2012
DOI: 10.3788/aos201232.0917001
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Stereological and Laser Scanning Confocal Microscopic Analysis of 3-Dimensional Morphology of Melanoma Cells

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Cited by 1 publication
(2 citation statements)
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“…On the one hand, it can select to specifically bind the components of the cells under research; on the other hand, after fluorescence confocal imaging, the dyeing cellular components must be conveniently separated from others often through digital image processing. To meet the requirements, instead of labeling cytoplasm and nucleus of lymphocytes as done in previous research, [13][14][15][16][17]29 the membrane marker CM-DiI V22888 (Life Technologies Co., Ltd.) and the nucleus marker Dapi S36968 (Life Technologies Co., Ltd.) are selected to effectively distinguish the edges of nucleuscytoplasm and cytoplasm membrane. The absorption spectral peak and the exciting fluorescence peak for CM-DiI V22888 are at 553 and 570 nm, respectively, and for Dapi S36968 they are at 364 and 460 nm, respectively.…”
Section: Sample Preparationmentioning
confidence: 99%
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“…On the one hand, it can select to specifically bind the components of the cells under research; on the other hand, after fluorescence confocal imaging, the dyeing cellular components must be conveniently separated from others often through digital image processing. To meet the requirements, instead of labeling cytoplasm and nucleus of lymphocytes as done in previous research, [13][14][15][16][17]29 the membrane marker CM-DiI V22888 (Life Technologies Co., Ltd.) and the nucleus marker Dapi S36968 (Life Technologies Co., Ltd.) are selected to effectively distinguish the edges of nucleuscytoplasm and cytoplasm membrane. The absorption spectral peak and the exciting fluorescence peak for CM-DiI V22888 are at 553 and 570 nm, respectively, and for Dapi S36968 they are at 364 and 460 nm, respectively.…”
Section: Sample Preparationmentioning
confidence: 99%
“…Thus, to identify the key features of light scattering from clinical lymphocytes, a three-dimensional (3-D) shape model is set up with the membrane, nucleus, and proper optical structures to mimic their pathological conditions. 7,[10][11][12][13][14][15][16][17][18][19][20] The LSP of the model is simulated by some numerical methods, such as the finite-difference time-domain (FDTD) 21,22 and discrete dipole approximation. 23,24 Finally, specific LSP features are extracted according to the statistical principles by analytical methods, such as machine learning.…”
Section: Introductionmentioning
confidence: 99%