Literature DB >> 12464572

Lymphocyte kinetics: the interpretation of labelling data.

Becca Asquith1, Christophe Debacq, Derek C Macallan, Luc Willems, Charles R M Bangham.   

Abstract

DNA labelling provides an exciting tool for elucidating the in vivo dynamics of lymphocytes. However, the kinetics of label incorporation and loss are complex and results can depend on the method of interpretation. Here we describe two approaches to interpreting labelling data. Both seek to explain the common observation that the estimated death rate of lymphocytes is higher than their estimated proliferation rate. In the first approach, an additional source of lymphocytes is postulated. In the second, it is maintained that lymphocyte heterogeneity is sufficient to account for the observation. We explain why we favour the second approach, arguing that the addition of a large source of lymphocytes is unnecessary and difficult to reconcile with what is currently known about lymphocyte physiology. We discuss how the choice of model can affect data interpretation.

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Year:  2002        PMID: 12464572     DOI: 10.1016/s1471-4906(02)02337-2

Source DB:  PubMed          Journal:  Trends Immunol        ISSN: 1471-4906            Impact factor:   16.687


  42 in total

Review 1.  An introduction to lymphocyte and viral dynamics: the power and limitations of mathematical analysis.

Authors:  Becca Asquith; Charles R M Bangham
Journal:  Proc Biol Sci       Date:  2003-08-22       Impact factor: 5.349

2.  Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity.

Authors:  Rob J De Boer; Alan S Perelson; Ruy M Ribeiro
Journal:  J R Soc Interface       Date:  2012-04-18       Impact factor: 4.118

3.  Quantifying lymphocyte kinetics in vivo using carboxyfluorescein diacetate succinimidyl ester (CFSE).

Authors:  Becca Asquith; Christophe Debacq; Arnaud Florins; Nicolas Gillet; Teresa Sanchez-Alcaraz; Angelina Mosley; Luc Willems
Journal:  Proc Biol Sci       Date:  2006-05-07       Impact factor: 5.349

Review 4.  Modeling T cell responses to antigenic challenge.

Authors:  Dominik Wodarz
Journal:  J Pharmacokinet Pharmacodyn       Date:  2014-10-01       Impact factor: 2.745

5.  A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations.

Authors:  Vitaly V Ganusov; Rob J De Boer
Journal:  J R Soc Interface       Date:  2012-11-08       Impact factor: 4.118

Review 6.  Human T-lymphotropic virus type 1 (HTLV-1): persistence and immune control.

Authors:  Charles R M Bangham
Journal:  Int J Hematol       Date:  2003-11       Impact factor: 2.490

7.  Estimating average cellular turnover from 5-bromo-2'-deoxyuridine (BrdU) measurements.

Authors:  Rob J De Boer; Hiroshi Mohri; David D Ho; Alan S Perelson
Journal:  Proc Biol Sci       Date:  2003-04-22       Impact factor: 5.349

8.  Explicit kinetic heterogeneity: mathematical models for interpretation of deuterium labeling of heterogeneous cell populations.

Authors:  Vitaly V Ganusov; José A M Borghans; Rob J De Boer
Journal:  PLoS Comput Biol       Date:  2010-02-05       Impact factor: 4.475

9.  Quantifying T lymphocyte turnover.

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

10.  In vivo T lymphocyte dynamics in humans and the impact of human T-lymphotropic virus 1 infection.

Authors:  Becca Asquith; Yan Zhang; Angelina J Mosley; Catherine M de Lara; Diana L Wallace; Andrew Worth; Lambrini Kaftantzi; Kiran Meekings; George E Griffin; Yuetsu Tanaka; David F Tough; Peter C Beverley; Graham P Taylor; Derek C Macallan; Charles R M Bangham
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-01       Impact factor: 11.205

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