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Record W2129789808 · doi:10.1002/rcm.6965

Detection and characterization of triamcinolone acetonide metabolites in human urine by liquid chromatography/tandem mass spectrometry after intramuscular administration

2014· article· en· W2129789808 on OpenAlexfundno aff
Xavier Matabosch, Óscar J. Pozo, Esther Papaseit, Magı́ Farré, Josep Marcos, Jordi Segura, Rosa Ventura

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2014
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersInstituto de Salud Carlos IIIDepartament d'Innovació, Universitats i Empresa, Generalitat de CatalunyaGeneralitat de CatalunyaWorld Anti-Doping Agency
KeywordsChemistryChromatographyTriamcinolone acetonideTandem mass spectrometryMass spectrometryUrineElectrospray ionizationLiquid chromatography–mass spectrometrySelected reaction monitoringBiochemistry

Abstract

fetched live from OpenAlex

RATIONALE: Glucocorticosteroids are prohibited in sports when used by systemic administrations (e.g. intramuscular, IM), whereas they are allowed using other ways of administration. Strategies to discriminate between administrations routes have to be developed by doping control laboratories. For this reason, the metabolism of triamcinolone acetonide (TA), one of the most used glucocorticosteroids, was studied using liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS). METHODS: Urine samples obtained after IM administration of TA were analyzed using two sample treatments: (a) hydrolysis with β-glucuronidase enzymes and liquid-liquid extraction under alkaline conditions, and (b) liquid-liquid extraction under acidic conditions. The extracts were analyzed by LC/MS/MS. RESULTS: TA, commercially available metabolites (6β-hydroxytriamcinolone acetonide, 6β-OH-TA, and triamcinolone), and their C20-reduced derivatives showed characteristic fragmentation behavior. Besides common product ions and neutral losses for corticosteroids containing fluorine, additional characteristic neutral losses (58 Da, loss of acetone; 44 Da, loss of acetaldehyde) were observed in positive electrospray ionization. Based on that behavior, two complementary approaches were applied to detect TA metabolites: (a) open detection by precursor ion and neutral loss scan methods and (b) targeted detection by selected reaction monitoring methods (SRM) containing theoretical ion transitions of the potential metabolites. Two main compounds, TA and 6β-OH-TA, and nine minor potential metabolites, were detected by open screening methods. Using SRM, two additional metabolites were detected. Some of the metabolites were characterized using reference standards and, for the rest of metabolites, feasible structures were proposed based on mass spectrometric data. CONCLUSIONS: Metabolites resulting from hydroxylation in C-6, oxidation of the 11-hydroxyl group, reduction of the Δ(4) double bond and oxidation of the side chain were detected. Some of them have not been previously described. Excretion profiles of the detected metabolites after IM administration are presented.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.013
GPT teacher head0.270
Teacher spread0.257 · 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 designBench or experimental
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

Citations22
Published2014
Admission routes1
Has abstractyes

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