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Nanochemistry advancing photon conversion in rare-earth nanostructures for theranostics

纳米技术 光子上转换 发光 纳米光子学 纳米化学 材料科学 光电子学
作者
Ruichan Lv,Micah Raab,Yanxing Wang,Jie Tian,Jun Lin,Paras N. Prasad
出处
期刊:Coordination Chemistry Reviews [Elsevier BV]
卷期号:460: 214486-214486 被引量:126
标识
DOI:10.1016/j.ccr.2022.214486
摘要

Rare-earth (RE) doped nanoparticles show unique features of photon conversion from an incident wavelength to a more suitable wavelength at an intended biological site, thus enhancing the scope of theranostics. A number of reviews have already addressed biomedical applications of photon upconversion luminescence (UCL) from infrared (IR) to a shorter wavelength. However, there has been a great deal of recent interest in using photon downshifting luminescence (DSL) in RE ions to produce wavelengths in the near infrared (NIR) optical transparency windows such as NIR II and NIR III to enable deep tissue penetration with significantly less scattering for 3D deep tissue imaging. This review is unique in scope and distinct from past reviews as we present nanochemistry approaches assisted by the new area of materials informatics utilizing artificial intelligence (AI) and machine learning to produce optimized multishell nanostructures containing RE ions. It introduces approaches for photosentitization utilizing new mechanisms of energy transfer for photon harvesting by strongly absorbing dye antennas to produce highly efficient both photon UCL and DSL (in some cases concurrently). This includes dye conjugation for sensitization, luminescence modulation by metal and other elemental co-doping, core-multishell structure for controlling excitation dynamics with minimal heating, and hierarchical composite nanostructures for multimodal MRI, CT, photoacoustic, cerenkov, UCL, and NIR II imaging. It presents AI machine learning assisted material informatics including discrete dipole approximation (DDA) simulation, heuristic algorithms (HAs), logistic regression (LR), and support vector machine (SVM) as providing valuable insight for nanochemistry by searching optimized element, concentration, and key influence element, which can improve the efficiency compared with the conventional “trial and error” method or intuitive experiments. We describe surface modification of these photonic nanoprobes for in vitro/ vivo deep tissue bioimaging, and for multimodal imaging. Also, the probes can be used for sensing, accurate NIR nanothermometry, theranostics, and imaging guided synergistic photodynamic therapy (PDT), photothermal therapy (PTT), photoactive therapy, and controlled drug release. Selected examples of theranostics such as the brain theranostics with neurophotonics, preclinical surgery navigation with the developed NIR II imaging are provided. We hope that this timely account of our current understanding and status of preclinically used RE luminescence probes will hopefully entice an abroad range of scientists in different disciplineses.
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