4.6 Article Proceedings Paper

Electromembrane extraction of aristolochic acids: New insights in separation of bioactive ingredients of traditional Chinese medicines

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1608, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.chroma.2019.460424

关键词

Electromembrane extraction; Bioactive ingredient; Traditional Chinese medicine; Aristolochic acids; Herbal plant; Human urine

资金

  1. National Natural Science Foundation of China [21876055, 81801875, 21874050, 21677056]
  2. Fundamental Research Funds for the Central Universities in China [2017KFYXJJ021]

向作者/读者索取更多资源

Aristolochic acid (AA) I and AA II, which have been classified as carcinogenic to human and have been proven to be nephrotoxic, are bioactive ingredients of many traditional Chinese medicines (TCMs). Thus, development of an efficient approach for separation and determination of AA I and AA 11 in biological samples and herbal plants is of significance. Herein, electromembrane extraction (EME) was for the first time used to separate AA I and AA II. It is noted that also for the first time 1-decanol was discovered and used as an efficient SLM solvent for EME of acidic compounds. The proposed EME system was used to extract AA 1 and AA II from urine samples (recovery >= 68%). The approach of EME combined with LC-MS (EME-LC/MS) was evaluated using urine samples. The linear range for AA 1 and AA II was 10-1000 ng mL(-1) (R-2 >= 0.9970), and the limits of detection (LOD, S/N = 3) for AA I and AA II were 2.7 and 2.9 ng mL(-1), respectively. Finally, this EME-LC/MS approach was employed to discover AA 1 and AA II in the herbal plants. In addition, using standard addition method, AA 1 in Aristolochicaceae-Liao Asarum (ALA) and Radix Aristolochice (RA) were 0.23 and 2044.13 mu g g(-1), and AA II in ALA and RA were 0 and 338.48 mu g g(-1), respectively. The repeatability of EME-LC/MS at all cases for both urine samples and herbal plants was below 15% (RSD-value). We believe that EME would be a useful tool to isolate bioactive ingredients of TCMs from complex samples for different purposes. (C) 2019 Elsevier B.V. All rights reserved.

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