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A stochastic model of corneal epithelium maintenance and recovery following perturbation.
Moraki, E; Grima, R; Painter, K J.
Affiliation
  • Moraki E; Department of Mathematics, Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK. em281@hw.ac.uk.
  • Grima R; School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JH, Scotland, UK.
  • Painter KJ; Department of Mathematics, Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK.
J Math Biol ; 78(5): 1245-1276, 2019 04.
Article in En | MEDLINE | ID: mdl-30478759
ABSTRACT
Various biological studies suggest that the corneal epithelium is maintained by active stem cells located in the limbus, the so-called limbal epithelial stem cell hypothesis. While numerous mathematical models have been developed to describe corneal epithelium wound healing, only a few have explored the process of corneal epithelium homeostasis. In this paper we present a purposefully simple stochastic mathematical model based on a chemical master equation approach, with the aim of clarifying the main factors involved in the maintenance process. Model analysis provides a set of constraints on the numbers of stem cells, division rates, and the number of division cycles required to maintain a healthy corneal epithelium. In addition, our stochastic analysis reveals noise reduction as the epithelium approaches its homeostatic state, indicating robustness to noise. Finally, recovery is analysed in the context of perturbation scenarios.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Epithelium, Corneal / Models, Biological Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: J Math Biol Year: 2019 Document type: Article Affiliation country: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Epithelium, Corneal / Models, Biological Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: J Math Biol Year: 2019 Document type: Article Affiliation country: Reino Unido
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