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Related Experiment Video

Updated: May 29, 2026

The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation

The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation

Published on: October 12, 2010

A new model for the estimation of cell proliferation dynamics using CFSE data.

H T Banks¹, Karyn L Sutton, W Clayton Thompson

¹Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC 27695-8212, USA. htbanks@ncsu.edu

Journal of Immunological Methods

|September 6, 2011

Summary

This study revises a mathematical model for CFSE cell proliferation assays. The enhanced model incorporates cellular autofluorescence and Gompertz decay for improved physiological accuracy in analyzing cell division dynamics.

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Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

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Last Updated: May 29, 2026

The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation

The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation

Published on: October 12, 2010

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Published on: December 13, 2012

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Published on: April 29, 2012

Area of Science:

Immunology
Mathematical Biology
Cell Biology

Background:

Carboxyfluorescein succinimidyl ester (CFSE) analysis is widely used to study cell division and associated behavioral changes.
Previous partial differential equation (PDE) models described lymphocyte dynamics in CFSE assays but lacked detailed physiological underpinnings.

Purpose of the Study:

To significantly revise an existing PDE model for CFSE proliferation assays.
To enhance the physiological interpretability of model parameters.
To improve the accuracy of modeling cell division and label decay.

Main Methods:

Replaced the heuristic parameter for CFSE dye dilution with cellular autofluorescence.
Quantified label decay using a Gompertz decay process.
Developed a revised method for fitting the model to CFSE histogram data.

Main Results:

The revised model offers a stronger physiological basis for understanding CFSE assay data.
The model accurately replicates observed behaviors in proliferation data.
Improved parameterization enhances the physiological relevance of the model.

Conclusions:

The enhanced CFSE proliferation model provides a more physiologically grounded approach to data analysis.
This revised model improves the understanding of cell division dynamics and label decay.
The method is capable of replicating experimental observations in CFSE assays.