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Patterns of Mesenchymal Condensation in a Multiscale, Discrete Stochastic Model

Overview of attention for article published in PLoS Computational Biology, April 2007
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Title
Patterns of Mesenchymal Condensation in a Multiscale, Discrete Stochastic Model
Published in
PLoS Computational Biology, April 2007
DOI 10.1371/journal.pcbi.0030076
Pubmed ID
Authors

Scott Christley, Mark S Alber, Stuart A Newman

Abstract

Cells of the embryonic vertebrate limb in high-density culture undergo chondrogenic pattern formation, which results in the production of regularly spaced "islands" of cartilage similar to the cartilage primordia of the developing limb skeleton. The first step in this process, in vitro and in vivo, is the generation of "cell condensations," in which the precartilage cells become more tightly packed at the sites at which cartilage will form. In this paper we describe a discrete, stochastic model for the behavior of limb bud precartilage mesenchymal cells in vitro. The model uses a biologically motivated reaction-diffusion process and cell-matrix adhesion (haptotaxis) as the bases of chondrogenic pattern formation, whereby the biochemically distinct condensing cells, as well as the size, number, and arrangement of the multicellular condensations, are generated in a self-organizing fashion. Improving on an earlier lattice-gas representation of the same process, it is multiscale (i.e., cell and molecular dynamics occur on distinct scales), and the cells are represented as spatially extended objects that can change their shape. The authors calibrate the model using experimental data and study sensitivity to changes in key parameters. The simulations have disclosed two distinct dynamic regimes for pattern self-organization involving transient or stationary inductive patterns of morphogens. The authors discuss these modes of pattern formation in relation to available experimental evidence for the in vitro system, as well as their implications for understanding limb skeletal patterning during embryonic development.

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Geographical breakdown

Country Count As %
Japan 2 2%
Netherlands 1 1%
India 1 1%
United Kingdom 1 1%
Switzerland 1 1%
Spain 1 1%
Canada 1 1%
United States 1 1%
Croatia 1 1%
Other 0 0%
Unknown 79 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 22%
Student > Ph. D. Student 18 20%
Professor > Associate Professor 13 15%
Professor 11 12%
Student > Master 8 9%
Other 12 13%
Unknown 7 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 35%
Biochemistry, Genetics and Molecular Biology 15 17%
Engineering 13 15%
Medicine and Dentistry 6 7%
Materials Science 4 4%
Other 12 13%
Unknown 8 9%