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基于氧化石墨烯的分子印迹共价有机框架用于同时精确识别胆汁酸代谢物的设计与应用

Design and application of graphene oxide-based molecularly imprinted covalent organic framework for simultaneous and precise recognition of bile acid metabolites.

作者信息

Yuan Yue, Xue Tianyi, Ren Mengxin, Liu Yanzhu, Song Zhexue, Xiong Zhili, Qin Feng

机构信息

School of Pharmacy, Shenyang Pharmaceutical University, New Tech Development Zone, No. 26 Huatuo Street, High &Liaoning Province, 117004, Benxi, China.

出版信息

Mikrochim Acta. 2025 Mar 31;192(4):271. doi: 10.1007/s00604-025-07120-1.

Abstract

In this study a bile acid (BA)-imprinted covalent organic framework (COF) was constructed via Schiff base reactions, which integrated the advantages of both inherent structural stability of COF and exceptional selectivity of molecular imprinting technology. Besides, it was found that the addition of graphene oxide (GO) effectively increased the dispersibility of nanoparticles, ultimately resulting in a GO-based molecularly imprinted COF (GO@MICOF). The GO@MICOF was identified with the characteristics of excellent mass transfer performance (20.09 mg g), specific surface area (152.35 m g), selectivity (IFs = 2.4), and regeneration ability (n ≥ 10). By coupling the GO@MICOF-based pretreatment method with ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis, sensitive and accurate validation results (LOQs, 0.01-2.5 µmol L; extraction efficiency, 81.1-118.9%) were obtained. Notably, the application of the proposed pretreatment techniques to metabolomics analysis holds great significance for the precision of metabolomics results. Sixteen BA metabolites were successfully quantified in rat liver and fecal samples, and some potential biomarkers and related metabolic pathways associated with postmenopausal osteoporosis had been identified. Therefore, the integrated analysis strategy has significant advantages in purifying complex biological samples and has great application prospects in targeted metabolomics research.

摘要

在本研究中,通过席夫碱反应构建了一种胆汁酸(BA)印迹共价有机框架(COF),其整合了COF固有的结构稳定性和分子印迹技术出色的选择性这两者的优势。此外,发现添加氧化石墨烯(GO)可有效提高纳米颗粒的分散性,最终得到基于GO的分子印迹COF(GO@MICOF)。GO@MICOF具有出色的传质性能(20.09 mg g)、比表面积(152.35 m g)、选择性(IFs = 2.4)和再生能力(n≥10)等特性。通过将基于GO@MICOF的预处理方法与超高效液相色谱-串联质谱(UHPLC-MS/MS)分析相结合,获得了灵敏且准确的验证结果(定量下限,0.01 - 2.5 µmol L;提取效率,81.1 - 118.9%)。值得注意的是,所提出的预处理技术应用于代谢组学分析对代谢组学结果的准确性具有重要意义。在大鼠肝脏和粪便样本中成功定量了16种BA代谢物,并鉴定了一些与绝经后骨质疏松症相关的潜在生物标志物和相关代谢途径。因此,该综合分析策略在纯化复杂生物样品方面具有显著优势,在靶向代谢组学研究中具有广阔的应用前景。

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