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  5. Fabrication of A Molecularly Imprinted Monolithic Column Via the Epitope Approach For the Selective Capillary Microextraction of Neuropeptides In Human Plasma

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Article
English
2022

Fabrication of A Molecularly Imprinted Monolithic Column Via the Epitope Approach For the Selective Capillary Microextraction of Neuropeptides In Human Plasma

0 Datasets

0 Files

English
2022
SSRN Electronic Journal
DOI: 10.2139/ssrn.4016296

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Herman Terryn
Herman Terryn

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Xiaoyun Lei
Ting Huang
Xiaoping Wu
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Abstract

A novel molecularly imprinted monolithic (MIM) column was designed and fabricated using the epitope approach and used for the selective capillary microextraction (CME) of neuropeptides neurotensin (NT) and neuromedin N (NmN). The MIMs were synthesized in a capillary by thermally initiated polymerization of the functional monomer (methacrylic acid (MAA)), in the presence of a dummy template (Pro-Tyr-Ile-Leu (PYIL)), a crosslinker and porogens. The resulting monoliths were characterized by scanning electron microscopy, pore size distribution measurement, and Fourier transform infrared spectroscopy. The MIMs were used to enrich NT and NmN from human plasma prior to HPLC-UV analysis. The imprinted monolith showed high dynamic binding capacity (rebinding equilibrium at 40~50 min) and selectivity (imprinting factor of 5.7~13.4) towards its target peptides, as well as an excellent maximum adsorption capacity of 245~711 mg mL -1 . Low detection limits of 0.62 and 1.20 nM, and satisfactory recoveries (82.5-98.8%) were obtained for NT and NmN, respectively. The proposed MIM-CME/HPLC-UV method may be used as an effective tool for the highly efficient and specific analysis of neuropeptides in biological fluids.

How to cite this publication

Xiaoyun Lei, Ting Huang, Xiaoping Wu, Debby Mangelings, Ann Van Eeckhaut, Jana Bongaerts, Herman Terryn, Yvan Vander Heyden (2022). Fabrication of A Molecularly Imprinted Monolithic Column Via the Epitope Approach For the Selective Capillary Microextraction of Neuropeptides In Human Plasma. SSRN Electronic Journal, DOI: 10.2139/ssrn.4016296.

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Publication Details

Type

Article

Year

2022

Authors

8

Datasets

0

Total Files

0

Language

English

Journal

SSRN Electronic Journal

DOI

10.2139/ssrn.4016296

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