1. Multi-photon near-infrared emission saturation nanoscopy using upconversion nanoparticles
- Author
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Mehran Kianinia, Dayong Jin, Baoming Wang, Xuchen Shan, Qian Peter Su, Shaun P. Jackson, Chaohao Chen, Peng Xi, Fan Wang, Mike C. L. Wu, Shihui Wen, Milos Toth, Yongtao Liu, Du Li, and Igor Aharonovich
- Subjects
Materials science ,Photon ,Science ,General Physics and Astronomy ,02 engineering and technology ,010402 general chemistry ,01 natural sciences ,Article ,General Biochemistry, Genetics and Molecular Biology ,law.invention ,law ,Stimulated emission ,lcsh:Science ,Penetration depth ,Multidisciplinary ,business.industry ,Near-infrared spectroscopy ,STED microscopy ,General Chemistry ,021001 nanoscience & nanotechnology ,Laser ,0104 chemical sciences ,Femtosecond ,Optoelectronics ,lcsh:Q ,0210 nano-technology ,business ,Excitation - Abstract
Multiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 μm thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking., Upconversion nanoparticles offer the potential for deep tissue biological imaging. Here, Chen et al. develop super resolution optical imaging in the near-infrared for imaging with sub-50 nm resolution through almost 100 microns of tissue.
- Published
- 2018
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