Title |
Estimating Lymphocyte Division and Death Rates from CFSE Data
|
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Published in |
Bulletin of Mathematical Biology, May 2006
|
DOI | 10.1007/s11538-006-9094-8 |
Pubmed ID | |
Authors |
Rob J. De Boer, Vitaly V. Ganusov, Dejan Milutinović, Philip D. Hodgkin, Alan S. Perelson |
Abstract |
The division tracking dye, carboxyfluorescin diacetate succinimidyl ester (CFSE) is currently the most informative labeling technique for characterizing the division history of cells in the immune system. Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] have pioneered the quantitative analysis of CFSE data. We confirm and extend their data analysis approach using simple mathematical models. We employ the extended Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] method to estimate the time to first division, the fraction of cells recruited into division, the cell cycle time, and the average death rate from CFSE data on T cells stimulated under different concentrations of IL-2. The same data is also fitted with a simple mathematical model that we derived by reformulating the numerical model of Deenick et al. [J. Immunol. 170:4963-4972, 2003]. By a non-linear fitting procedure we estimate parameter values and confidence intervals to identify the parameters that are influenced by the IL-2 concentration. We obtain a significantly better fit to the data when we assume that the T cell death rate depends on the number of divisions cells have completed. We provide an outlook on future work that involves extending the Deenick et al. [J. Immunol. 170:4963-4972, 2003] model into the classical smith-martin model, and into a model with arbitrary probability distributions for death and division through subsequent divisions. |
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Australia | 1 | 1% |
Mexico | 1 | 1% |
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Korea, Republic of | 1 | 1% |
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Unknown | 82 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 21 | 22% |
Researcher | 21 | 22% |
Student > Master | 10 | 11% |
Student > Doctoral Student | 7 | 7% |
Professor > Associate Professor | 6 | 6% |
Other | 19 | 20% |
Unknown | 10 | 11% |
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Immunology and Microbiology | 10 | 11% |
Mathematics | 7 | 7% |
Biochemistry, Genetics and Molecular Biology | 7 | 7% |
Other | 17 | 18% |
Unknown | 12 | 13% |