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10.1186/s12918-015-0235-2

http://scihub22266oqcxt.onion/10.1186/s12918-015-0235-2
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C4672575!4672575!26642882
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suck abstract from ncbi


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pmid26642882      BMC+Syst+Biol 2015 ; 9 (ä): ä
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  • Cellular automaton-based model for radiation-induced bystander effects #MMPMID26642882
  • Hattori Y; Yokoya A; Watanabe R
  • BMC Syst Biol 2015[]; 9 (ä): ä PMID26642882show ga
  • Background: 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. Methods: 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. Results: 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. Conclusions: 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. Electronic supplementary material: The online version of this article (doi:10.1186/s12918-015-0235-2) contains supplementary material, which is available to authorized users.
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