Fast screening of 170 doping substances in pastes by ultra-high performance liquid chromatography-high resolution mass spectrometry method
Objective To develop a detection method with ultra-high performance liquid chromatogra-phy-high resolution mass spectrometry(UPLC-HRMS) for fast screening of doping substances in pastes,so as to strengthen the drug-borne doping risk prevention system.Methods The paste samples were removed the covering film and extracted by using tert-butyl methyl ether and anhydrous ethanol,respectively.The extracts were combined and blown dry under nitrogen flow at 40 ℃,and methanol was used to dissolve the residues,which were then filtered and analyzed with the Thermo Vaniquish-Q Exactive Plus.Then,3 μL of the solution was injected into and separated by the Agilent ZORBAX-Eclipse C18 column (2.1 × 100 mm,1.8 μm),and the gradient elution was performed with 10 mM ammonium formate (containing 0.1％ formic acid,pH3.5) and acetonitrile as mobile phase.The 170 kinds of doping substances were detected in positive ion electrospray (ESI+) and negative ion electro-spray(ESI-) respectively under Full Mass/data-dependent mass spectrometry(Full MS/ddMS2) mode.Re-sults The results showed that the method had good selectivity and samples were stable within 48 h af-ter pretreatment.The detection limit(LOD) of 92 doping substances were about 3 ng/g,while that of another 31 and 47 ones was about 6 ng/g and 30 ng/g,respectively.In this study,among 10 paste samples,4 were tested positive for strychnine,and 3 were positive for higenamine and ephedrine,re-spectively.Conclusion A fast screening method for 170 kinds of doping substances in 9 categories is developed by using ultra-high performance liquid chromatography with high resolution mass spectrome-try in this study.Such method proves to be simple,sensitive and reliable,which is suitable for fast screening of doping substances in pastes.
pastedoping substancesultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS)fast screening
NETL
NSTL
万方数据
