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Wet NH3-Triggered NH2-MIL-125(Ti) Structural Switch for Visible Fluorescence Immunoassay Impregnated on Paper
Abstract
High Resolution Image Download MS PowerPoint Slide This work has looked to explore an innovative and powerful visible fluorescence immunoassay method through wet NH 3 -triggered structural change of NH 2 -MIL-125(Ti) impregnated on paper for the detection of carcinoembryonic antigen (CEA). Gold nanoparticles heavily functionalized with glutamate dehydrogenase (GDH) and secondary antibody were used for generation of wet NH 3 with a sandwiched immunoassay format. Paper-based analytical device (PAD) coated with NH 2 -MIL-125(Ti) exhibited good visible fluorescence intensity through wet NH 3 -triggeried structural change with high accuracy and reproducibility. Moreover, NH 2 -MIL-125(Ti)-based PAD displayed two visual modes of fluorescence color and physical color with the naked eye and allowed the detection of CEA at a concentration as low as 0.041 ng mL –1 . Importantly, the PAD-based assay provides promise for use in the mass production of miniaturized devices and opens new opportunities for protein diagnostics and biosecurity.
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Cited by
Recent advances in isolation and detection of exosomal microRNAs related to Alzheimer's disease
Pishbin, E., Sadri, F., Dehghan, A., Kiani, M. J., Hashemi, N., Zare, I., Mousavi, P., & Rahi, A. (2023) · Environmental Research · doi:10.1016/j.envres.2023.115705 · Cited by 25
Metadata
- Authors
- Lv, S., Tang, Y., Zhang, K., & Tang, D.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-11-21
- Volume
- 90
- Issue
- 24
- Pages
- 14121-14125
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2901980767
- Cited by
- 311
- References
- 0
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
