Nickel in equine sports drug testing – pilot study results on urinary nickel concentrations
Bibliographic record
Abstract
RATIONALE: The issue of illicit performance enhancement spans human and animal sport in presumably equal measure, with prohibited substances and methods of doping conveying both ways. Due to the proven capability of unbound ionic cobalt (Co(2) (+) ) to stimulate erythropoiesis in humans, both human and equine anti-doping regulations have listed cobalt as a banned substance, and in particular in horse drug testing, thresholds for cobalt concentrations applying to plasma and urine have been suggested or established. Recent reports about the finding of substantial amounts of undeclared nickel in arguably licit performance- and recovery-supporting products raised the question whether the ionic species of this transition metal (Ni(2) (+) ), which exhibits similar prolyl hydroxylase inhibiting properties to Co(2) (+) , has been considered as a substitute for cobalt in doping regimens. METHODS: Therefore, a pilot study with 200 routine post-competition doping control horse urine samples collected from animals participating in equestrian, gallop, and trotting in Europe was conducted to provide a first dataset on equine urinary Ni(2) (+) concentrations. All specimens were analyzed by conventional inductively coupled plasma mass spectrometry (ICP-MS) to yield quantitative data for soluble nickel. RESULTS: Concentrations ranging from below the assay's limit of quantification (LOQ, 0.5 ng/mL) up to 33.4 ng/mL with a mean value (± standard deviation) of 6.1 (±5.1) ng/mL were determined for the total nickel content. CONCLUSIONS: In horses, nickel is considered a micronutrient and feed supplements containing nickel are available; hence, follow-up studies are deemed warranted to consolidate potential future threshold levels concerning urine and blood nickel concentrations in horses using larger sets of samples for both matrices and to provide in-depth insights by conducting elimination studies with soluble Ni(2) (+) -salt species. Copyright © 2016 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".