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Stanozolol-N-glucuronide metabolites in human urine samples as suitable targets in terms of routine anti-doping analysis

Permanent lenke
https://hdl.handle.net/10037/22804
DOI
https://doi.org/10.1002/dta.3109
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article.pdf (1.333Mb)
Publisert versjon (PDF)
Dato
2021-06-05
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Göschl, Lorenz; Gmeiner, Günter; Gärtner, Peter; Stadler, Georg; Enev, Valentin; Thevis, Mario; Schänzer, Wilhelm; Guddat, Sven; Forsdahl, Guro
Sammendrag
The exogenous anabolic-androgenic steroid (AAS) stanozolol stays one of the most detected substances in professional sports. Its detection is a fundamental part of doping analysis, and the analysis of this steroid has been intensively investigated for a long time. This contribution to the detection of stanozolol doping describes for the first time the unambiguous proof for the existence of 17-epistanozolol-1′N-glucuronide and 17-epistanozolol-2′N-glucuronide in stanozolol-positive human urine samples due to the access to high-quality reference standards. Examination of excretion study samples shows large detection windows for the phase-II metabolites stanozolol-1′N-glucuronide and 17-epistanozolol-1′N-glucuronide up to 12 days and respectively up to almost 28 days. In addition, we present appropriate validation parameters for the analysis of these metabolites using a fully automatic method online solid-phase extraction (SPE) method already published before. Limits of identification (LOIs) as low as 100 pg/ml and other validation parameters like accuracy, precision, sensitivity, robustness, and linearity are given.
Er en del av
Göschl, L. (2022). Discovery and detection of phase-II metabolites of exogenous steroids in anti-doping analysis. (Doctoral thesis). https://hdl.handle.net/10037/24767
Forlag
Wiley
Sitering
Göschl L, Gmeiner G, Gärtner P, Stadler, Enev, Thevis M, Schänzer W, Guddat, Forsdahl G. Stanozolol-N-glucuronide metabolites in human urine samples as suitable targets in terms of routine anti-doping analysis. Drug Testing and Analysis. 2021;13(9):1668-1677
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Copyright 2021 The Author(s)

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