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 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.

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.

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.

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

High-resolution (0.12 a.u.

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.

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.

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.

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.

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.

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 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.

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.

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 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.

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.