Direct quantitation of endogenous steroid sulfates in human urine by liquid chromatography‐electrospray tandem mass spectrometry
Bibliographic record
Abstract
A method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the direct quantitation of endogenous steroid sulfates has been developed to be able to evaluate these metabolites as biomarkers to detect the misuse of endogenous androgenic anabolic steroids in sports. For sample preparation, a mixed-mode solid-phase extraction was optimized to eliminate the glucuronide fraction in the washing step thus obtaining only the sulfate fraction. Chromatographic separation was optimized to achieve adequate resolution between isomers. The electrospray ionization and the product ion mass spectra of the sulfates were studied in order to obtain the most specific and selective transitions. The method was validated for quantitative purposes for 11 steroid sulfates obtaining satisfactory values for linearity, accuracy, and intra- and inter-day precision (relative standard deviation better than 16.2%). Limits of quantitation ranged between 0.5 and 2 ng/mL. Extraction recoveries for sulfate metabolites were between 90 and 94%. Matrix effect ranged from 90 to 110% showing the absence of significant ion suppression/enhancement. Samples were found to be stable after 2 freeze/thaw cycles. The applicability of the method was checked by the analysis of 75 urine samples from healthy volunteers (54 males, 37 Caucasian and 17 Asian, and 21 Caucasian females) to evaluate the concentration levels of endogenous sulfate metabolites in basal conditions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".