Characterizing the Size and Shape of Stem Cells

Stem cells are interesting because they are undifferentiated, and eventually, they differentiate into particular cell types. There is a large amount of research going into stem cells and how they can help with therapeutics. Analyzing them using Particle Insight can aid this.

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Using Particle Insight for Characterizing Size and Shape of Stem Cells

The Particle Insight is an instrument that analyzes particles using dynamic image analysis and has been used to analyze stem cells by quantifying them by their size and shape. This high-speed technique offers quantification and differentiation between identified particles such as the cells themselves and any debris in the suspended fluid. 

The ability to measure concentration is critical in this application. Not only is it essential to accurately differentiate cells from debris or bubbles based on shape, but it is also crucial to know the concentration of each identified population in the sample to best understand the contents. The ability to also keep pictures of the thousands of measured particles offers objective evidence of the sample. With stem cell measurements, it is necessary to look at the size information, opacity information to differentiate viability and other shape parameters such as circularity and concentration information.

Advantages of Particle Insight

Shape, size, and concentration information are helpful when applied to this research application. The Particle insight has been used to study cell kinetics, such as stem cells becoming more elongated as they move towards apoptosis or perhaps towards differentiating different populations in the suspended sample.

The Particle Insight measures and calculates data in real-time and stores all the data, including thumbnail images. The thumbnails allow the information to be presented visually in order to better understand all the particles in the suspension. 

Circularity determines how round the particles are, and opacity determines how dark they are. These are only two of more than 32 measured shape measures for every particle that can be used to further differentiate the concentration of measured subpopulations of particles.   

There are additional software tools that enable the user to better study the kinetics of the samples.

Other Benefits Offered by Particle Insight

As mentioned briefly before, besides obtaining the size and shape information of every cell, the Particle Insight is also capable of enumeration, meaning it can be used to determine not only the concentration but also the percentage of small particles or dark particles in the entire population.

Scrolling through the thumbnails only gives qualitative information. Available software tools can be used to obtain more in-depth information. For example, you could perform a correlation between cell size and opacity. A correlation plot is then created to easily identify the outlier particles and determine if they are cells or debris. This same correlation function can be used to compare; for example, as the particles or cells are getting larger, are they also become rougher, which can be a sign of cell death.  

Some of the particles could actually be agglomerates, which can easily be identified, ignored, or discarded from the statistics. Because this technique is a number-based analysis, it is commonly used as a "rare event detector" where very small occurrences of outlier particles can easily be identified in populations of tens of thousands of measured particles.

 Another feature of the Particle Insight is particle classification. Particle classification is a feature that allows the user to obtain a more in-depth analysis of sub-populations of the sample. Particles can be separated into different classes using their differences in shape to then obtain what percent of each population is present in the sample.  

Conclusion

In conclusion, the Particle Insight, using dynamic image analysis, offers more information than traditional cell counters and particle size analyzers combined.

This information has been sourced, reviewed and adapted from materials provided by Vision Analytical Inc.

For more information on this source, please visit Vision Analytical Inc.