Detection and confirmation of 60 anabolic and androgenic steroids in equine plasma by liquid chromatography‐tandem mass spectrometry with instant library searching
Bibliographic record
Abstract
In 2008, Pennsylvania (PA) became the first State in the USA to ban and enforce the ban on the use of anabolic and androgenic steroids (AAS) in equine athletes by using plasma for analysis. To enforce the ban, a rapid and high-throughput method for analysis of 60 AAS in equine plasma was developed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Analytes were recovered from plasma by liquid-liquid extraction (LLE) using methyl tert-butyl ether, separated on a reversed-phase C₁₈ column and analyzed by electrospray ionization mass spectrometry. Multiple-reaction monitoring (MRM) scan was employed for screening. When the MRM signal of an analyte exceeded 1000 counts per second (cps), information-dependent acquisition (IDA) triggered generation of an enhanced product ion (EPI) scan of the analyte. A library for the analytes was simultaneously established using the EPI spectrum. Unambiguous identification of any of the 60 AAS in a test sample was based on both the presence of MRM response within the correct retention time (t(R)) window and a qualitative match between EPI spectrum of the test sample and that of the reference drug standard stored in the library. Total analysis time was 7 min. The limit of detection (LOD) and limit of confirmation (LOC) for most of the analytes were 0.01-2 ng/mL and 0.1-10 ng/mL, respectively. Recovery of the analytes from plasma by LLE was 74-138%. The method was successfully verified and is routinely used in the screening of post-race equine plasma samples for the presence of these 60 AAS. The method is rapid, sensitive, reproducible, and reliable.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".