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Record W4390743688 · doi:10.1002/dta.3638

Comparison of analytical approaches for the detection of oral testosterone undecanoate administration in men

2024· article· en· W4390743688 on OpenAlexfundno aff
Tobias Langer, Raul Nicoli, Carine Schweizer‐Grundisch, Silke Grabherr, Tiia Kuuranne, Alessandro Musenga

Bibliographic record

VenueDrug Testing and Analysis · 2024
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsUrineChemistryChromatographyTestosterone (patch)EpitestosteroneMass spectrometryUrinary systemSteroidInternal medicineMedicineHormoneBiochemistry

Abstract

fetched live from OpenAlex

For antidoping laboratories, the determination of an illicit testosterone (T) administration in urine samples remains a difficult process as it requires the determination of the exogenous origin by carbon isotope ratios (CIRs) of testosterone and its metabolites. As a complement to the urinary analysis, targeting testosterone esters (e.g. testosterone undecanoate [TU]) in serum samples by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) could represent a simpler approach compared with isotope ratio mass spectrometry (IRMS). These two approaches both lead to the direct detection of the administration of exogenous T but with a difference in effort and complexity of the analysis. To compare the detection window obtained with the two strategies, serum and the corresponding urine samples collected from an administration study with oral TU were analysed. Results showed that, at all timepoints where the intact TU was detected in serum, the CIRs of urinary steroids were also not in agreement with an endogenous origin. IRMS analysis required more effort but resulted in slightly longer detection windows than the ester analysis. Finally, this comparison study showed that, in the presence of a suspicious urinary steroid profile, the LC-MS/MS steroid esters analysis in the corresponding serum samples can be very helpful. If steroid esters are not detected, the IRMS analysis can then be conducted on the urine sample afterwards. Overall, the combination of matrices might facilitate the detection of prohibited T administration in sports, especially for athletes with naturally low T/E ratios.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.129
GPT teacher head0.357
Teacher spread0.228 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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