Stochastic modeling of oligodendrocyte generation in cell culture: Model validation with time-lapse data

Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA.
Theoretical Biology and Medical Modelling (Impact Factor: 0.95). 02/2006; 3(1):21. DOI: 10.1186/1742-4682-3-21
Source: PubMed


The purpose of this paper is two-fold. The first objective is to validate the assumptions behind a stochastic model developed earlier by these authors to describe oligodendrocyte generation in cell culture. The second is to generate time-lapse data that may help biomathematicians to build stochastic models of cell proliferation and differentiation under other experimental scenarios.
Using time-lapse video recording it is possible to follow the individual evolutions of different cells within each clone. This experimental technique is very laborious and cannot replace model-based quantitative inference from clonal data. However, it is unrivalled in validating the structure of a stochastic model intended to describe cell proliferation and differentiation at the clonal level. In this paper, such data are reported and analyzed for oligodendrocyte precursor cells cultured in vitro.
The results strongly support the validity of the most basic assumptions underpinning the previously proposed model of oligodendrocyte development in cell culture. However, there are some discrepancies; the most important is that the contribution of progenitor cell death to cell kinetics in this experimental system has been underestimated.

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Available from: Margot Mayer-Proschel, Oct 08, 2015
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    • "The former process was used to analyze the division of the so-called O-2A progenitor cells and their differentiation into terminally differentiated oligodendrocytes by Hyrien et al (2005a), where dissimilar distributions were used to model the distributions of the time to occurrence of these two events. An analysis of experimental data on this cell system suggested the need for such a feature (Hyrien et al, 2005a), and time-lapse cinematography data provided further evidence in support of the proposed model extension (Hyrien et al, 2006). Of note, the above process reduces to the " usual " multi-type Markov process (Athreya and Ney, 1972) if λ k,x = λ k for every x ∈ k . "
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