Authors
Mingjin Yang, Meiyun He, Weian DU, Pengfei Mei, Xuelian Cheng, Xin Liu, Yuesen Shi, Hao Jin, Yiling Hu, Meixin He, Ling Chen, Chao Liu
Published in
Fa yi xue za zhi. Volume 42. Issue 3. Pages 261-268. Jun 25, 2026.
Abstract
To establish a liquid chromatography-tandem mass spectrometry (LC-MS/MS)method based on enzymatic digestion for the rapid qualitative and quantitative detection of drugs in hair.
The enzymatic digestion parameters for etomidate, ketamine, methamphetamine, and codeine, including dithiothreitol (DTT) concentration, proteinase K concentration, incubation temperature and digestion time were optimized using controlled-variable experiments. After digestion, hair samples were filtered through a 0.22 μm membrane and separated on a C18 column with a gradient elution using 0.1% formic acid in water and 0.1% formic acid in acetonitrile and analyzed using electrospray ionization (ESI) in multiple reaction monitoring (MRM) mode. After validation, the method was applied to 155 drug-related hair samples and compared with the cryogenic wet-grinding method.
Etomidate, ketamine, methamphetamine, and codeine in hair samples all showed good linearity with their respective linear ranges (R2>0.998 0), with limits of detection (LOD) of 0.005-0.010 ng/mg and limits of quantification (LOQ) of 0.02-0.04 ng/mg. Matrix effects ranged from -12.09% to 8.23%, while the relative standard deviations of intra-day precision and inter-day precision were 2.56%-10.37% and 5.50%-15.11%, respectively. Average recoveries (88.97%-104.05%) met analytical requirements. Results from drug-related hair samples suggested good consistency between enzymatic digestion and cryogenic grinding pretreatment method, while enzymatic digestion demonstrated higher extraction amounts for codeine than cryogenic grinding pretreatment method.
The established method is simple to operate, highly sensitive, and reproducible, making it suitable for high-throughput hair drug analysis, providing an efficient and reliable analytical method for forensic identification.
PMID:
42732987
Bibliographic data and abstract were imported from PubMed on 14 Sep 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 6
- Comments 0