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Cellular automaton-based model for radiation-induced bystander effects

Overview of attention for article published in BMC Systems Biology, December 2015
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Title
Cellular automaton-based model for radiation-induced bystander effects
Published in
BMC Systems Biology, December 2015
DOI 10.1186/s12918-015-0235-2
Pubmed ID
Authors

Yuya Hattori, Akinari Yokoya, Ritsuko Watanabe

Abstract

The radiation-induced bystander effect is a biological response observed in non-irradiated cells surrounding an irradiated cell. The bystander effect is known to be induced by two intercellular signaling pathways, the medium-mediated pathway (MDP) and the gap junctional pathway (GJP). To investigate the relative contribution of each signaling pathway, we have developed a mathematical model of the cellular response through these two pathways, with a particular focus on cell-cycle modification. The model is based on a cellular automaton and consists of four components: (1) irradiation, (2) generation and diffusion of intercellular signals, (3) induction of DNA double-strand breaks (DSBs), and (4) cell-cycle modification or cell death. The intercellular signals are generated in and released from irradiated cells. The signals through the MDP and the GJP are modeled independently based on diffusion equations. The irradiation and both signals raise the number of DSBs, which determines transitions of cellular states, such as cell-cycle arrest or cell death. Our model reproduced fairly well previously reported experimental data on the number of DSBs and cell survival curves. We examined how radiation dose and intercellular signaling dynamically affect the cell cycle. The analysis of model dynamics for the bystander cells revealed that the number of arrested cells did not increase linearly with dose. Arrested cells were more efficiently accumulated by the GJP than by the MDP. We present here a mathematical model that integrates various bystander responses, such as MDP and GJP signaling, DSB induction, cell-cycle arrest, and cell death. Because it simulates spatial and temporal conditions of irradiation and cellular characteristics, our model will be a powerful tool to predict dynamical radiobiological responses of a cellular population in which irradiated and non-irradiated cells co-exist.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Student > Master 4 17%
Researcher 4 17%
Student > Doctoral Student 3 13%
Professor > Associate Professor 2 8%
Other 1 4%
Unknown 4 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 17%
Physics and Astronomy 3 13%
Mathematics 2 8%
Agricultural and Biological Sciences 2 8%
Environmental Science 2 8%
Other 7 29%
Unknown 4 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 December 2015.
All research outputs
#4,961,551
of 6,697,548 outputs
Outputs from BMC Systems Biology
#571
of 789 outputs
Outputs of similar age
#190,048
of 281,300 outputs
Outputs of similar age from BMC Systems Biology
#27
of 34 outputs
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