Modeling of single cell cancer transformation using phase transition theory: application of the Avrami equation.

The nucleation and growth theory, described by the Avrami equation (also called Johnson-Mehl-Avrami-Kolmogorov equation), and usually used to describe crystallization and nucleation processes in condensed matter physics, was applied in the present paper to cancer physics. This can enhance the popular multi-hit model of carcinogenesis to volumetric processes of single cell's DNA neoplastic transformation. The presented approach assumes the transforming system as a DNA chain including many oncogenic mutations. Finally, the probability function of the cell's cancer transformation is directly related to the number of oncogenic mutations. This creates a universal sigmoidal probability function of cancer transformation of single cells, as observed in the kinetics of nucleation and growth, a special case of a phase transition process. The proposed model, which represents a different view on the multi-hit carcinogenesis approach, is tested on clinical data concerning gastric cancer. The results also show that cancer transformation follows DNA fractal geometry.

The radiation adaptive response and priming dose influence: the quantification of the Raper-Yonezawa effect and its three-parameter model for postradiation DNA lesions and mutations.

The priming dose effect, called also the Raper-Yonezawa effect or simply the Yonezawa effect, is a special case of the radiation adaptive response phenomenon (radioadaptation), which refers to: (a) faster repair of direct DNA lesions (damage), and (b) DNA mutation frequency reduction after irradiation, by applying a small priming (conditioning) dose prior to the high detrimental (challenging) one. This effect is observed in many (but not all) radiobiological experiments which present the reduction of lesion, mutation or even mortality frequency of the irradiated cells or species. Additionally, the multi-parameter model created by Dr. Yonezawa and collaborators tried to explain it theoretically based on experimental data on the mortality of mice with chronic internal irradiation. The presented paper proposes a new theoretical approach to understanding and explaining the priming dose effect: it starts from the radiation adaptive response theory and moves to the three-parameter model, separately for two previously mentioned situations: creation of fast (lesions) and delayed damage (mutations). The proposed biophysical model was applied to experimental data-lesions in human lymphocytes and chromosomal inversions in mice-and was shown to be able to predict the Yonezawa effect for future investigations. It was also found that the strongest radioadaptation is correlated with the weakest cellular radiosensitivity. Additional discussions were focussed on more general situations where many small priming doses are used.

Electron momentum density of hexagonal Zn studied by high-resolution Compton scattering.

High-resolution (0.12 a.u.) electron momentum density projections (Compton profiles) of a hexagonal Zn single crystal have been measured along five high-symmetry directions in reciprocal space. The experiment was performed with the use of 115.6 keV synchrotron radiation on the BL08W station at SPring-8. The quality of the measured Compton profiles is significantly better than that of previous medium- and high-resolution data. The experimental data were compared with the corresponding theoretical Korringa-Kohn-Rostoker (KKR) and density functional theory (DFT) calculations. Some minor and major differences between the two theoretical band-structure calculations have been observed. However, the good quality experimental results indicate their better agreement with DFT.

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.

Analysis of Indoor Radon Data Using Bayesian, Random Binning, and Maximum Entropy Methods.

Three statistical methods: Bayesian, randomized data binning and Maximum Entropy Method (MEM) are described and applied in the analysis of US radon data taken from the US registry. Two confounding factors-elevation of inhabited dwellings, and UVB (ultra-violet B) radiation exposure-were considered to be most correlated with the frequency of lung cancer occurrence. MEM was found to be particularly useful in extracting meaningful results from epidemiology data containing such confounding factors. In model testing, MEM proved to be more effective than the least-squares method (even via Bayesian analysis) or multi-parameter analysis, routinely applied in epidemiology. Our analysis of the available residential radon epidemiology data consistently demonstrates that the relative number of lung cancers decreases with increasing radon concentrations up to about 200 Bq/m3, also decreasing with increasing altitude at which inhabitants live. Correlation between UVB intensity and lung cancer has also been demonstrated.

