Estradiol, Estrone and Ethinyl Estradiol Metabolism Studied by High Resolution LC-MS/MS Using Stable Isotope Labeling and Trapping of Reactive Metabolites
Bibliographic record
Abstract
Biotransformation reactions that xenobiotics undergo during their metabolism are crucial for their proper excretion from the body, but can also be a source of toxicity, especially in the case of reactive metabolite formation. Unstable, reactive metabolites are capable of covalent binding to proteins, and have often been linked to liver damage and other undesired side effects. A common technique to assess the formation of reactive metabolites employs trapping them in vitro with glutathione and characterizing the resulting adducts by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Some endogenous compounds, however, can interfere with xenobiotic metabolites of interest, making the analysis more difficult. This study demonstrates the usefulness of isotope-labeled compounds to detect and elucidate the structures of both stable metabolites and trapped adducts of three estrogen analogs using an untargeted LC-MS/MS workflow. The metabolism of estradiol, estrone and ethinyl estradiol was investigated. Unlabeled and deuterated versions of these three compounds were incubated with human or rat liver microsomes in the presence of two different trapping agents, namely glutathione and N-acetylcysteine. The detection of closely eluting deuterated peaks allowed us to confirm the formation of several known metabolites, as well as many previously uncharacterized ones. The structure of each adduct was elucidated by the detailed analysis of high-resolution MS/MS spectra for elucidating fragmentation pathways with accurate mass measurements. The use of isotopic labeling was crucial in helping confirm many metabolites and adduct structures, as well as removing endogenous interferences.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".