Profiling Endogenous Serum Estrogen and Estrogen-Glucuronides by Liquid Chromatography−Tandem Mass Spectrometry
Bibliographic record
Abstract
Estrogens, namely, 17beta-estradiol (E(2)), are conjugated to glucuronides (G), and this metabolic conversion is part of their tissular-concentration control-mechanism. This inactivation process has been observed, in addition to the liver, in several estrogen-dependent tissues and the resulting polar metabolites are detected in circulation. We developed and validated a highly sensitive and specific mass spectrometry-based method to directly measure estrogen-G serum levels. The method uses deuterated standards but does not involve enzymatic hydrolysis, a major improvement over previous techniques. Estrone (E(1)), E(1)-sulfate, E(2), the 3-G of E(1), E(2), 2-methoxy-E(1) (2-MeOE(1)) and 2-methoxy-E(2) (2-MeOE(2)), and the 17-G of E(2) were measured in serum of 19 premenopausal and 10 postmenopausal healthy women. Two extractions, solid-phase and liquid-liquid, were performed to isolate the estrogens. Estrogens were then quantified by mass spectrometry in the negative MRM ion mode using an API3200 spectrometer with a turbo ionspray source. The method selectively measured estrogen glucuronides with sensitivity > or = 5 pg/mL, accuracy 90-111%, and reproducibility (CV = 1.4-13.3%). The method is applicable between 5 and 1000 pg/mL. For the ovarian follicular phase, the major metabolite found was E(1)-3G, with E(2)-3G and 2-MeOE(1)-3G found in lesser amounts (54, 10.4, and 7.8 pg/mL, respectively) These concentrations are 2.6- to 3-fold greater than found for luteal-phase estrogens. The concentrations of E(2)-17G and 2-MeOE(2)-3G were usually less than the limit of quantification. In serum of postmenopausal women, E(1)-3G was the most abundant estrogen found (30.9 pg/mL). Our method profiles estrogens and estrogen-glucuronides and may represent a new tool to identify biomarkers in hormone-dependent diseases.
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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 | 0.000 | 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 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".