Recent Advances in Design and Fabrication of Upconversion Nanoparticles and Their Safe Theranostic Applications

Zhanjun Gu(Chinese Academy of Sciences), Liang Yan(Chinese Academy of Sciences), Gan Tian(Chinese Academy of Sciences), Shoujian Li(Sichuan University), Zhifang Chai(Soochow University), Yuliang Zhao(Chinese Academy of Sciences)
Advanced Materials
July 1, 2013
Cited by 487Open Access
Full Text

Abstract

Lanthanide (Ln) doped upconversion nanoparticles (UCNPs) have attracted enormous attention in the recent years due to their unique upconversion luminescent properties that enable the conversion of low-energy photons (near infrared photons) into high-energy photons (visible to ultraviolet photons) via the multiphoton processes. This feature makes them ideal for bioimaging applications with attractive advantages such as no autofluorescence from biotissues and a large penetration depth. In addition, by incorporating advanced features, such as specific targeting, multimodality imaging and therapeutic delivery, the application of UCNPs has been dramatically expanded. In this review, we first summarize the recent developments in the fabrication strategies of UCNPs with the desired size, enhanced and tunable upconversion luminescence, as well as the combined multifunctionality. We then discuss the chemical methods applied for UCNPs surface functionalization to make these UCNPs biocompatible and water-soluble, and further highlight some representative examples of using UCNPs for in vivo bioimaging, NIR-triggered drug/gene delivery applications and photodynamic therapy. In the perspectives, we discuss the need of systematically nanotoxicology data for rational designs of UCNPs materials, their surface chemistry in safer biomedical applications. The UCNPs can actually provide an ideal multifunctionalized platform for solutions to many key issues in the front of medical sciences such as theranostics, individualized therapeutics, multimodality medicine, etc.


Related Papers

No related papers found

Powered by citation graph analysis