A facile and sensitive magnetic relaxation sensing strategy based on the conversion of Fe 3+ ions to Prussian blue precipitates for the detection of alkaline phosphatase and ascorbic acid oxidase
Herein, a novel magnetic relaxation sensing strategy based on the change in Fe content has been proposed by utilizing the conversion of Fe ions to Prussian blue (PB) precipitates. Compared with the common detection approach based on the valence state change of Fe ions, our strategy can cause a large...
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Veröffentlicht in: | Talanta (Oxford) 2023-08, Vol.260, p.124579 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Herein, a novel magnetic relaxation sensing strategy based on the change in Fe
content has been proposed by utilizing the conversion of Fe
ions to Prussian blue (PB) precipitates. Compared with the common detection approach based on the valence state change of Fe
ions, our strategy can cause a larger change in the relaxation time of water protons and higher detection sensitivity since PB precipitate can induce a larger change in the Fe
ion concentration and has a weaker effect on the relaxation process of water protons relative to Fe
ions. Then, we employ alkaline phosphatase (ALP) as a model target to verify the feasibility and detection performance of the as-proposed strategy. Actually, ascorbic acid (AA) generated from the ALP-catalyzed L-ascorbyl-2-phosphate hydrolysis reaction can reduce potassium ferricyanide into potassium ferrocyanide, and potassium ferrocyanide reacts with Fe
to form PB precipitates, leading to a higher relaxation time. Under optimum conditions, the method for ALP detection has a wide linear range from 5 to 230 mU/mL, and the detection limit is 0.28 mU/mL, sufficiently demonstrating the feasibility and satisfactory analysis performance of this strategy, which opens up a new path for the construction of magnetic relaxation sensors. Furthermore, this strategy has also been successfully applied to ascorbic acid oxidase detection, suggesting its expansibility in magnetic relaxation detection. |
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ISSN: | 1873-3573 |