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A biologically based mathematical model for spontaneous and ionizing radiation cataractogenesis

Cataracts have long been known, but a biomathematical model is still unavailable for cataratogenesis. There has been a renewed interest in ionizing radiation cataracts because the recent international recommendation of the reduced lens dose limit stimulated the discussion toward its regulatory imple...

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Bibliographic Details
Published in:PloS one 2019-08, Vol.14 (8), p.e0221579-e0221579
Main Authors: Sakashita, Tetsuya, Sato, Tatsuhiko, Hamada, Nobuyuki
Format: Article
Language:English
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Summary:Cataracts have long been known, but a biomathematical model is still unavailable for cataratogenesis. There has been a renewed interest in ionizing radiation cataracts because the recent international recommendation of the reduced lens dose limit stimulated the discussion toward its regulatory implementation in various countries. Nevertheless, a relationship between radiation (dose and dose rate) and response (e.g., incidence, onset and progression) remains incompletely understood, raising the need for a risk-predictive mathematical model. We here report for the first time an in silico model for cataractogenesis. First, a simplified cell proliferation model was developed for human lens growth based on stem and progenitor cell proliferation as well as epithelial-fiber cell differentiation. Then, a model for spontaneous cataractogenesis was developed to reproduce the human data on a relationship between age and cataract incidence. Finally, a model for radiation cataractogenesis was developed that can reproduce the human data on a relationship between dose and cataract onset at various ages, which was further applied to estimate cataract incidence following chronic lifetime exposure. The model can serve as the foundation for further development of the risk-predictive model for cataractogenesis along with additional considerations of various biological mechanisms and epidemiological datasets.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0221579