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Record W2749991754 · doi:10.1002/dta.2293

Steroid profile and IRMS analysis of musk administration for doping control

2017· article· en· W2749991754 on OpenAlexfundno aff
Jingzhu Wang, Yi He, Xin Liu, Zhiyong Yang, Wenning Yang

Bibliographic record

VenueDrug Testing and Analysis · 2017
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsChemistryPharmacologyMedicine

Abstract

fetched live from OpenAlex

Musk, the dried secretion of the musk pod (sac) of adult male musk deer, has been used as traditional Chinese Medicine (TCM) in China and south‐east Asian countries for thousands of years. Due to the anabolic steroid component in this TCM, musk preparations have been included in the list of medical products containing prohibited substances employed for doping by the State Food and Drug Administration of China. The application of musk pod formulation was claimed to be responsible for some adverse analytical findings (AAFs) in the 2011 FIFA Women's World Cup. Our preliminary study has suggested that musk ingestion did not lead to AAFs of doping control with the single dosage of 100 mg. However, the influences of musk administration in large and multi dosage are still unclear. The aim of this study is to further investigate the influences of musk administration for doping control. Wild and domestic deer musk samples were collected. The concentrations and δ 13 C‐values of steroids in musk were analyzed. In an excretion study, 200 and 100 mg of wild and domestic deer musk samples were administrated by 29 subjects, respectively. Fluctuations in steroid profile could be observed, and the ratio of 5α‐androstane‐3α,17β‐diol to 5β‐androstane‐3α,17β‐diol was more sensitive than other parameters. In the IRMS test, the ∆Δδ 13 C‐value between endogenous reference compound and etiocholanolone was a sensitive parameter, and AAFs were obtained. It is the first time to confirm with excretion study that musk administration could lead to positive result of doping control. Copyright © 2017 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.318
Teacher spread0.281 · 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 teacher head, 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
Published2017
Admission routes1
Has abstractyes

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