Fluorescence Spot Quantification
Fluorescence Spot Quantification - Related Videos
08:38
Quantification of the Immunosuppressant Tacrolimus on Dried Blood Spots Using LC-MS/MS
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Cited by 28 •
2015
Here we describe a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) assay to quantify the immunosuppressant tacrolimus in dried blood spots using a simple manual protein precipitation step and online column extraction.
12:22
Automated Quantification of Synaptic Fluorescence in C. elegans
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Cited by 5 •
2012
The abundance of neurotransmitter receptors clustered at synapses strongly influences synaptic strength. This method quantifies fluorescently-labeled neurotransmitter receptors in three dimensions with single-synapse resolution in C. elegans, allowing hundreds of synapses to be rapidly characterized within a single sample without distortions introduced by z-plane projection.
07:44
Quantification of dsDNA using the Hitachi F-7000 Fluorescence Spectrophotometer and PicoGreen Dye
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Cited by 6 •
2010
Demonstration of quantification of dsDNA using Molecular Probes PicoGreen dye and Hitachi F-7000 Fluorescence Spectrophotometer equipped with a microplate reader accessory.
10:45
Finding Your Blind Spot and Perceptual Filling-in
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University In the back of everyone's eye is a small piece of neural tissue called the retina. The retina has photosensitive cells that respond to stimulation by light. The responses of these cells are sent into the brain through the optic nerve, a bundle of neural fibers. In each retina there is a place somewhere in the periphery where the outputs from retinal cells collect and the bundled optic nerve exits to the brain. At that location,...
02:37
Quantification of Infectious Hepatitis C Virus by Fluorescence Microscopy
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2026
Source: Ren, S., et al. A Protocol for Analyzing Hepatitis C Virus Replication. J. Vis. Exp. (2014)This video demonstrates the fluorescence focus assay used to quantify infectious Hepatitis C virus in cell culture. It demonstrates the serial dilution of viral supernatant, the infection of hepatoma cells, and the detection of viral replication sites using antibody-based fluorescence microscopy.
FAQs
Background correction reduces the contribution of surrounding pixels, making fluorescent features easier to distinguish from local signal variation. Thresholding then sets a criterion for deciding which pixels belong to a candidate spot. If the threshold is too low, nonspecific background may be included; if it is too high, genuine signal may be excluded. Consistent settings therefore affect measured spot number and size.
Spot segmentation determines which connected or spatially defined pixels are treated as individual fluorescent features. This step allows analysis to move beyond visual inspection by assigning measurements such as spot number, area, and intensity to detected signals. Accurate segmentation is especially important when comparing cellular or pathogen-associated fluorescence across samples, because inconsistent boundaries can change the resulting quantitative values.
Spot number, area, intensity, and spatial distribution describe different aspects of a fluorescence pattern. Number can indicate how many discrete features are detected, while area reflects their measured extent and intensity reflects signal strength. Spatial distribution adds information about where features occur. Examining these metrics together can provide a more informative comparison than relying on a single measurement.
A basic workflow starts with a fluorescence microscopy image and applies background correction before selecting a threshold for signal detection. The detected pixels are then segmented into spots, after which the analysis calculates number, area, intensity, or spatial distribution. Applying the same processing sequence across samples, experimental conditions, or time points supports more consistent comparisons.
In immunology and infection studies, the method can quantify labeled immune cells, intracellular structures, or pathogen-associated signals in microscopy images. These measurements support assessment of cellular responses and infection burden while allowing researchers to compare experimental conditions. The same approach can also help evaluate treatment effects when fluorescence patterns change between treated and untreated samples.
Quantified spot measurements provide numerical outcomes for comparing samples, conditions, or time points. Changes in spot number, area, intensity, or spatial distribution may indicate differences in labeled cellular features, intracellular structures, or pathogen-associated signals. Standardized analysis is important because it improves reproducibility and helps researchers interpret whether observed differences correspond to altered immune responses, infection burden, or treatment effects.