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Issue 55, 2016, Issue in Progress
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Novel green and red autofluorescent protein nanoparticles for cell imaging and in vivo biodegradation imaging and modeling

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Abstract

Albumins are widely used in bioengineering due to their low-cost, good biocompatibility and biodegradability. Herein we report that cross-linked bovine serum albumin (BSA) forms a suspension of novel fluorescent nanoparticles with an average size of ∼40 nm, exhibiting strong green/red autofluorescence. UV-vis spectra, in conjunction with fluorescence emission spectra, suggest that three classes of fluorescent compounds presumably formed during the preparation. The size distribution and surface morphology of the autofluorescent BSA nanoparticles were characterized using various advanced techniques. After removal of excessive cross-linking agent through dialysis, the autofluorescent BSA nanoparticles were first demonstrated for cell bioimaging application using 293FT human kidney cell line. Its good biocompatibility and low cytotoxicity were further validated by an in vitro cytotoxicity assay and an in vivo histological study. The strong red autofluorescence of the BSA nanoparticles was further exploited in the realization of convenient and non-invasive tracking/modeling of its in vivo degradation based on real-time fluorescence imaging. A mathematical model was proposed and in good agreement with the experimental results. This study indicates that the as-prepared functional, biocompatible and biodegradable autofluorescent protein nanoparticles are suitable for a range of biomedical applications.

Graphical abstract: Novel green and red autofluorescent protein nanoparticles for cell imaging and in vivo biodegradation imaging and modeling

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Publication details

The article was received on 14 Mar 2016, accepted on 12 May 2016 and first published on 23 May 2016


Article type: Paper
DOI: 10.1039/C6RA06783B
RSC Adv., 2016,6, 50091-50099

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    Novel green and red autofluorescent protein nanoparticles for cell imaging and in vivo biodegradation imaging and modeling

    X. Ma, D. Hargrove, Q. Dong, D. Song, J. Chen, S. Wang, X. Lu, Y. K. Cho, T. Fan and Y. Lei, RSC Adv., 2016, 6, 50091
    DOI: 10.1039/C6RA06783B

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