Formation of a partially oxidized gold compound by electrolytic oxidation of the solvoluminescent gold(I) trimer, Au3(MeN=COMe)3.

The trinuclear complex, Au(3)(MeN=COMe)(3), which displays a number of remarkable properties including solvoluminescence, has been found to undergo electrochemical oxidation with the deposition of long, thin needles on the electrode surface. The electro-deposition process has been studied by cyclic voltammetry, chronoamperometry, and quartz crystal microbalance techniques. The composition of the electrically conducting needles has been determined to be [Au(3)(MeN=COMe)(3)](ClO(4))(0.34) by two complementary methods. The related complex Au(3)(PhCH(2)N=COMe)(3) underwent oxidation at a significantly more positive potential and did not produce a deposit on the electrode surface.

Commentary regarding "Residential radon and small cell lung cancer. A systematic review".

Rodríguez-Martínez et al. proposed a systematic review of residential radon and small cell lung cancer. Although this is a noteworthy project, it must utilize the complete set of radon data and provide a rigorous analysis of these data. The authors utilized a selected set of radon data, and do not utilize rigorous statistical methods in relating the effects of radon and small cell lung cancer. These limitations detract from the conclusions of the systematic review.

Meta-analysis of thirty-two case-control and two ecological radon studies of lung cancer.

A re-analysis has been carried out of thirty-two case-control and two ecological studies concerning the influence of radon, a radioactive gas, on the risk of lung cancer. Three mathematically simplest dose-response relationships (models) were tested: constant (zero health effect), linear, and parabolic (linear-quadratic). Health effect end-points reported in the analysed studies are odds ratios or relative risk ratios, related either to morbidity or mortality. In our preliminary analysis, we show that the results of dose-response fitting are qualitatively (within uncertainties, given as error bars) the same, whichever of these health effect end-points are applied. Therefore, we deemed it reasonable to aggregate all response data into the so-called Relative Health Factor and jointly analysed such mixed data, to obtain better statistical power. In the second part of our analysis, robust Bayesian and classical methods of analysis were applied to this combined dataset. In this part of our analysis, we selected different subranges of radon concentrations. In view of substantial differences between the methodology used by the authors of case-control and ecological studies, the mathematical relationships (models) were applied mainly to the thirty-two case-control studies. The degree to which the two ecological studies, analysed separately, affect the overall results when combined with the thirty-two case-control studies, has also been evaluated. In all, as a result of our meta-analysis of the combined cohort, we conclude that the analysed data concerning radon concentrations below ~1000 Bq/m3 (~20 mSv/year of effective dose to the whole body) do not support the thesis that radon may be a cause of any statistically significant increase in lung cancer incidence.

Modeling of Irradiated Cell Transformation: Dose- and Time-Dependent Effects.

We report here on various biophysical aspects of irradiated cells, beginning with a phenomenological description of radiation-induced cancer cells. This description includes detrimental factors such as chromosomal aberrations, as well as beneficial factors, such as adaptive response. Also discussed here is the dose- and time-dependent evolution of cancer cells using a purely mathematical approach. The general dose-response shape, which is sigmoidal, is shown to be modified by such mechanisms as adaptive response or bystander effect. The many aspects of the sigmoid function, which most appropriately demonstrates the relationships among irradiated organisms, are discussed here as well. Finally, the balance equation is presented as the most general relationship for irradiated cell behavior.

Atomic Bomb Survivors Life-Span Study: Insufficient Statistical Power to Select Radiation Carcinogenesis Model.

