Paper
5 March 2015 Detecting polymeric nanoparticles with coherent anti-stokes Raman scattering microscopy in tissues exhibiting fixative-induced autofluorescence
N. L. Garrett, Lisa Godfrey, A. Lalatsa, D. R. Serrano, I. F. Uchegbu, A. Schatzlein, J. Moger
Author Affiliations +
Abstract
Recent advances in pharmaceutical nanotechnology have enabled the development of nano-particulate medicines with enhanced drug performance. Although the fate of these nano-particles can be macroscopically tracked in the body (e.g. using radio-labeling techniques), there is little information about the sub-cellular scale mechanistic processes underlying the particle-tissue interactions, or how these interactions may correlate with pharmaceutical efficacy. To rationally engineer these nano-particles and thus optimize their performance, these mechanistic interactions must be fully understood. Coherent Anti-Stokes Raman scattering (CARS) microscopy provides a label-free means for visualizing biological samples, but can suffer from a strong non-resonant background in samples that are prepared using aldehyde-based fixatives. We demonstrate how formalin fixative affects the detection of polymeric nanoparticles within kidneys following oral administration using CARS microscopy, compared with samples that were snap-frozen. These findings have implications for clinical applications of CARS for probing nanoparticle distribution in tissue biopsies.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
N. L. Garrett, Lisa Godfrey, A. Lalatsa, D. R. Serrano, I. F. Uchegbu, A. Schatzlein, and J. Moger "Detecting polymeric nanoparticles with coherent anti-stokes Raman scattering microscopy in tissues exhibiting fixative-induced autofluorescence", Proc. SPIE 9329, Multiphoton Microscopy in the Biomedical Sciences XV, 932922 (5 March 2015); https://doi.org/10.1117/12.2079365
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KEYWORDS
Nanoparticles

Kidney

Signal detection

Tissues

Microscopy

Raman spectroscopy

CARS tomography

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