Sunlight Irradiation of Highly Brominated Polyphenyl Ethers Generates Polybenzofuran Products That Alter Dioxin-responsive mRNA Expression in Chicken Hepatocytes
Bibliographic record
Abstract
We report on two highly brominated polyphenyl ether flame retardants, tetradecabromo-1,4- diphenoxybenzene (TeDB-DiPhOBz) and 2,2',3,3',4,4',5,5',6,6'-decabromodiphenyl ether (BDE-209), that formed photolytic degradation products in tetrahydrofuran (THF)/hexane solvent after 21 days of natural sunlight irradiation (SI). These degradation products of SI-TeDB-DiPhOBz and SI-BDE-209 included the numerous polybrominated homologue groups of polybenzofurans and dibenzofurans, respectively. Formation of similar polybenzofuran and dibenzofuran products was also observed following a 3 month exposure of the solid powder forms of TeDB-DiPhOBz and BDE-209 to natural SI. These resulting degradation product mixtures were administered to chicken embryonic hepatocytes (CEH) to determine effects on mRNA expression levels of 27 dioxin-responsive genes. For the solvent-based SI study, equivalent concentrations of 1 or 25 μM of SI-TeDB-DiPhOBz or 1 or 10 μM of SI-BDE-209 resulted in gene expression profiles that were similar to those of the most potent dioxin-like compound, 2,3,7,8-tetrachlorodibenzo-p-dioxin. In addition, a concentration-dependent induction of CYP1A4 and CYP1A5 mRNA was observed following exposure to SI-TeDB-DiPhOBz and SI-BDE-209. Based on ECthreshold values for CYP1A4/5 mRNA expression, relative potency (ReP) values were 1 × 10(-6) and 1 × 10(-5) for SI-TeDB-DiPhOBz and SI-BDE-209, respectively. The SI TeDB-DiPhOBz and BDE-209 powder degradation product mixture also significantly induced CYP1A4 mRNA levels in CEH. Our findings clearly show that the environmental stability of TeDB-DiPhOBz and BDE-209, and possibly other highly brominated polyphenyl ethers, is of great concern from a dioxin-like degradation products and toxicity perspective.
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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) | 0.000 | 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".