Oxidative Metabolism of BDE-99 by Human Liver Microsomes: Predominant Role of CYP2B6
Bibliographic record
Abstract
Hydroxylated polybrominated diphenyl ethers (PBDEs) have been found in human serum, suggesting that they are formed by in vivo oxidative metabolism of PBDEs. However, the biotransformation of 2,2',4,4',5-pentabromodiphenyl ether (BDE-99), a major PBDE detected in human tissue and environmental samples, is poorly understood. In the present study, the oxidative metabolism of BDE-99 was assessed using pooled and single-donor human liver microsomes, a panel of human recombinant cytochrome P450 (CYP) enzymes, and CYP-specific antibodies. Hydroxylated metabolites were quantified using a liquid chromatography/tandem mass spectrometry-based method. In total, 10 hydroxylated metabolites of BDE-99 were produced by human liver microsomes. Six metabolites were identified as 2,4,5-tribromophenol (2,4,5-TBP), 4-OH-BDE-90, 5'-OH-BDE-99, 6'-OH-BDE-99, 4'-OH-BDE-101, and 2-OH-BDE-123 using authentic standards. Three monohydroxy- and one dihydroxy-pentabrominated metabolites were unidentified. Rates of formation of the three major metabolites (2,4,5-TBP, 5'-OH-BDE-99, and 4'-OH-BDE-101) by human liver microsomes ranged from 24.4 to 44.8 pmol/min/mg protein. Additional experiments demonstrated that the dihydroxylated metabolite was a primary metabolite of BDE-99 and was not produced by hydroxylation of a monohydroxy metabolite. Among the panel of recombinant CYP enzymes tested, formation of all 10 hydroxylated metabolites was catalyzed solely by CYP2B6. A combined approach using antibodies to CYP2B6 and single-donor liver microsomes expressing a wide range of CYP2B6 levels confirmed that CYP2B6 was responsible for the biotransformation of BDE-99. Collectively, the results show that the oxidative metabolism of BDE-99 by human liver microsomes is catalyzed solely by CYP2B6 and is an important determinant of the toxicity and bioaccumulation of BDE-99 in humans.
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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 | 0.001 |
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; 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".