The atomic bomb survivors life-span study (LSS) is often claimed to support the linear no-threshold hypothesis (LNTH) of radiation carcinogenesis. This paper shows that this claim is baseless. The LSS data are equally or better described by an s-shaped dependence on radiation exposure with a threshold of about 0.3 Sievert (Sv) and saturation level at about 1.5 Sv. A Monte-Carlo simulation of possible LSS outcomes demonstrates that, given the weak statistical power, LSS cannot provide support for LNTH. Even if the LNTH is used at low dose and dose rates, its estimation of excess cancer mortality should be communicated as 2.5% per Sv, i.e., an increase of cancer mortality from about 20% spontaneous mortality to about 22.5% per Sv, which is about half of the usually cited value. The impact of the "neutron discrepancy problem" - the apparent difference between the calculated and measured values of neutron flux in Hiroshima - was studied and found to be marginal. Major revision of the radiation risk assessment paradigm is required.

Cancer Mortality Among People Living in Areas With Various Levels of Natural Background Radiation.

There are many places on the earth, where natural background radiation exposures are elevated significantly above about 2.5 mSv/year. The studies of health effects on populations living in such places are crucially important for understanding the impact of low doses of ionizing radiation. This article critically reviews some recent representative literature that addresses the likelihood of radiation-induced cancer and early childhood death in regions with high natural background radiation. The comparative and Bayesian analysis of the published data shows that the linear no-threshold hypothesis does not likely explain the results of these recent studies, whereas they favor the model of threshold or hormesis. Neither cancers nor early childhood deaths positively correlate with dose rates in regions with elevated natural background radiation.

Commentary: ethical issues of current health-protection policies on low-dose ionizing radiation.

The linear no-threshold (LNT) model of ionizing-radiation-induced cancer is based on the assumption that every radiation dose increment constitutes increased cancer risk for humans. The risk is hypothesized to increase linearly as the total dose increases. While this model is the basis for radiation safety regulations, its scientific validity has been questioned and debated for many decades. The recent memorandum of the International Commission on Radiological Protection admits that the LNT-model predictions at low doses are "speculative, unproven, undetectable and 'phantom'." Moreover, numerous experimental, ecological, and epidemiological studies show that low doses of sparsely-ionizing or sparsely-ionizing plus highly-ionizing radiation may be beneficial to human health (hormesis/adaptive response). The present LNT-model-based regulations impose excessive costs on the society. For example, the median-cost medical program is 5000 times more cost-efficient in saving lives than controlling radiation emissions. There are also lives lost: e.g., following Fukushima accident, more than 1000 disaster-related yet non-radiogenic premature deaths were officially registered among the population evacuated due to radiation concerns. Additional negative impacts of LNT-model-inspired radiophobia include: refusal of some patients to undergo potentially life-saving medical imaging; discouragement of the study of low-dose radiation therapies; motivation for radiological terrorism and promotion of nuclear proliferation.

The cancer mortality in high natural radiation areas in poland.

The cancer mortality ratios (CMRs) in Poland in high and low level radiation areas were analyzed based on information from national cancer registry. Presented ecological study concerned six regions, extending from the largest administration areas (a group of voivodeships), to the smallest regions (single counties). The data show that the relative risk of cancer deaths is lower in the higher radiation level areas. The decrease by 1.17%/mSv/year (p = 0.02) of all cancer deaths and by 0.82%/mSv/year (p = 0.2) of lung cancers only are observed.Tribute to Prof. Zbigniew Jaworowski (1927-2011).

Pooled Bayesian analysis of twenty-eight studies on radon induced lung cancers.

The influence of ionizing radiation of (222)Rn and its progeny on lung cancer risks that were published in 28 papers was re-analyzed using seven alternative dose-response models. The risks of incidence and mortality were studied in two ranges of low annual radiation dose: 0-70 mSv per year (391 Bq m(-3)) and 0-150 mSv per year (838 Bq m(-3)). Assumption-free Bayesian statistical methods were used. The analytical results demonstrate that the published incidence and mortality data do not show that radiation dose is associated with increased risk in this range of doses. This conclusion is based on the observation that the model assuming no dependence of the lung cancer induction on the radiation doses is at least ∼90 times more likely to be true than the other models tested, including the linear no-threshold (LNT) model.

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.

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 Dobrzynski 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.