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Supported liquid extraction coupled to gas chromatography-selective mass spectrometric scan modes for serum steroid profiling

Authors
Moon, Ju-YeonLee, Hye SukKim, Jun HoLee, Jin HyupChoi, Man Ho
Issue Date
11-12월-2018
Publisher
ELSEVIER SCIENCE BV
Keywords
Steroids; SLE; GC-MS; Serum; Mouse
Citation
ANALYTICA CHIMICA ACTA, v.1037, pp.281 - 292
Indexed
SCIE
SCOPUS
Journal Title
ANALYTICA CHIMICA ACTA
Volume
1037
Start Page
281
End Page
292
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/71212
DOI
10.1016/j.aca.2018.02.059
ISSN
0003-2670
Abstract
Although, steroid profiling is being applied in clinical and biochemical studies, improvement of the technique is still needed for accurate quantification of steroids in case of limited biological sample volumes. To improve analytical sensitivity and selectivity in comparison to that of conventional methods, a method that comprises supported liquid extraction (SLE) and gas chromatography-mass spectrometry with a combination of selected-reaction and selected-ion monitoring modes (GC-SRM/SIM-MS) was developed. Here, this combination of SLE purification with GC-MS method was optimized with 37 different types of steroids and the results were compared to a solid-phase extraction (SPE) method. The devised assay led to an increase in extraction efficiency with the good chromatographic selectivity through a single extraction step. The limits of quantification of the serum steroids, ranged from 0.2 to 5 ngmL(-1), except for cholesterol (0.2 mgmL(-1)), and the correlation coefficients for calibration curves were higher than 0.99. The precision and accuracy were 1.4%-10.5% and 82.7%-115.3%, respectively. The overall recoveries of 30 steroids ranged from 62.1% to 104.3%, while that of 7 sterols was 44.7%-75.7%. Then, this validated method was applied to monitor the serum steroid levels of mice, which showed significant sex and age dependent metabolic patterns. This technique can be used to evaluate the metabolic changes occurring in animal models as well as in clinical patients. (C) 2018 Elsevier B.V. All rights reserved.
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