Literature DB >> 20195910

Estimation of cell proliferation dynamics using CFSE data.

H T Banks1, Karyn L Sutton, W Clayton Thompson, Gennady Bocharov, Dirk Roose, Tim Schenkel, Andreas Meyerhans.   

Abstract

Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57-89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1-26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experimental data. These investigations suggest that the new decay/label loss and time dependent effective proliferation and death rates do indeed provide improved fits of the model to data. Statistical models for the observed variability/noise in the data are discussed with implications for uncertainty quantification. The resulting new cell dynamics model should prove useful in proliferation assay tracking and modeling, with numerous applications in the biomedical sciences.

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Year:  2010        PMID: 20195910      PMCID: PMC2911498          DOI: 10.1007/s11538-010-9524-5

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  28 in total

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Journal:  Math Comput Model       Date:  2010-11-01

5.  Quantifying cell turnover using CFSE data.

Authors:  Vitaly V Ganusov; Sergei S Pilyugin; Rob J de Boer; Kaja Murali-Krishna; Rafi Ahmed; Rustom Antia
Journal:  J Immunol Methods       Date:  2005-03       Impact factor: 2.303

6.  Estimating lymphocyte division and death rates from CFSE data.

Authors:  Rob J De Boer; Vitaly V Ganusov; Dejan Milutinović; Philip D Hodgkin; Alan S Perelson
Journal:  Bull Math Biol       Date:  2006-05-16       Impact factor: 1.758

7.  Computational analysis of CFSE proliferation assay.

Authors:  Tatyana Luzyanina; Sonja Mrusek; John T Edwards; Dirk Roose; Stephan Ehl; Gennady Bocharov
Journal:  J Math Biol       Date:  2006-11-09       Impact factor: 2.259

8.  Measuring lymphocyte proliferation, survival and differentiation using CFSE time-series data.

Authors:  Edwin D Hawkins; Mirja Hommel; Marian L Turner; Francis L Battye; John F Markham; Philip D Hodgkin
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

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10.  Effect of cellular quiescence on the success of targeted CML therapy.

Authors:  Natalia L Komarova; Dominik Wodarz
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  21 in total

1.  Label Structured Cell Proliferation Models.

Authors:  H T Banks; Frédérique Charles; Marie Doumic Jauffret; Karyn L Sutton; W Clayton Thompson
Journal:  Appl Math Lett       Date:  2010-12-01       Impact factor: 4.055

2.  Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division.

Authors:  Tatyana Luzyanina; Jovana Cupovic; Burkhard Ludewig; Gennady Bocharov
Journal:  J Math Biol       Date:  2013-12-13       Impact factor: 2.259

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

Authors:  H T Banks; Karyn L Sutton; W Clayton Thompson; Gennady Bocharov; Marie Doumic; Tim Schenkel; Jordi Argilaguet; Sandra Giest; Cristina Peligero; Andreas Meyerhans
Journal:  J Immunol Methods       Date:  2011-08-24       Impact factor: 2.303

Review 4.  Estimation methods for heterogeneous cell population models in systems biology.

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5.  An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations.

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Journal:  Inverse Probl       Date:  2016-07-15       Impact factor: 2.407

6.  Numerical rate function determination in partial differential equations modeling cell population dynamics.

Authors:  Andreas Groh; Holger Kohr; Alfred K Louis
Journal:  J Math Biol       Date:  2016-06-13       Impact factor: 2.259

7.  Learning partial differential equations for biological transport models from noisy spatio-temporal data.

Authors:  John H Lagergren; John T Nardini; G Michael Lavigne; Erica M Rutter; Kevin B Flores
Journal:  Proc Math Phys Eng Sci       Date:  2020-02-19       Impact factor: 2.704

8.  Nongenetic origins of cell-to-cell variability in B lymphocyte proliferation.

Authors:  Simon Mitchell; Koushik Roy; Thomas A Zangle; Alexander Hoffmann
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-07       Impact factor: 11.205

9.  Quantifying CFSE Label Decay in Flow Cytometry Data.

Authors:  H T Banks; A Choi; T Huffman; J Nardini; L Poag; W C Thompson
Journal:  Appl Math Lett       Date:  2013-01-03       Impact factor: 4.055

10.  Quantifying T lymphocyte turnover.

Authors:  Rob J De Boer; Alan S Perelson
Journal:  J Theor Biol       Date:  2013-01-09       Impact factor: 2.691

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