Noise-Corrected Principal Component Analysis of fluorescence lifetime imaging data
| Autor: | Alix Le Marois, Klaus Suhling, Rainer Heintzmann, Simon Labouesse |
|---|---|
| Přispěvatelé: | King‘s College London, Institute of Photonic Technology [IPHT] Leibniz-Institute of Photonic Technology, Albert Einstein Str 9, D-07745 Jena, Germany, Coherent Optical Microscopy and X-rays (COMiX), Institut FRESNEL (FRESNEL), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU), Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany], Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Fluorescence-lifetime imaging microscopy Materials science Photon Analytical chemistry General Physics and Astronomy 01 natural sciences Noise (electronics) General Biochemistry Genetics and Molecular Biology 010309 optics 03 medical and health sciences Live cell imaging 0103 physical sciences Microscopy Humans General Materials Science Photons Principal Component Analysis Cell Membrane Optical Imaging General Engineering General Chemistry Image Enhancement Photon counting 030104 developmental biology Membrane Microscopy Fluorescence Principal component analysis [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic Biological system HeLa Cells |
| Zdroj: | Journal of Biophotonics Journal of Biophotonics, Wiley, 2017, 10 (9), pp.1124-1133. ⟨10.1002/jbio.201600160⟩ Journal of Biophotonics, 2017, 10 (9), pp.1124-1133. ⟨10.1002/jbio.201600160⟩ |
| ISSN: | 1864-063X 1864-0648 |
| DOI: | 10.1002/jbio.201600160⟩ |
| Popis: | Fluorescence Lifetime Imaging (FLIM) is an attractive microscopy method in the life sciences, yielding information on the sample otherwise unavailable through intensity-based techniques. A novel Noise-Corrected Principal Component Analysis (NC-PCA) method for time-domain FLIM data is presented here. The presence and distribution of distinct microenvironments are identified at lower photon counts than previously reported, without requiring prior knowledge of their number or of the dye's decay kinetics. A noise correction based on the Poisson statistics inherent to Time-Correlated Single Photon Counting is incorporated. The approach is validated using simulated data, and further applied to experimental FLIM data of HeLa cells stained with membrane dye di-4-ANEPPDHQ. Two distinct lipid phases were resolved in the cell membranes, and the modification of the order parameters of the plasma membrane during cholesterol depletion was also detected. Noise-corrected Principal Component Analysis of FLIM data resolves distinct microenvironments in cell membranes of live HeLa cells. |
| Databáze: | OpenAIRE |
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