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磁性混合半胶束固相萃取的平台构建与萃取机理研究。

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction.

机构信息

Department of Analytical Chemistry, China Pharmaceutical University, Nanjing 210009, China.

Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, China Pharmaceutical University, Nanjing 210009, China.

出版信息

Sci Rep. 2016 Dec 7;6:38106. doi: 10.1038/srep38106.

Abstract

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What's more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples.

摘要

简单、准确且高通量的预处理方法将有助于大规模研究复杂样品中的痕量分析。磁性混合半胶束固相萃取有潜力成为生物、环境和临床研究中关键的预处理方法。然而,缺乏实验可预测性和萃取机制的不明确性限制了这种有前途的方法的发展。在此,本工作试图使用磁性混合半胶束固相萃取为从复杂样品中萃取痕量分析物建立基于理论的实验设计。我们选择了三类和六亚类化合物进行萃取机制的系统比较研究,首次全面说明了不同力(疏水相互作用、π-π 堆积相互作用、氢键相互作用、静电相互作用)的作用。此外,还总结了支持材料、表面活性剂和样品基质的应用指南。本研究中建立的萃取机制和平台有望在理论基础的实验设计下,为从环境、生物和临床样品中萃取痕量分析物提供可预见和高效的预处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52ba/5141489/35aed38d5f8b/srep38106-f1.jpg

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