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Record W2471230521 · doi:10.1002/rcm.7528

Nickel in equine sports drug testing – pilot study results on urinary nickel concentrations

2016· article· en· W2471230521 on OpenAlexfundno aff
Mario Thevis, M. Machnik, Ina Schenk, Oliver Krug, Thomas Piper, Wilhelm Schänzer, Michael R. Due, Ulf Bondesson, Mikael Hedeland

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2016
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsChemistryNickelCobaltUrineInductively coupled plasma mass spectrometryDetection limitChromatographyEnvironmental chemistryNuclear chemistryMass spectrometryBiochemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.079
GPT teacher head0.356
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2016
Admission routes1
Has abstractyes

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