Issue 25, 2024

Fabrication of a β-CD-functionalized magnetic microporous organic network for effective enrichment and detection of fluoroquinolone antibiotics in water samples

Abstract

Fluoroquinolone (FQ) antibiotics, one of the leading environmental pollutants, have ecotoxic effects that can accumulate through ecosystems and harm human health. The determination of FQs is still difficult due to the complex matrix, many interfering factors, and low concentration. Hence, a magnetic microporous organic network (MON) composite denoted as Fe3O4@MON-NH2@CM-β-CD with excellent FQ adsorption performance was prepared by β-CD covalent modification of a MON. Based on the existence of π–π packing, hydrophobic interaction, and hydrogen bonding between Fe3O4@MON-NH2@CM-β-CD and FQs, a new magnetic solid phase extraction (MSPE) method for the enrichment of FQs was developed. Under optimized MSPE conditions, five FQs were detected by HPLC-UV with good linearity (R2 ≥ 0.9989) in the range of 0.02–1 μg mL−1, and detection limits (S/N = 3) in the range of 0.0014–0.0023 μg mL−1. The satisfactory recoveries ranged from 93.1 to 116.2% with RSDs lower than 8.39% when applied to actual environmental water samples. These results revealed that Fe3O4@MON-NH2@CM-β-CD as an adsorbent for MSPE had excellent performance for FQ extraction from real samples, and the MON material types were expanded through the functionalization of MONs, which would have great potential for further application in various analytical methods.

Graphical abstract: Fabrication of a β-CD-functionalized magnetic microporous organic network for effective enrichment and detection of fluoroquinolone antibiotics in water samples

Supplementary files

Article information

Article type
Paper
Submitted
10 Feb 2024
Accepted
23 May 2024
First published
24 May 2024

Anal. Methods, 2024,16, 4104-4115

Fabrication of a β-CD-functionalized magnetic microporous organic network for effective enrichment and detection of fluoroquinolone antibiotics in water samples

H. Cui, Q. Tian, Y. Liu, L. Liu, X. Li, J. Nie and R. Zhang, Anal. Methods, 2024, 16, 4104 DOI: 10.1039/D4AY00245H

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