Normalized Spot Volume
Normalized Spot Volume - Related Videos
10:45
Finding Your Blind Spot and Perceptual Filling-in
0 Views •
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,...
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.
05:10
A Spot Plate Assay for Evaluating Oxidative Stress Responses in Bacterial Strains
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2025
This video demonstrates a spot plate assay tailored to assess the oxidative stress responses of bacterial strains. Some strains produce pyomelanin, an antioxidant pigment. Conversely, strains treated with a test agent, leading to reduced pyomelanin production, exhibit increased susceptibility to oxidative stress, resulting in decreased cell viability compared to pyomelanin-producing strains.
11:28
Dried Blood Spots - Preparing and Processing for Use in Immunoassays and in Molecular Techniques
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Cited by 175 •
2015
The preparing and processing of dried blood spots (DBS) for their final analysis are still poorly standardized for most diagnostic applications. To overcome this shortcoming, a comprehensive step-by-step protocol is suggested and subsequently evaluated with regard to its effectiveness for detecting markers of viral infections.
01:19
Normal Stress
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2024
Normal stress is a type of stress that occurs when forces act perpendicular, or normal, to a material's cross-sectional area. This stress often arises in structures when subjected to axial loading, which is the application of force along the axis of an object. A practical example of this can be found in bridge truss members. When a rod is under axial loading, the internal forces and corresponding stress are normal to the plane of the section, so it is termed normal stress. It's important to...
FAQs
Normalization places integrated spot signals on a common reference scale, reducing the influence of differences in cell input or assay background. This makes comparisons more meaningful when samples produce spots with different overall signal strengths or morphologies. The resulting value supports relative assessment of cellular activity across conditions or experiments rather than relying only on visual spot counts.
Image analysis accounts for both the area occupied by a spot and the strength of its signal by integrating them into a volume measurement. A larger spot, a more intense spot, or both can therefore contribute differently than a small, faint spot. Normalization then helps compare these integrated measurements when spot morphology varies among samples.
The reference determines how integrated signal is scaled for comparison. Cell input can account for differences in the number of cells contributing to an assay, whereas assay background provides a basis for interpreting signal relative to nonspecific or baseline activity. Selecting and applying a defined reference consistently is therefore important for meaningful comparisons between samples.
The workflow must quantify the signal across individual immunospots rather than treating every spot as identical. Software integrates each spot's signal, incorporating its measured morphology and intensity, and then applies the selected reference, such as cell input or assay background. Consistent analysis across samples produces values that can be compared more directly.
It is useful when researchers compare antigen-specific cytokine secretion, antibody-producing cells, or other cellular responses measured by ELISpot and related assays. The metric adds information beyond spot presence or count by reflecting integrated signal. That can help distinguish samples when spot size or signal intensity differs across immune stimulation conditions or experiments.
In infection research, the measure can help compare pathogen-responsive immune activity across samples while accounting for variation in spot morphology or overall signal strength. Depending on the assay, the analyzed response may represent antigen-specific cytokine secretion or antibody-producing cells. Normalized results can therefore support comparisons of immune responses to pathogen-related stimulation across experimental conditions.