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09:11
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
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Cited by 5 •
2023
The micronucleus (MN) assay is a well-established test for quantifying DNA damage. However, scoring the assay using conventional techniques such as manual microscopy or feature-based image analysis is laborious and challenging. This paper describes the methodology to develop an artificial intelligence model to score the MN assay using imaging flow cytometry data.
10:43
Flow Cytometry Purification of Mouse Meiotic Cells
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Cited by 57 •
2011
An efficient method to obtain highly purified viable meiotic fractions from mouse testis is described, which combines a refined cell dissociation protocol with fluorescent activated cell sorting (FACS). This method takes advantage of differences in the DNA content and nuclear density of discrete meiotic fractions.
09:39
Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry
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Cited by 32 •
2015
Many different methods exist for the measurement of extracellular vesicles (EVs) using flow cytometry (FCM). Several aspects should be considered when determining the most appropriate method to use. Two protocols for measuring EVs are presented, using either individual detection or a bead-based approach.
07:34
Schlieren Imaging: A Technique to Visualize Supersonic Flow Features
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2023
Source: Jose Roberto Moreto, Jaime Dorado, and Xiaofeng Liu, Department of Aerospace Engineering, San Diego State University, San Diego, CA Military jet fighters and projectiles can fly at incredible speeds that exceed the speed of sound, which means they are traveling at a supersonic speed. The speed of sound is the speed at which a sound wave propagates through a medium, which is 343 m/s. Mach numbers are used to gauge the flight speed of an object relative to the speed of sound. An object...
07:22
Quality-Controlled Sputum Analysis by Flow Cytometry
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Cited by 4 •
2021
This protocol describes an efficient method for dissociating sputum into a single cell suspension and the subsequent characterization of cellular subsets on standard flow cytometric platforms.
FAQs
The rapid combination starts the structural process, while stopping the flow at a chosen delay captures the system at a defined stage. Repeating measurements at different delays produces a time-resolved sequence of scattering patterns. Comparing that sequence allows researchers to follow how nanoscale size, shape, organization, and interactions change during a nonequilibrium transformation.
Scattering patterns contain information about several aspects of nanoscale organization rather than only indicating that a reaction occurred. Their changes can be interpreted in terms of evolving size, shape, organization, and interactions among components. This makes the measurement useful for following structural progression and connecting transient nanoscale arrangements with the behavior of evolving materials.
Rapid combination establishes a well-defined starting point for the process being observed. Because the flow can then be stopped after a selected delay, the measurement focuses on a particular stage rather than an undifferentiated final state. This is especially important for fast-evolving materials, where meaningful structural changes may occur during the interval after mixing.
Researchers rapidly combine two or more components, deliver the mixture through a flow cell, and stop the flow at a selected delay. A neutron beam then records the scattering pattern from the stopped sample. Measurements collected at different delays can be compared to track structural progression across the process, including changes in dimensions, organization, and interactions.
Timing determines which stage of the transformation the neutron measurement examines. A short delay captures an earlier state, whereas a longer delay samples a later state after additional structural evolution. Selecting and comparing delays therefore provides a practical way to map progression from the mixed starting condition toward subsequent organization, aggregation, or other changes supported by the sample.
In engineering research, the method can examine polymer assembly, colloidal transformations, protein aggregation, and other nonequilibrium processes. The resulting structural information helps relate nanoscale changes to material performance. That connection supports the design and evaluation of advanced soft and functional materials, especially when performance depends on how components organize or interact during formation.