A review: Development of a microdose model for analysis of adaptive response and bystander dose response behavior

Biophysical Modeling of the Ionizing Radiation Influence on Cells Using the Stochastic (Monte Carlo) and Deterministic (Analytical) Approaches

This review article describes our simplified biophysical model for the response of a group of cells to ionizing radiation. The model, which is a product of 10 years of studies, acts as (a) a comprehensive stochastic approach based on the Monte Carlo simulation with a probability tree and (b) the thereof derived detailed deterministic models describing the selected biophysical and radiobiological phenomena in an analytical manner. Specifically, the presented model describes effects such as the risk of neoplastic transformation of cells relative to the absorbed radiation dose, the dynamics of tumor development, the priming dose effect (also called the Raper-Yonezawa effect) based on the introduced adaptive response approach, and the bystander effect. The model is also modifiable depending on users' potential needs.

Computational modeling of cellular effects post-irradiation with low- and high-let particles and different absorbed doses

The use of computational methods to improve the understanding of biological responses to various types of radiation is an approach where multiple parameters can be modelled and a variety of data is generated. This study compares cellular effects modelled for low absorbed doses against high absorbed doses. The authors hypothesized that low and high absorbed doses would contribute to cell killing via different mechanisms, potentially impacting on targeted tumour radiotherapy outcomes. Cellular kinetics following irradiation with selective low- and high-linear energy transfer (LET) particles were investigated using the Virtual Cell (VC) radiobiology algorithm. Two different cell types were assessed using the VC radiobiology algorithm: human fibroblasts and human crypt cells. The results showed that at lower doses (0.01 to 0.2 Gy), all radiation sources used were equally able to induce cell death (p>0.05, ANOVA). On the other hand, at higher doses (1.0 to 8.0 Gy), the radiation response was LET and dose dependent (p<0.05, ANOVA). The data obtained suggests that the computational methods used might provide some insight into the cellular effects following irradiation. The results also suggest that it may be necessary to re-evaluate cellular radiation-induced effects, particularly at low doses that could affect therapeutic effectiveness.

A stochastic markov model of cellular response to radiation

A stochastic model based on the Markov Chain Monte Carlo process is used to describe responses to ionizing radiation in a group of cells. The results show that where multiple relationships linearly depending on the dose are introduced, the overall reaction shows a threshold, and, generally, a non-linear response. Such phenomena have been observed and reported in a number of papers. The present model permits the inclusion of adaptive responses and bystander effects that can lead to hormetic effects. In addition, the model allows for incorporating various time-dependent phenomena. Essentially, all known biological effects can be reproduced using the proposed model.

Human Lung Cancer Risks from Radon - Part III - Evidence of Influence of Combined Bystander and Adaptive Response Effects on Radon Case-Control Studies - A Microdose Analysis

Since the publication of the BEIR VI (1999) report on health risks from radon, a significant amount of new data has been published showing various mechanisms that may affect the ultimate assessment of radon as a carcinogen, in particular the potentially deleterious Bystander Effect (BE) and the potentially beneficial Adaptive Response radio-protection (AR). The case-control radon lung cancer risk data of the pooled 13 European countries radon study (Darby et al 2005, 2006) and the 8 North American pooled study (Krewski et al 2005, 2006) have been evaluated. The large variation in the odds ratios of lung cancer from radon risk is reconciled, based on the large variation in geological and ecological conditions and variation in the degree of adaptive response radio-protection against the bystander effect induced lung damage. The analysis clearly shows Bystander Effect radon lung cancer induction and Adaptive Response reduction in lung cancer in some geographical regions. It is estimated that for radon levels up to about 400 Bq m(-3) there is about a 30% probability that no human lung cancer risk from radon will be experienced and a 20% probability that the risk is below the zero-radon, endogenic spontaneous or perhaps even genetically inheritable lung cancer risk rate. The BEIR VI (1999) and EPA (2003) estimates of human lung cancer deaths from radon are most likely significantly excessive. The assumption of linearity of risk, by the Linear No-Threshold Model, with increasing radon exposure is invalid.

Human lung cancer risks from radon - part I - influence from bystander effects - a microdose analysis

Since the publication of the BEIR VI report in 1999 on health risks from radon, a significant amount of new data has been published showing various mechanisms that may affect the ultimate assessment of radon as a carcinogen, at low domestic and workplace radon levels, in particular the Bystander Effect (BE) and the Adaptive Response radio-protection (AR). We analyzed the microbeam and broadbeam alpha particle data of Miller et al. (1995, 1999), Zhou et al. (2001, 2003, 2004), Nagasawa and Little (1999, 2002), Hei et al. (1999), Sawant et al. (2001a) and found that the shape of the cellular response to alphas is relatively independent of cell species and LET of the alphas. The same alpha particle traversal dose response behavior should be true for human lung tissue exposure to radon progeny alpha particles. In the Bystander Damage Region of the alpha particle response, there is a variation of RBE from about 10 to 35. There is a transition region between the Bystander Damage Region and Direct Damage Region of between one and two microdose alpha particle traversals indicating that perhaps two alpha particle "hits" are necessary to produce the direct damage. Extrapolation of underground miners lung cancer risks to human risks at domestic and workplace levels may not be valid.

