The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
A nanosized metal–organic framework of Fe-MIL-88NH2 as a novel peroxidase mimic used for colorimetric detection of glucose
Abstract
In this paper, a nanosized porous metal-organic framework, Fe-MIL-88NH₂, was facilely prepared with a uniform octahedral shape by the addition of acetic acid, and for the first time was demonstrated to possess intrinsic peroxidase-like activity. Kinetic analysis and electron spin resonance measurements indicated that the catalytic behavior was consistent with typical Michaelis-Menten kinetics and follows a ping-pong mechanism. As a novel peroxidase mimic material, Fe-MIL-88NH₂ shows the advantages of high catalytic efficiency, ultrahigh stability and high biocompatibility in aqueous medium compared with natural enzymes and other peroxidase nanomimetics. Here, Fe-MIL-88NH₂ was used to quickly catalyze oxidation of the peroxidase substrate 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H₂O₂ to produce a colored product, which provided a simple, sensitive and selective method for the colorimetric detection of glucose. Glucose could be linearly detected in the range from 2.0 × 10⁻⁶ to 3.0 × 10⁻⁴ M with a detection limit of 4.8 × 10⁻⁷ M, and the color variation for glucose response was also obvious by visual observation at concentrations as low as 2.0 × 10⁻⁶ M. More importantly, the colorimetric method could be successfully applied to the determination of glucose in diluted serum samples.
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Cites
Intrinsic peroxidase-like activity of ferromagnetic nanoparticles
Gao, L., Zhuang, J., Nie, L., Zhang, J., Zhang, Y., Gu, N., Wang, T., Feng, J., Yang, D., Perrett, S., et al. (2007) · Nature Nanotechnology · doi:10.1038/nnano.2007.260 · Cited by 7,483
Metal−Organic Frameworks with Functional Pores for Recognition of Small Molecules
Chen, B., Xiang, S., & Qian, G. (2010) · Accounts of Chemical Research · doi:10.1021/ar100023y · Cited by 2,033
Graphene Oxide: Intrinsic Peroxidase Catalytic Activity and Its Application to Glucose Detection
Song, Y., Qu, K., Zhao, C., Ren, J., & Qu, X. (2010) · Advanced Materials · doi:10.1002/adma.200903783 · Cited by 2,024
Potential applications of metal-organic frameworks
Kuppler, R. J., Timmons, D. J., Fang, Q.-R., Li, J.-R., Makal, T. A., Young, M. D., Yuan, D., Zhao, D., Zhuang, W., & Zhou, H.-C. (2009) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2009.05.019 · Cited by 1,659
Taylor-Pashow, K. M. L., Della Rocca, J., Xie, Z., Tran, S., & Lin, W. (2009) · Journal of the American Chemical Society · doi:10.1021/ja906198y · Cited by 1,522
Wei, H., & Wang, E. (2008) · Analytical Chemistry · doi:10.1021/ac702203f · Cited by 1,412
Jv, Y., Li, B., & Cao, R. (2010) · Chemical Communications · doi:10.1039/c0cc02698k · Cited by 936
Intrinsic peroxidase-like activity and catalase-like activity of Co3O4 nanoparticles
Mu, J., Wang, Y., Zhao, M., & Zhang, L. (2012) · Chemical Communications · doi:10.1039/c2cc17013b · Cited by 768
Au@Pt nanostructures as oxidase and peroxidase mimetics for use in immunoassays
He, W., Liu, Y., Yuan, J., Yin, J.-J., Wu, X., Hu, X., Zhang, K., Liu, J., Chen, C., Ji, Y., et al. (2011) · Biomaterials · doi:10.1016/j.biomaterials.2010.09.040 · Cited by 587
Self-citationColorimetric Detection of Urine Glucose Based ZnFe2O4 Magnetic Nanoparticles
Su, L., Feng, J., Zhou, X., Ren, C., Li, H., & Chen, X. (2012) · Analytical Chemistry · doi:10.1021/ac300939z · Cited by 503
Cited by
Nanomaterials with enzyme-like characteristics (nanozymes): next-generation artificial enzymes
Wei, H., & Wang, E. (2013) · Chemical Society Reviews · doi:10.1039/c3cs35486e · Cited by 3,779
Metadata
- Authors
- Liu, Y. L., Zhao, X. J., Yang, X. X., & Li, Y. F.
- Venue
- The Analyst
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2013
- Volume
- 138
- Issue
- 16
- Pages
- 4526
- ISSN
- 0003-2654 (ISSN-L)
- 1364-5528
- OpenAlex
- W2044770851
- Cited by
- 320
- References
- 34
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- closed
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