to or exceeding those of known dioxin-like compounds, including HO-/MeO-polybrominated diphenyl ethers, polychlorinated diphenyl sulfides, and several highly halogenated dibenzo- p -dioxins and dibenzofurans. Overall, these findings indicate that AHR activation serves as the primary molecular mechanism underlying the toxicity of PCDEs in vertebrates and provide critical data for ecological risk assessment. Given their structural similarity to dioxins and significant bioaccumulation potential, PCDEs should be considered for inclusion in global toxicity equivalency factor frameworks.
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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".