Human Lung Cancer Risks from Radon - Part II - Influence from Combined Adaptive Response and Bystander Effects - A Microdose Analysis

In the prior Part I, the potential influence of the low level alpha radiation induced bystander effect (BE) on human lung cancer risks was examined. Recent analysis of adaptive response (AR) research results with a Microdose Model has shown that single low LET radiation induced charged particles traversals through the cell nucleus activates AR. We have here conducted an analysis based on what is presently known about adaptive response and the bystander effect (BE) and what new research is needed that can assist in the further evaluation human cancer risks from radon. We find that, at the UNSCEAR (2000) worldwide average human exposures from natural background and man-made radiations, the human lung receives about a 25% adaptive response protection against the radon alpha bystander damage. At the UNSCEAR (2000) minimum range of background exposure levels, the lung receives minimal AR protection but at higher background levels, in the high UNSCEAR (2000) range, the lung receives essentially 100% protection from both the radon alpha damage and also the endogenic, spontaneously occurring, potentially carcinogenic, lung cellular damage.

The healthy worker effect and nuclear industry workers

The linear no-threshold (LNT) dose-effect relationship has been consistently used by most radiation epidemiologists to estimate cancer mortality risk. The large scattering of data by International Agency for Research on Cancer, IARC (Vrijheid et al. 2007; Therry-Chef et al. 2007; Cardis et al. 2007), interpreted in accordance with LNT, has been previously demonstrated (Fornalski and Dobrzyński 2009). Using conventional and Bayesian methods the present paper demonstrates that the standard mortality ratios (SMRs), lower in the IARC cohort of exposed nuclear workers than in the non exposed group, should be considered as a hormetic effect, rather than a healthy worker effect (HWE) as claimed by the IARC group.

The dose window for radiation-induced protective adaptive responses

Adaptive responses to low doses of low LET radiation occur in all organisms thus far examined, from single cell lower eukaryotes to mammals. These responses reduce the deleterious consequences of DNA damaging events, including radiation-induced or spontaneous cancer and non-cancer diseases in mice. The adaptive response in mammalian cells and mammals operates within a certain window that can be defined by upper and lower dose thresholds, typically between about 1 and 100 mGy for a single low dose rate exposure. However, these thresholds for protection are not a fixed function of total dose, but also vary with dose rate, additional radiation or non-radiation stressors, tissue type and p53 functional status. Exposures above the upper threshold are generally detrimental, while exposures below the lower threshold may or may not increase either cancer or non-cancer disease risk.

A perspective on the scientific, philosophical, and policy dimensions of hormesis

The hormesis concept has broad implications for biology and the biomedical sciences. This perspective on hormesis concentrates on toxicology and toxicological risk assessment and secondarily explores observations from other fields. It considers the varied manifestations of hormesis in the context of a broad family of biological stress responses. Evidence for hormesis is reviewed, and the hormesis model is contrasted with more widely accepted dose-response models in toxicology: a linear nonthreshold (LNT) model for mutagenesis and carcinogenesis, and a threshold model for most other toxicologic effects. Scientific, philosophical, and political objections to the hormesis concept are explored, and complications in the hormesis concept are analyzed. The review concludes with a perspective on the current state of hormesis and challenges that the hormesis model poses for risk assessment.

"Protective bystander effects simulated with the state-vector model"--HeLa x skin exposure to Cs not protective bystander response but mammogram and diagnostic X-rays are

The recent Dose Response journal article "Protective Bystander Effects Simulated with the State-Vector Model" (Schollnberger and Eckl 2007) identified the suppressive (below natural occurring, zero primer dose, spontaneous level) dose response for HeLa x skin exposure to (137)Cs gamma rays (Redpath et al 2001) as a protective Bystander Effect (BE) behavior. I had previously analyzed the Redpath et al (2001) data with a Microdose Model and conclusively showed that the suppressive response was from Adaptive Response (AR) radio-protection (Leonard 2005, 2007a). The significance of my microdose analysis has been that low LET radiation induced single (i.e. only one) charged particle traversals through a cell can initiate a Poisson distributed activation of AR radio-protection. The purpose of this correspondence is to clarify the distinctions relative to the BE and the AR behaviors for the Redpath groups (137)Cs data, show conversely however that the Redpath group data for mammography (Ko et al 2004) and diagnostic (Redpath et al 2003) X-rays do conclusively reflect protective bystander behavior and also herein emphasize the need for radio-biologist to apply microdosimetry in planning and analyzing their experiments for BE and AR. Whether we are adamantly pro-LNT, adamantly anti-LNT or, like most of us, just simple scientists searching for the truth in radio-biology, it is important that we accurately identify our results, especially when related to the LNT hypothesis controversy.