Protective Bystander Effects Simulated with the State-Vector Model

Abstract

Apoptosis induced in non-hit bystander cells is an important biological mechanism which operates after exposure to low doses of low-LET radiation. This process was implemented into a deterministic multistage model for in vitro neoplastic transformation: the State-Vector Model (SVM). The new model is tested on two data sets that show a reduction of the transformation frequency below the spontaneous level after exposure of the human hybrid cell line CGL1 to low doses of gamma-radiation. Stronger protective effects are visible in the data for delayed plating while the data for immediate plating show more of an LNT-like dose-response curve. It is shown that the model can describe both data sets. The calculation of the time-dependent numerical solution of the model also allows to obtain information about the time-dependence of the protective apoptosis-mediated process after low dose exposures. These findings are compared with experimental observations after high dose exposures.

Mammogram and diagnostic X-rays–evidence of protective Bystander, Adaptive Response (AR) radio-protection and AR retention at high dose levels

“…In our analysis (Leonard 2005(Leonard , 2007a, we saw no evidence of either a protective or deleterious BE for the Redpath 137 Cs data. Others have mistakenly claimed a BE in the Redpath et al 137 Cs data (Schollnberger and Ecki 2007) but our Microdose Model clearly shows, from the 137 Cs data in Figures 3A, 3B, 3C, that the sub-spontaneous response is simply the expected AR radio-protection.…”

“…We show by microdose analysis that the protective Bystander Effect, observed for the 30 kVp mammography X-rays, could not have been observed in these other studies, except for diagnostic X-rays, since the lowest administered doses were above the Specific Energy deposition per Hit, 5z 1 4, values. This provides opposition to the premise reported by others (Schollnberger and Ecki 2007) that the 137 Cs exposures exhibit a protective Bystander Effect from cellular apoptosis mechanisms. .…”

Low dose radiation and intercellular induction of apoptosis: potential implications for the control of oncogenesis

“…Non-targeted effects (bystander effects) have been reported for micronucleus formation , Shao et al 2005, mutagenic effects (Zhou et al 2000), sister chromatide exchange (Nagasawa & Little 1992, Deshpande et al 1996, genomic instability (Kadhim et al 1992, Morgan et al 1996, Limoli et al 1999, Limoli & Giedzinski 2003, Mothersill & Seymour 2003, Hooker et al 2004, Huang et al 2007, reduction in clonogenic survival (Mothersill & Seymour 1997), apoptosis (Kadhim et al 1995, Kadhim 2003, Lyng et al 2006, increase in tumorigenic potential (Barcellos-Hoff & Ravani 2000, Barcellos-Hoff 2001, decrease in observable transformation frequency (Azzam et al 1994, Pant et al 2003, Redpath 2005, Ko et al 2006, resistance against renewed irradiation with a challenging dose (Hooker et al 2004, Prise 2006, Zeng et al 2006) and removal of transformed cells via intercellular induction of apoptosis (Portess et al 2007). The decrease in detectable transformation frequency and removal of transformed cells through low dose radiation effects has been included into models for the mathematical simulation of multistage oncogenesis (Schö llnberger et al 2002, Scott et al 2003, Scott 2004, Schö llnberger & Eckl 2007.…”

Issues and challenges of space radiation risk assessment in manned deep space exploration missions

“…模型(state-vector model) [68] , B&D模型(bystander and direct model) [69] , 旁效应扩散模型(bystander diffusion model) [70] , 三维点阵模型(3D lattice model) [70] 等, 以及 描述基因组不稳定性的两阶段、三阶段及多阶段肿瘤 模型(multistage clonal expansion model) [71] [45] . Preston等人 [75] 利用近似调整泊松回归 模型的方法, 比较了多种剂量效应模型对辐射暴露诱 的算术平均计算实体癌(solid cancers)风险, 使用EAR 模型计算白血病(leukemia)风险 [35] .…”