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Near-Infrared Emission CuInS/ZnS Quantum Dots: All-in-One Theranostic Nanomedicines with Intrinsic Fluorescence/Photoacoustic Imaging for Tumor Phototherapy
Open accessAbstract
Many theranostic nanomedicines (NMs) have been fabricated by packaging imaging and therapeutic moieties together. However, concerns about their potential architecture instability and pharmacokinetic complexity remain major obstacles to their clinical translation. Herein, we demonstrated the use of CuInS/ZnS quantum dots (ZCIS QDs) as "all-in-one" theranostic nanomedicines that possess intrinsic imaging and therapeutic capabilities within a well-defined nanostructure. ZCIS QDs were exploited for multispectral optical tomography (MSOT) imaging and synergistic PTT/PDT therapy. Due to the intrinsic fluorescence/MSOT imaging ability of the ZCIS QDs, their size-dependent distribution profiles were successfully visualized at tumor sites in vivo. Our results showed that the smaller nanomedicines (ZCIS NMs-25) have longer tumor retention times, higher tumor uptake, and deeper tumor penetration than the larger nanomedicines (ZCIS NMs-80). The ability of ZCIS QDs to mediate photoinduced tumor ablation was also explored. Our results verified that under a single 660 nm laser irradiation, the ZCIS NMs had simultaneous inherent photothermal and photodynamic effects, resulting in high therapy efficacy against tumors. In summary, the ZCIS QDs as "all-in-one" versatile nanomedicines allow high therapeutic efficacy as well as noninvasively monitoring tumor site localization profiles by imaging techniques and thus hold great potential as precision theranostic nanomedicines.
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Cites
Principles of nanoparticle design for overcoming biological barriers to drug delivery
Blanco, E., Shen, H., & Ferrari, M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3330 · Cited by 7,002
Photoacoustic tomography: In vivo imaging from organelles to organs
Wang, L. V., & Hu, S. (2012) · Science · doi:10.1126/science.1216210 · Cited by 4,331
Li, H.-J., Du, J.-Z., Liu, J., Du, X.-J., Shen, S., Zhu, Y.-H., Wang, X., Ye, X., Nie, S., & Wang, J. (2016) · ACS Nano · doi:10.1021/acsnano.6b02326 · Cited by 537
Super-Resolution Fluorescence Imaging of Telomeres Reveals TRF2-Dependent T-loop Formation
Doksani, Y., Wu, J. Y., de Lange, T., & Zhuang, X. (2013) · Cell · doi:10.1016/j.cell.2013.09.048 · Cited by 493
Cited by
Recent progress in drug delivery
Li, C., Wang, J., Wang, Y., Gao, H., Wei, G., Huang, Y., Yu, H., Gan, Y., Wang, Y., Mei, L., et al. (2019) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2019.08.003 · Cited by 818
Self-citationQi, J., Sun, C., Zebibula, A., Zhang, H., Kwok, R. T. K., Zhao, X., Xi, W., Lam, J. W. Y., Qian, J., & Tang, B. Z. (2018) · Advanced Materials · doi:10.1002/adma.201706856 · Cited by 418
Application of semiconductor quantum dots in bioimaging and biosensing
Martynenko, I. V., Litvin, A. P., Purcell-Milton, F., Baranov, A. V., Fedorov, A. V., & Gun'ko, Y. K. (2017) · Journal of Materials Chemistry B · doi:10.1039/c7tb01425b · Cited by 382
Zhang, S., Guo, W., Wei, J., Li, C., Liang, X.-J., & Yin, M. (2017) · ACS Nano · doi:10.1021/acsnano.6b08720 · Cited by 284
Self-citationXiao, W., Ruan, S., Yu, W., Wang, R., Hu, C., Liu, R., & Gao, H. (2017) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.7b00475 · Cited by 84
Metadata
- Authors
- Lv, G., Guo, W., Zhang, W., Zhang, T., Li, S., Chen, S., Eltahan, A. S., Wang, D., Wang, Y., Zhang, J., Wang, P. C., Chang, J., & Liang, X.-J.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-09-20
- Volume
- 10
- Issue
- 10
- Pages
- 9637-9645
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2497807614
- Cited by
- 256
- References
- 4
- FWCI
- 18.24
- Type
- journal article
- Language
- en
- Open access
- green
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- Lv, G., Guo, W., Zhang, W., Zhang, T., Li, S., Chen, S., Eltahan, A. S., Wang, D., Wang, Y., Zhang, J., Wang, P. C., Chang, J., & Liang, X.-J. (2016). Near-Infrared Emission CuInS/ZnS Quantum Dots: All-in-One Theranostic Nanomedicines with Intrinsic Fluorescence/Photoacoustic Imaging for Tumor Phototherapy. ACS Nano. https://doi.org/10.1021/acsnano.6b05419
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