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  5. Human Motion Driven Self-Powered Photodynamic System for Long-Term Autonomous Cancer Therapy

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Article
en
2020

Human Motion Driven Self-Powered Photodynamic System for Long-Term Autonomous Cancer Therapy

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en
2020
Vol 14 (7)
Vol. 14
DOI: 10.1021/acsnano.0c00675

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Zhuo Liu
Lingling Xu
Qiang Zheng
+8 more

Abstract

Long-term and low-dose photodynamic therapy for treating tumors requires a sustainable energy supply. The power source technology of batteries and wireless charging for driving a light-emitting diode (LED) may cause inconveniences during treatment. In addition, the development of telemedicine and Internet medicine put forward higher demands on treatment methods, such as better patient compliance and autonomous management. Here, we show a self-powered photodynamic therapy (s-PDT) system with two different irradiation modes that can be autonomously managed by patients. The as-fabricated s-PDT system based on a twinning structured piezoelectric nanogenerator is powered by energy harvested from body motion and realizes effective tumor tissue killing and inhibition. As demonstrated at the cellular level, the s-PDT system can significantly suppress tumor cell growth with the pulsed light stimulation mode. When the miniature LED was implanted subcutaneously in mice with transplanted tumors, the s-PDT system led to significant antitumor effects by irradiation with intermittent continuous light stimulation mode for 12 days, and an 87.46% tumor inhibition rate was obtained. This innovative s-PDT system combined with two treatment modes may provide a great opportunity to develop wearable/implantable and self-controllable devices for long-term photodynamic therapy, which would be a promising method for clinical cancer treatment.

How to cite this publication

Zhuo Liu, Lingling Xu, Qiang Zheng, Yong Kang, Bojing Shi, Dongjie Jiang, Hu Li, Xuecheng Qu, Yubo Fan, Zhong Lin Wang, Zhou Li (2020). Human Motion Driven Self-Powered Photodynamic System for Long-Term Autonomous Cancer Therapy. , 14(7), DOI: https://doi.org/10.1021/acsnano.0c00675.

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Publication Details

Type

Article

Year

2020

Authors

11

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.0c00675

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