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Issue 38, 2017
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Selective separation of xanthones and saponins from the rhizomes of Anemarrhena asphodeloides by modulating the density of surface charges in C18-bonded stationary phases

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Abstract

A rapid and robust separation method based on the positively charged reversed-phase (PGRP) stationary phase was developed for selective separation of saponins and xanthones from the rhizomes of Anemarrhena asphodeloides (A. asphodeloides). In this work, the chromatographic performances of three PGRP stationary phases with different surface positive charge densities were systematically evaluated by studying hydrophobicity, effects of pH and buffer concentration of the mobile phase, ion-exchange capacity, etc. The PGRP stationary phase exhibited reversed-phase/anion-exchange mixed-mode properties. Then the retention behaviors of xanthones were investigated. A good retention of xanthones was obtained at high pH and xanthones were easily eluted at low pH. The pH is like an on–off switch on the PGRP stationary phase that controls the retention of xanthones. Finally, this PGRP material was successfully applied to the selective separation of saponins and xanthones from A. asphodeloides. The result demonstrated that neutral and ionic compounds, such as xanthones and saponins from the rhizomes of A. asphodeloides, were separated selectively by modulating both the density of surface charges in the PGRP stationary phase and the pH of the mobile phase.

Graphical abstract: Selective separation of xanthones and saponins from the rhizomes of Anemarrhena asphodeloides by modulating the density of surface charges in C18-bonded stationary phases

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Publication details

The article was received on 08 Jul 2017, accepted on 23 Aug 2017 and first published on 23 Aug 2017


Article type: Paper
DOI: 10.1039/C7AY01667K
Citation: Anal. Methods, 2017,9, 5604-5610
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    Selective separation of xanthones and saponins from the rhizomes of Anemarrhena asphodeloides by modulating the density of surface charges in C18-bonded stationary phases

    J. Cai, H. Xin, L. Cheng, Z. Guo, J. Feng, Q. Fu, Y. Jin and X. Liang, Anal. Methods, 2017, 9, 5604
    DOI: 10.1039/C7AY01667K

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