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Living on Three Time Scales: The Dynamics of Plasma Cell and Antibody Populations Illustrated for Hepatitis A Virus

Overview of attention for article published in PLoS Computational Biology, March 2012
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Title
Living on Three Time Scales: The Dynamics of Plasma Cell and Antibody Populations Illustrated for Hepatitis A Virus
Published in
PLoS Computational Biology, March 2012
DOI 10.1371/journal.pcbi.1002418
Pubmed ID
Authors

Mathieu Andraud, Olivier Lejeune, Jammbe Z. Musoro, Benson Ogunjimi, Philippe Beutels, Niel Hens

Abstract

Understanding the mechanisms involved in long-term persistence of humoral immunity after natural infection or vaccination is challenging and crucial for further research in immunology, vaccine development as well as health policy. Long-lived plasma cells, which have recently been shown to reside in survival niches in the bone marrow, are instrumental in the process of immunity induction and persistence. We developed a mathematical model, assuming two antibody-secreting cell subpopulations (short- and long-lived plasma cells), to analyze the antibody kinetics after HAV-vaccination using data from two long-term follow-up studies. Model parameters were estimated through a hierarchical nonlinear mixed-effects model analysis. Long-term individual predictions were derived from the individual empirical parameters and were used to estimate the mean time to immunity waning. We show that three life spans are essential to explain the observed antibody kinetics: that of the antibodies (around one month), the short-lived plasma cells (several months) and the long-lived plasma cells (decades). Although our model is a simplified representation of the actual mechanisms that govern individual immune responses, the level of agreement between long-term individual predictions and observed kinetics is reassuringly close. The quantitative assessment of the time scales over which plasma cells and antibodies live and interact provides a basis for further quantitative research on immunology, with direct consequences for understanding the epidemiology of infectious diseases, and for timing serum sampling in clinical trials of vaccines.

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Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Netherlands 1 <1%
Belgium 1 <1%
Unknown 100 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 27%
Student > Ph. D. Student 22 21%
Student > Postgraduate 10 10%
Student > Bachelor 6 6%
Professor > Associate Professor 6 6%
Other 20 19%
Unknown 12 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 22%
Medicine and Dentistry 18 17%
Biochemistry, Genetics and Molecular Biology 13 13%
Mathematics 12 12%
Immunology and Microbiology 8 8%
Other 19 18%
Unknown 11 11%