JOURNAL ARTICLE

Molecularly imprinted polymer for solid-phase extraction of oleanolic acid from Ligustrum lucidum fruit.

  • Published In: Journal of Chromatographic Science, 2025, v. 63, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Xu, Jianling; Wang, Wenna; Chen, Yixin; Xu, Xiaotian; Duan, Ao; Zhu, Yongyan; Zhu, Quanhong 3 of 3

Abstract

This article focuses on the synthesis and application of molecularly imprinted polymers (MIPs) for the selective extraction and enrichment of oleanolic acid (OA) from Ligustrum lucidum fruit. Using OA as the template molecule, acrylamide (AM) as the functional monomer, ethylene glycol dimethacrylate (EGDMA) as the cross-linker, and azobisisobutyronitrile (AIBN) as the initiator, MIPs were prepared via bulk polymerization and characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), Brunauer–Emmett–Teller (BET) analysis, and X-ray photoelectron spectroscopy (XPS). The MIPs demonstrated high adsorption capacity (128.32 mg/g) and were employed in a molecularly imprinted solid-phase extraction (MISPE) system, achieving a 76.0% enrichment rate of OA from crude extracts under optimized conditions. Additionally, a validated high-performance liquid chromatography (HPLC) method was established for accurate OA quantification, indicating the potential of this approach for selective separation and enrichment of OA and other triterpenoids from complex plant matrices.

Additional Information

  • Source:Journal of Chromatographic Science. 2025/03, Vol. 63, Issue 3, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:0021-9665
  • DOI:10.1093/chromsci/bmaf010
  • Accession Number:184405627
  • Copyright Statement:Copyright of Journal of Chromatographic Science is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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