A Validated Liquid Chromatography-Mass Spectrometry Method for the Detection and Quantification of Oxidative Metabolites of 2,2',4,4'-Tetrabromodiphenyl Ether in Rat Hepatic Microsomes
Bibliographic record
Abstract
In the present study, we developed and validated an analytical method using ultra performance liquid chromatography-mass spectrometry (UPLC/MS) for the quantitative determination of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) metabolism by rat hepatic microsomes. BDE-47 is a brominated flame retardant that was widely used in a variety of consumer products and has subsequently been identified as a ubiquitous environmental contaminant. Hydroxy-bromodiphenyl ethers (OH-BDEs) were isolated from rat hepatic microsomes by liquid-liquid extraction. Chromatographic separation was achieved by UPLC on a C18 column with gradient elution using a mobile phase consisting of methanol and water, each containing 0.1% formic acid, at a flow rate of 0.2 mL/min. Detection and quantification were performed using a mass spectrometer in single ion recording mode with negative electrospray ionization. The UPLC/MS method was validated for linearity, limit of quantification (LOQ), accuracy, precision and recovery. The weighted calibration curves (1/X2) were linear over a concentration range of 5 - 250 nM with LOQ values between 5 nM and 50 nM for the individual OH-BDEs. Intra- and inter- day accuracy (%DEV) and precision (%RSD) values ranged from –11.7% to 9.5% and 5.9% to 16.5%, respectively. Recovery values of 70% to 90% were obtained for all OH-BDEs. The validated method allowed us to successfully analyze metabolite formation following incubation of BDE-47 with hepatic microsomes prepared from phenobarbital-treated rats. Results demonstrate that the UPLC/MS method has sufficient sensitivity and reproducibility to fully characterize the in vitro metabolism of BDE-47 and possibly other PBDEs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".