Multi-parameter Fluorescence Detection
Multi-parameter Fluorescence Detection - Related Videos
07:36
Isolation of Human Lymphatic Endothelial Cells by Multi-parameter Fluorescence-activated Cell Sorting
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Cited by 11 •
2015
The goal of this protocol is to isolate lymphatic endothelial cells lining human lymphatic malformation cyst-like vessels and foreskins using fluorescence-activated cell sorting (FACS). Subsequent cell culturing and expansion of these cells permits a new level of experimental sophistication for genetic, proteomic, functional and cell differentiation studies.
08:43
Production and Multi-Parameter Live Cell Fluorescence Lifetime Imaging Microscopy (FLIM) of Multicellular Spheroids
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Cited by 3 •
2024
Here, we describe different multicellular spheroid formation methods to perform follow-up multi-parameter live cell microscopy. Using fluorescence lifetime imaging microscopy (FLIM), cellular autofluorescence, staining dyes, and nanoparticles, the approach for analysis of cell metabolism, hypoxia, and cell death in live three-dimensional (3D) cancer and stem cell-derived spheroids is demonstrated.
13:42
Multi-parameter Measurement of the Permeability Transition Pore Opening in Isolated Mouse Heart Mitochondria
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Cited by 19 •
2012
A spectrofluorometric protocol for the measurement of the mitochondrial permeability transition pore opening in isolated mouse heart mitochondria is presented here. The assay involves the simultaneous measurement of mitochondria Ca2+ handling, mitochondrial membrane potential and mitochondrial volume. The procedure for obtaining high-quality and functional heart mitochondria is also described.
03:44
Detection of Inflammasome Activation via Fluorescence Microscopy
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2025
This video demonstrates a method to detect NLRP3 inflammasome activation in macrophages using fluorescent reporter probes. The cells are treated with potassium ionophores and glycine to induce inflammasome assembly and caspase-1 activation. Fluorescent reporter probes visualize activated caspase-1, and cells are stained with a fluorescent dye for nuclei visualization.
11:19
ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
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Cited by 4 •
2017
We present a method for quantifying growth phenotypes of individual yeast cells as they grow into colonies on solid media using time-lapse microscopy termed, One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). Population heterogeneity of genetically identical cells growing into colonies can be directly observed and quantified.
FAQs
Distinct excitation and emission spectra allow each fluorophore to be assigned an optical signature. The instrument uses optical filters and separate detection channels to collect signals associated with those signatures, rather than treating the sample as a single fluorescent output. This separation lets one measurement track multiple biochemical targets or processes.
Spectral compensation is important when fluorophore signals overlap. It supports separation of contributions that would otherwise be difficult to distinguish in the detected output, improving the reliability of comparisons among labeled targets. In practice, compensation is central to interpreting multiplexed measurements quantitatively, especially when several fluorescent labels are measured from the same sample.
The number and distinctness of fluorescent labels influence how effectively signals can be resolved. Labels need sufficiently different excitation or emission behavior for the optical system to assign them to separated channels. When signals overlap, filter selection, channel separation, and spectral compensation become especially important for preserving interpretable measurements.
An assay begins by labeling the biochemical targets or processes with fluorophores that provide distinct spectral signals. The sample is then examined through optical filters and separated detection channels, followed by spectral compensation to distinguish overlapping outputs. The resulting measurements can be compared across targets within the same sample, supporting multiplexed analysis.
In biochemistry, this approach can be applied to protein expression, enzyme activity, molecular binding, and cellular function. Measuring these features together helps conserve sample and reduces analysis time compared with examining each parameter separately. It also allows related biochemical signals to be evaluated within the same experimental sample.
Simultaneous measurement of several fluorescent parameters reveals differences that may be hidden in a single-parameter readout. Accurate signal separation supports quantitative comparisons among components or processes, while the shared sample context helps researchers examine complex interactions and heterogeneous samples. The result is greater resolution of biochemical variation without requiring separate measurements for every target.