Application of Statistical Data Analysis Methods to Test the Degradation of Urine Samples for Doping Control Purposes

被引：2
|
作者：
Podolskiy, I. I. [1 ]
Mochalova, E. S. [2 ]
Temerdashev, A. Z. [3 ]
Gashimova, E. M. [3 ]
机构：
[1] Bruker Ltd, Moscow 119017, Russia
[2] Moscow MV Lomonosov State Univ, Natl Antidoping Lab Inst, Moscow 105005, Russia
[3] Kuban State Univ, Krasnodar 350040, Russia
来源：
JOURNAL OF ANALYTICAL CHEMISTRY | 2021年 / 76卷 / 06期
基金：
俄罗斯科学基金会;
关键词：
steroids; doping; urine degradation; GC-MS; chemometrics; discriminant analysis; neural networks; ANABOLIC-STEROIDS; STABILIZATION;
D O I：
10.1134/S1061934821060071
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
The results of applying various statistical methods of analysis to the processing of a large array of data obtained using a validated method of gas chromatographic analysis with tandem mass-spectrometric detection are considered. The findings are an integral part of a human steroid profile, and they are used as characteristics in doping control laboratories. The applicability of statistical methods of analysis to detect the degradation of urine samples in the course of storage based on chemometric approaches is considered; the factors that are most influenced during the degradation of urine samples are identified, and the capabilities and limitations of various statistical methods in operations with large data arrays are demonstrated.
引用
收藏
页码：761 / 771
页数：11
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