Abstract
Collagen and other components in the extracellular matrix are proving of increasing importance for the understanding of complex cell and tissue interactions in a variety of settings. Detection and quantitation of these components can still prove challenging, and a number of techniques have been developed. We focus here on methods in fluorescence-based assessments, including multiplexed immunodetection and the use of simpler histochemical stains, both complemented by linear unmixing techniques. Typically, differentiating these components requires the use of a set of optical filters to isolate each fluorescent compound from each other and from often bright background autofluorescence signals. However, standard fluorescent microscopes are usually only able to separate a limited number of components. If the emission spectra of the fluorophores are spectrally distinct, but overlapping, sophisticated spectral imaging or computational methods can be used to optimize separation and quantitation. This chapter describes spectral unmixing methodology and associated open-source software tools available to analyze multispectral as well as simple color (RGB) images.
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Acknowledgments
We acknowledge Nenad Bozinovic for providing the MATLAB code for the UnmixingGUI.
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Harmany, Z.T., Fereidouni, F., Levenson, R.M. (2017). Spectral Unmixing Methods and Tools for the Detection and Quantitation of Collagen and Other Macromolecules in Tissue Specimens. In: Rittié, L. (eds) Fibrosis. Methods in Molecular Biology, vol 1627. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7113-8_30
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DOI: https://doi.org/10.1007/978-1-4939-7113-8_30
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