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Type: Journal article
Title: An image processing application for quantitative cross-correlative microscopy for large cell-populations: a gold nanoparticle radiosensitisation study
Author: Turnbull, T.
Douglass, M.
Bezak, E.
Thierry, B.
Kempson, I.
Citation: Powder Diffraction, 2017; 32(S2):S33-S37
Publisher: International Centre for Diffraction Data
Issue Date: 2017
ISSN: 0885-7156
Statement of
Tyron Turnbull, Michael Douglass, Eva Bezak, Benjamin Thierry and Ivan Kempson
Abstract: A robust analysis script was developed in MATLAB for cross-correlative quantification of internalised gold nanoparticle (AuNP) uptake in a large number of individual cells with the corresponding number of DNA double-strand breaks (DSBs) in the same cells. The correlation of inorganic NP content with a biological marker at the single-cell level will aid in the elucidation of mechanisms of NP radiosensitisation. PC-3 cells were co-cultured with AuNPs and irradiated using an iridium-192 source. AuNP uptake was measured using synchrotron X-ray fluorescence (XRF) and DSBs imaged via confocal microscopy. MATLAB 2016a was used to develop a script to cross-correlate the two imaging modalities and quantify both DSBs and internalised AuNP content in the same cell. Various user-defined options written into the script give a high degree of versatility, which can account for a large number of variables in experimental parameters and data acquisition. The analysis procedure is flexible and robust, which gives consistent consideration to the wide spectrum of potential input image/data sets. Quantitative correlative microscopy was achieved with a custom MATLAB script used to correlate γH2AX foci (a marker of DNA DSBs) from confocal microscopy with AuNP content acquired using synchrotron XRF at the single-cell level. The script can be extended to a broad range of multi-modality imaging spectroscopies.
Keywords: Radiation damage evaluation methods; image processing; X-ray fluorescence (XRF) systems; imaging spectroscopy
Rights: © International Centre for Diffraction Data 2017
RMID: 0030074194
DOI: 10.1017/S0885715617000719
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Appears in Collections:Physics publications

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