Photodynamic Graphene Quantum Dot: Reduction Condition Regulated Photoactivity and Size Dependent Efficacy
Source abstract
Abstract
Prequenching and selective activation of photosensitizer (PS) are highly desired in photodynamic therapy (PDT) to avoid off-target effect due to nonspecific activation and poor targeting selectivity of PS. In this study, nanographene materials as a unique π-conjugated planar system for electronic transfer were employed as the robust platform for temporarily quenching of PS. Photosensitizer chlorin e6 (Ce6) was integrated onto planar structure of graphene quantum dot (GQD) or graphene oxide (GO) via a reduction cleavable disulfide linker. The formed hybrid nanosystem displayed considerable fluorescence quenching and slight phototoxicity, even under the condition of light irradiation, while the photoactivity of PS could be selectively recovered in the presence of the reducing agent. Compared with graphene oxide system with larger size (around 200 nm), GQD nanosystem exhibited significantly improved tumor accumulation via enhanced permeation and retention effect (EPR effect). The in vivo study demonstrated extremely effective suppression of tumor growth for the group treated with the GQD nanosystem with cleavable linker, revealing the promising application of the presented novel strategy.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Graphene and Nanomaterials Applications · Carbon and Quantum Dots Applications · Nanoplatforms for cancer theranostics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shanghai East Hospital, The Institute for Biomedical Engineering & Nano Science (iNANO), Tongji University School of Medicine, Shanghai, People’s Republic of China
Funding
Ministry of Education of the People's Republic of China · Ministry of Science and Technology of the People's Republic of China · Shanghai Municipal Education Commission · National Natural Science Foundation of China · Shanghai Education Development Foundation
References (37)
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