Comprehensive Profiling of Free and Conjugated Estrogens by Capillary Electrophoresis–Time of Flight/Mass Spectrometry
Bibliographic record
Abstract
The biological activity of estrogens is tightly regulated by regioselective phase I/II metabolic transformations that are critical to human health. Current methods for analysis of urinary estrogens are limited by complicated sample pretreatment and/or inadequate specificity for free estrogens and their glucuronide/sulfate conjugates that vary widely in their intrinsic polarity. In this work, direct speciation of intact estrogen conjugates and their regioisomers is demonstrated using capillary electrophoresis-time-of-flight/mass spectrometry (CE-TOF/MS) when using an alkaline buffer system with negative ion mode detection. This method allows for resolution of weakly acidic native estrogens, anionic estrogen conjugates and their positional isomers without significant matrix-induced ion suppression effects in human urine. Identification of unknown estrogen metabolites using CE-TOF/MS is supported by accurate mass together with their characteristic relative migration times, which can be predicted based on two intrinsic physicochemical properties of an ion. CE-TOF/MS offers a promising strategy for comprehensive profiling of estrogens and other classes of steroid conjugates that is needed for deeper insight into the etiology and treatment of chronic disorders associated with impaired estrogen metabolism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| 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".