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Ratiometric afterglow luminescent nanoplatform enables reliable quantification and molecular imaging

Afterglow luminescence is an internal luminescence pathway that occurs after photo-excitation, holds great promise for non-background molecular imaging in vivo, but suffer from poor quantitative ability owing to luminescent attenuation over time. Moreover, the inert structure and insufficient reacti...

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Detalles Bibliográficos
Autores principales: Liu, Yongchao, Teng, Lili, Lyu, Yifan, Song, Guosheng, Zhang, Xiao-Bing, Tan, Weihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039063/
https://www.ncbi.nlm.nih.gov/pubmed/35468901
http://dx.doi.org/10.1038/s41467-022-29894-1
Descripción
Sumario:Afterglow luminescence is an internal luminescence pathway that occurs after photo-excitation, holds great promise for non-background molecular imaging in vivo, but suffer from poor quantitative ability owing to luminescent attenuation over time. Moreover, the inert structure and insufficient reactive sites of current afterglow materials make it hard to design activatable afterglow probes for specific detection. Here, we report a ratiometric afterglow luminescent nanoplatform to customize various activatable afterglow probes for reliable quantification and molecular imaging of specific analytes, such as NO, ONOO(−) or pH. Notably, these afterglow probes can not only address the attenuation of afterglow intensity and eliminate the interference of factors (e.g., laser power, irradiation time, and exposure time), but also significantly improve the imaging reliability in vivo and signal-to-background ratios (~1200-fold), both of which enable more reliable quantitative analysis in biological systems. Moreover, as a proof-of-concept, we successfully design an NO-responsive ratiometric afterglow nanoprobe, RAN1. This nanoprobe can monitor the fluctuations of intratumoral NO, as a biomarker of macrophage polarization, making it possible to real-time dynamically evaluate the degree cancer immunotherapy, which provides a reliable parameter to predict the immunotherapeutic effect.