Multiplex Imaging Capacity
Multiplex Imaging Capacity - Related Videos
07:18
Highly-Multiplexed Tissue Imaging with Raman Dyes
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Cited by 5 •
2022
Electronic pre-resonance stimulated Raman scattering (epr-SRS) imaging of rainbow-like Raman dyes is a new platform for highly multiplexed epitope-based protein imaging. Here, we present a practical guide including antibody preparation, tissue sample staining, SRS microscope assembly, and epr-SRS tissue imaging.
08:43
Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM
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Cited by 4 •
2017
We demonstrate a method to image multiple molecules within heterogeneous nano-structures at single molecule accuracy using sequential binding and elution of fluorescently labeled antibodies.
01:47
Lung Capacity
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2019
The air in the lungs is measured in volumes and capacities. Lung volume measures reflect the amount of air taken in, released, or left over after a lung function, like a single inhalation. Lung capacity measures are sums of two or more lung volume measures. There are four defined lung volume measures: tidal volume, inspiratory reserve volume, expiratory reserve volume, and residual volume. Tidal volume is the amount of air inhaled and exhaled in a normal breath. Inspiratory...
06:05
Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment
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Cited by 11 •
2023
In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.
07:16
Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach
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Cited by 1 •
2025
This article describes a protocol for multiplex immunofluorescence optimized to characterize the three-dimensional architecture of peritoneal metastases.
FAQs
Each molecular, cellular, or structural target receives an identifiable optical, chemical, or spatial signature. The imaging system then records signals that can be associated with those signatures, while image processing helps separate information that overlaps in the specimen. This organization allows multiple target types to remain distinguishable and supports analysis of biological features in their original context.
Image processing helps disentangle overlapping information collected from the same specimen. Rather than treating the image as a single undifferentiated signal, researchers can separate target-associated information and examine it quantitatively. This step is important when several molecular, cellular, or structural features occupy related regions and must be interpreted together to understand organization or change.
Capacity depends on how many targets can be assigned distinct signatures and subsequently distinguished in the acquired image data. The available signatures may be optical, chemical, spatial, or a combination of these approaches. Capture can occur simultaneously or sequentially, with processing used to organize the resulting signals for multicomponent analysis.
Because multiple target classes are examined within the same specimen, their distributions can be considered together rather than as isolated measurements. Researchers can relate molecular signals to cellular states and structural organization in place. This contextual view supports interpretation of how biological features are arranged and how disease-associated or engineered changes affect that organization.
A study first identifies the molecular, cellular, or structural targets of interest and assigns distinguishable signatures to them. The system then captures the relevant signals either simultaneously or sequentially. Image processing separates and organizes the information, after which researchers quantify target distributions, cell states, tissue architecture, or other features relevant to the investigation.
In bioengineering, researchers can use the approach to evaluate cell states, tissue architecture, and interactions between cells or tissues and biomaterials within one specimen. Comparing these features in context helps characterize how engineered systems are organized and how biological components respond to their surrounding material environment.
The method supports diagnostics research and systems-level studies of biological function by combining information from multiple target types. It can reveal coordinated patterns among molecular, cellular, and structural features, including changes associated with disease. These measurements provide a broader basis for examining biological organization than an analysis focused on a single signal.