Quality evaluation of Semen Platycladi samples from different origins by Internal Extractive Electrospray Ionization Mass Spectrometry

Abstract

Semen Platycladi is a widely used natural product in Chinese medicine with pharmacological effects such as anti-arteriosclerosis, sleep improvement, antioxidant and anti-inflammatory. The quality of Semen Platycladi is fundamentally important for its therapeutic use. However, tedious sample pretreatment required by the currently available methods poses great challenge to the high throughput analysis and evaluation of the quality of Semen Platycladi. Here we established a high-throughput analysis platform for evaluating the quality of various Semen Platycladi samples using Internal Extractive Electrospray Ionization Mass Spectrometry (iEESI-MS). The fatty acids including linoleic acid, linolenic acid, arachidonic acid, stearic acid and palmitic acid, known as one of the major ingredients in Semen Platycladi, were directly quantified in the range of 0.001-100.00 μg/mg (R2 > 0.995) using raw samples of different origins, with the limits of detection of 0.02 - 0.04 μg/mg, the limits of quantification of 0.07 - 0.14 μg/mg, the recovery rate of 89.5 - 102.0%, and the relative standard deviation of repeatability (n=9) of 0.51% - 3.88%, respectively. The data revealed that these five fatty acids were the main differential compounds, which could be used to differentiate the samples originated from Hebei, Shandong and Henan province. The experimental results demonstrated that the iEESI-MS could be a useful platform for fast quality analysis of Semen Platycladi, and thus showing advanced applications in natural product analysis, drug discovery and related fields.

Supplementary files

Article information

Article type
Paper
Submitted
15 Oct 2024
Accepted
12 Jan 2025
First published
13 Jan 2025

Anal. Methods, 2025, Accepted Manuscript

Quality evaluation of Semen Platycladi samples from different origins by Internal Extractive Electrospray Ionization Mass Spectrometry

N. Wang, S. Xie, P. Liu, L. Wang, C. Zhong, J. Yu, M. Qin and H. Chen, Anal. Methods, 2025, Accepted Manuscript , DOI: 10.1039/D4AY01881H

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