Liquid chromatographic–mass spectrometric analysis of glucuronide‐conjugated anabolic steroid metabolites: method validation and interlaboratory comparison
Bibliographic record
Abstract
Liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) method for simultaneous and direct detection of 12 glucuronide-conjugated anabolic androgenic steroid (AAS) metabolites in human urine is described. The compounds selected were the main metabolites detected in human urine after dosing of the most widely abused AAS in sports, e.g. methandienone, methenolone, methyltestosterone, nandrolone and testosterone, and certain deuterium-labeled analogs of these metabolites. Sample preparation and the LC-ESI-MS/MS method were optimized, validated, and the overall process was implemented and the results between seven laboratories were compared. All the metabolites were extracted simultaneously by solid-phase extraction (SPE) and analyzed by LC-ESI-MS/MS with positive ionization mode and multiple reaction monitoring (MRM). Recovery of the SPE for the AAS glucuronides was 89-100% and ten out of twelve compounds had detection limits in the range of 1-10 ng/ml in urine. The results for inter/intraday repeatability were satisfactory and the interlaboratory comparison with authentic urine samples demonstrated the ease of method transfer from one instrument setup to another. When equivalent triple quadrupole analyzers were employed the overall performance was independent from instrument manufacturer, electrospray ionisation (ESI) or atmospheric pressure chemical ionization (APCI) and liquid chromatohraphic (LC) column, whereas major differences were encountered when changing from one analyzer type to another, especially in the analysis of those AAS glucuronides ionized mainly as adducts.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".