Multicolor Analysis
Multicolor Analysis - Related Videos
12:51
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
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Cited by 13 •
2013
We demonstrate the use of fluorescence photo activation localization microscopy (FPALM) to simultaneously image multiple types of fluorescently labeled molecules within cells. The techniques described yield the localization of thousands to hundreds of thousands of individual fluorescent labeled proteins, with a precision of tens of nanometers within single cells.
07:11
Multicolor Flow Cytometry Analyses of Cellular Immune Response in Rhesus Macaques
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Cited by 6 •
2010
We demonstrate the utility of multicolor flow cytometry for detailed phenotypic and functional characterization of total as well as memory subsets of CD4+ and CD8+ T cells in rhesus macaques, the ideal model for HIV/AIDS vaccine studies.
14:15
Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery
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Cited by 21 •
2020
The protocol describes the fabrication of fully colored three-dimensional prints of patient-specific, anatomical skull models to be used for surgical simulation. The crucial steps of combining different imaging modalities, image segmentation, three-dimensional model extraction, and production of the prints are explained.
10:21
Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers
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Cited by 18 •
2016
Multicolor fluorescence detection in droplet microfluidics typically involves bulky and complex epifluorescence microscope-based detection systems. Here we describe a compact and modular multicolor detection scheme that utilizes an array of optical fibers to temporally encode multicolor data collected by a single photodetector.
10:31
Multicolor Time-lapse Imaging of Transgenic Zebrafish: Visualizing Retinal Stem Cells Activated by Targeted Neuronal Cell Ablation
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Cited by 41 •
2010
In this video, techniques for multicolor confocal time-lapse imaging and targeted cell ablation are provided. Time-lapse imaging is used to monitor the behavior of multiple cell types of interest in vivo. Targeted cell ablation facilitates the study neural circuit function and cell-specific neuronal regeneration paradigms.
FAQs
Each fluorescent marker is selected for a different emission spectrum or signal characteristic, allowing the resulting signals to be distinguished during imaging. This separation lets researchers associate individual colors with particular cell types, structures, molecular markers, or activity patterns. The approach therefore supports simultaneous examination of several biological features while retaining their locations within the same specimen.
Image processing separates and interprets the detected signals so that overlapping biological features can be assigned to their corresponding markers. Rather than treating the specimen as a single composite image, researchers can examine each color-defined component and compare its position with other labeled components. This is especially useful for resolving cellular relationships, synaptic organization, and neural morphology.
Spatial context shows where labeled cells, structures, and molecular features occur relative to one another. That information can reveal organization within neural circuits, associations between neurons and glial cells, and the arrangement of synaptic components. Multicolor Analysis is valuable because it increases the number of measured features without discarding the positional relationships needed to interpret cellular organization.
A typical workflow combines fluorescent markers with distinct detectable signals, applies them to the biological specimen, and captures the labeled material with microscopy. Image-processing methods then separate the signals, allowing each target to be examined individually and in relation to the others. The resulting analysis connects marker identity with spatial organization, morphology, or activity patterns.
Researchers would choose it when one specimen contains several features that must be examined together, such as cell identity, neuronal structure, molecular markers, and activity patterns. Measuring these features simultaneously can expose relationships that are difficult to assess when each target is studied separately. The method is therefore suited to complex cellular organization and neural-circuit analysis.
By combining cellular identity, organization, and activity-related patterns in a spatially resolved image, the approach helps researchers relate microscopic structure to brain function. It can also reveal how neurons, glial cells, synaptic features, and molecular markers are arranged within affected tissue. These measurements provide a basis for examining cellular relationships relevant to neurological disease research.