Literature DB >> 12964991

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

Becca Asquith1, Charles R M Bangham.   

Abstract

Mathematics is a useful tool in the analysis and understanding of population dynamic aspects of the immune response. However, the power of mathematical modelling in immunology is frequently limited by the shortage of experimental data. Here, we review the contribution of mathematics to two areas of immunology. We highlight the problem caused by lack of knowledge of the system, which can greatly restrict the use of mathematics and lead to errors caused by model-specific results.

Mesh:

Year:  2003        PMID: 12964991      PMCID: PMC1691432          DOI: 10.1098/rspb.2003.2386

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  27 in total

1.  Response of naïve and memory CD8+ T cells to antigen stimulation in vivo.

Authors:  H Veiga-Fernandes; U Walter; C Bourgeois; A McLean; B Rocha
Journal:  Nat Immunol       Date:  2000-07       Impact factor: 25.606

2.  Increased turnover of T lymphocytes in HIV-1 infection and its reduction by antiretroviral therapy.

Authors:  H Mohri; A S Perelson; K Tung; R M Ribeiro; B Ramratnam; M Markowitz; R Kost; A Hurley; L Weinberger; D Cesar; M K Hellerstein; D D Ho
Journal:  J Exp Med       Date:  2001-11-05       Impact factor: 14.307

Review 3.  Lymphocyte kinetics: the interpretation of labelling data.

Authors:  Becca Asquith; Christophe Debacq; Derek C Macallan; Luc Willems; Charles R M Bangham
Journal:  Trends Immunol       Date:  2002-12       Impact factor: 16.687

4.  The dynamics of T-cell fratricide: application of a robust approach to mathematical modelling in immunology.

Authors:  Becca Asquith; Charles R M Bangham
Journal:  J Theor Biol       Date:  2003-05-07       Impact factor: 2.691

Review 5.  The virology and immunobiology of lymphocytic choriomeningitis virus infection.

Authors:  M J Buchmeier; R M Welsh; F J Dutko; M B Oldstone
Journal:  Adv Immunol       Date:  1980       Impact factor: 3.543

6.  Fratricide among CD8(+) T lymphocytes naturally infected with human T cell lymphotropic virus type I.

Authors:  E Hanon; J C Stinchcombe; M Saito; B E Asquith; G P Taylor; Y Tanaka; J N Weber; G M Griffiths; C R Bangham
Journal:  Immunity       Date:  2000-11       Impact factor: 31.745

7.  Polygenic control of human T lymphotropic virus type I (HTLV-I) provirus load and the risk of HTLV-I-associated myelopathy/tropical spastic paraparesis.

Authors:  Alison M Vine; Aviva D Witkover; Alun L Lloyd; Katie J M Jeffery; Asna Siddiqui; Sara E F Marshall; Mike Bunce; Nobutaka Eiraku; Shuji Izumo; Koichiro Usuku; Mitsuhiro Osame; Charles R M Bangham
Journal:  J Infect Dis       Date:  2002-09-13       Impact factor: 5.226

8.  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

9.  The transactivator gene of human T-cell leukemia virus type I is more variable within and between healthy carriers than patients with tropical spastic paraparesis.

Authors:  S Niewiesk; S Daenke; C E Parker; G Taylor; J Weber; S Nightingale; C R Bangham
Journal:  J Virol       Date:  1994-10       Impact factor: 5.103

10.  Lifespan of human lymphocyte subsets defined by CD45 isoforms.

Authors:  C A Michie; A McLean; C Alcock; P C Beverley
Journal:  Nature       Date:  1992-11-19       Impact factor: 49.962

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  5 in total

Review 1.  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

2.  Quantifying T lymphocyte turnover.

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

3.  How does HTLV-I persist despite a strong cell-mediated immune response?

Authors:  Becca Asquith; Charles R M Bangham
Journal:  Trends Immunol       Date:  2007-11-26       Impact factor: 16.687

4.  Numerical solutions for a model of tissue invasion and migration of tumour cells.

Authors:  M Kolev; B Zubik-Kowal
Journal:  Comput Math Methods Med       Date:  2010-12-30       Impact factor: 2.238

5.  The cycle of EBV infection explains persistence, the sizes of the infected cell populations and which come under CTL regulation.

Authors:  Jared B Hawkins; Edgar Delgado-Eckert; David A Thorley-Lawson; Michael Shapiro
Journal:  PLoS Pathog       Date:  2013-10-17       Impact factor: 6.823

  5 in total

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