pH-responsive magnetic graphene oxide composite as an adsorbent with high affinity for rapid capture of nucleosides

A novel pH-responsive magnetic graphene oxide composite (MGO@PEI-BA) is proposed for the first time as an adsorbent for the rapid capture and detection of nucleosides (cytidine, uridine, guanosine, and adenosine). The morphology, structure, and magnetic properties of the composite were evaluated usi...

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Published in:Mikrochimica acta (1966) Vol. 190; no. 9; p. 365
Main Authors: Yin, Huawen, Yuan, Yue, Xin, Ling, Hang, Qian, Zhao, Longshan, Qin, Feng, Xiong, Zhili
Format: Journal Article
Language:English
Published: Vienna Springer Vienna 01-09-2023
Springer
Springer Nature B.V
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Summary:A novel pH-responsive magnetic graphene oxide composite (MGO@PEI-BA) is proposed for the first time as an adsorbent for the rapid capture and detection of nucleosides (cytidine, uridine, guanosine, and adenosine). The morphology, structure, and magnetic properties of the composite were evaluated using various characterization techniques. The results indicated that the composite was successfully fabricated. A series of parameters that affect extraction and elution were optimized through one-factor-at-a-time and Box-Behnken design of response surface methodology (BBD-RSM). The unique layered structures and easily accessible active sites of the composite facilitated molecular transport, resulting in instantaneous equilibrium of nucleosides adsorption within 5 min. Based on this study, a magnetic dispersive micro-solid-phase extraction (MD-μ-SPE) method assisted by the MGO@PEI-BA was developed in combination with UHPLC-UV analysis for the determination of nucleosides in rat urine. Under the optimum conditions, a wide linear range (10–2000 ng mL −1 ), good linearity ( r > 0.99), low detection limits (1–3 ng mL −1 ), low relative standard deviations (RSDs ≤ 3.9%), and satisfactory recoveries (82.7–96.3%) were achieved. These results demonstrate that the MGO@PEI-BA is an excellent adsorbent for extracting nucleosides from biological samples. Graphical Abstract
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ISSN:0026-3672
1436-5073
DOI:10.1007/s00604-023-05945-2