Doping control study of AICAR in post‐race urine and plasma samples from horses
Bibliographic record
Abstract
Acadesine, 5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside, commonly known as AICAR, is a naturally occurring adenosine monophosphate-activated protein kinase (AMPK) activator in many mammals, including humans and horses. AICAR has attracted considerable attention recently in the field of doping control because of a study showing the enhancement of endurance performance in unexercised or untrained mice, resulting in the term 'exercise pill'. Its use has been classified as gene doping by the World Anti-Doping Agency (WADA), and since it is endogenous, it may only be possible to control deliberate administration of AICAR to racehorses after establishment of an appropriate threshold. Herein we report our studies of AICAR in post-race equine urine and plasma samples including statistical studies of AICAR concentrations determined from 1,470 urine samples collected from thoroughbreds and standardbreds and analyzed in Australia, France, and Hong Kong. Quantification methods in equine urine and plasma using liquid chromatography-mass spectrometry were developed by the laboratories in each country. An exchange of spiked urine and plasma samples between the three countries was conducted, confirming no significant differences in the methods. However, the concentration of AICAR in plasma was found to increase upon haemolysis of whole blood samples, impeding the establishment of a suitable threshold in equine plasma. A possible urine screening cut-off at 600 ng/mL for the control of AICAR in racehorses could be considered for adoption. Application of the proposed screening cut-off to urine samples collected after intravenous administration of a small dose (2 g) of AICAR to a mare yielded a short detection time of approximately 4.5 h. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".