Detection of efaproxiral (RSR13) and its metabolites in equine by liquid chromatography tandem mass spectrometry
Bibliographic record
Abstract
Efaproxiral (RSR 13) is an experimental synthetic allosteric modifier of haemoglobin (Hb) that acts by increasing the release of oxygen from Hb to the surrounding tissues. It has been shown to increase maximum oxygen uptake (VO(2max)) in a canine skeletal muscle model. The ability to increase maximal muscle oxygen uptake makes efaproxiral a potential performance-enhancing agent and is therefore prohibited by the World Anti-Doping Agency. In this study, a method for the detection and elimination of efaproxiral in equine plasma and urine after a 2.5 g intravenous administration of efaproxiral is described. Post administration plasma and urine samples were collected up to 120 h. Efaproxiral was detected up to 120 h in urine and up to 78 h in plasma. In plasma, the peak concentration was 42 µg/ml and detected at 5 min post administration. In urine, the peak concentration was 2.8 mg/ml and detected at 0-1 h post administration. A validated liquid chromatography tandem mass spectrometry method was used for the quantitation of efaproxiral in equine plasma and urine. The limit of detection of the method is 0.05 ng/ml in plasma and 0.1 ng/ml in urine. The method is highly sensitive and specific with good precision, accuracy and recovery. The manuscript also describes the systematic identification of efaproxiral metabolites detected in post administration equine urine samples. The metabolites were identified by use of enhanced mass spectra and enhanced product ion scans. Both positive and negative mode ionizations were utilized for metabolite identification and plausible fragmentation pathways were proposed for the phase 1 metabolite identified. In addition to free efaproxiral, one phase 1 metabolite and two phase 2 metabolites were identified in post administration urine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".