Please use this identifier to cite or link to this item: https://doi.org/10.1002/advs.202001831
Title: Controllable Assembly of Upconversion Nanoparticles Enhanced Tumor Cell Penetration and Killing Efficiency
Authors: Zhang, Z.
Rahmat, J.N. 
Mahendran, Ratha
Zhang, Y. 
Keywords: clusters
nanoparticle assembly
photodynamic therapy
tumor cell penetration
upconversion
Issue Date: 2020
Publisher: John Wiley and Sons Inc
Citation: Zhang, Z., Rahmat, J.N., Mahendran, Ratha, Zhang, Y. (2020). Controllable Assembly of Upconversion Nanoparticles Enhanced Tumor Cell Penetration and Killing Efficiency. Advanced Science 7 (24) : 2001831. ScholarBank@NUS Repository. https://doi.org/10.1002/advs.202001831
Rights: Attribution 4.0 International
Abstract: The use of upconversion nanoparticles (UCNPs) for treating deep-seated cancers and large tumors has recently been gaining momentum. Conventional approaches for loading photosensitizers (PS) to UCNPs using noncovalent physical adsorption and covalent conjugation had been previously described. However, these methods are time-consuming and require extra modification steps. Incorporating PS loading during the controlled UCNPs assembly process is seldom reported. In this study, an amphiphilic copolymer, poly(styrene-co-maleic anhydride), is used to instruct UCNPs assembly formations into well-controlled UCNPs clusters of various sizes, and the gap zones formed between individual UCNPs can be used to encapsulate PS. This nanostructure production process results in a considerably simpler and reliable method to load PS and other compounds. Also, after considering factors such as PS loading quantity, penetration in 3D bladder tumor organoids, and singlet oxygen production, the small UCNPs clusters displayed superior cell killing efficacy compared to single and big sized clusters. Therefore, these UCNPs clusters with different sizes could facilitate a clear and deep understanding of nanoparticle-based delivery platform systems for cell killing and may pave a new way for other fields of UCNPs based applications. © 2020 The Authors. Published by Wiley-VCH GmbH
Source Title: Advanced Science
URI: https://scholarbank.nus.edu.sg/handle/10635/199517
ISSN: 2198-3844
DOI: 10.1002/advs.202001831
Rights: Attribution 4.0 International
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