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The non-random distribution of DNA breakage in pulsed-field gel electrophoresis (PFGE) experiments poses a problem of proper subtraction of the background damage to obtain a fragment-size distribution due to radiation only. As been pointed out by various authors, a naive bin-to-bin subtraction of the background signal will not result in the right DNA mass distribution histogram, and may even result in negative values. Previous more systematic subtraction methods have been based mainly on random breakage, appropriate for low-LET radiation but problematic for high LET. Moreover, an investigation is needed whether the background breakage itself is random or non-random. Previously a new generalized formalism based on stochastic processes for the subtraction of the background damage in PFGE experiments for any LET and any background was proposed, and as now applied it to a set of PFGE data for Fe ions. We developed a Monte Carlo algorithm to compare the naïve subtraction procedure in artificial data sets to the result produced by the new formalism. The simulated data corresponded to various cases, involving non-random (high-LET) or random radiation breakage and random or non-random background breakage. The formalism systematically gives better results than naïve bin-by-bin subtraction in all these artificial data sets.

The non-random distribution of DNA breakage in PFGE (pulsed-field gel electrophoresis) experiments poses a problem of proper subtraction of the background DNA damage to obtain a fragment-size distribution due to radiation only. A naive bin-to-bin subtraction of the background signal will not result in the right DNA mass distribution histogram. This problem could become more pronounced for high-LET (linear energy transfer) radiation, because the fragment-size distribution manifests a higher frequency of smaller fragments. Previous systematic subtraction methods have been based on random breakage, appropriate for low-LET radiation. Moreover, an investigation is needed to determine whether the background breakage is itself random or non-random. We consider two limiting cases: (1) the background damage is present in all cells, and (2) it is present in only a small subset of cells, while other cells are not contributing to the background DNA fragmentation. We give a generalized formalism based on stochastic processes for the subtraction of the background damage in PFGE experiments for any LET and apply it to two sets of PFGE data for iron ions.

The present system of radiation protection assumes that exposure at low doses and/or low dose-rates leads to health risks linearly related to the dose. They are evaluated by a combination of epidemiological data and radiobiological models. The latter imply that radiation induces deleterious effects via genetic mutation caused by DNA damage with a linear dose-dependence. This picture is challenged by the observation of radiation-induced epigenetic effects (changes in gene expression without altering the DNA sequence) and of non-linear responses, such as non-targeted and adaptive responses, that in turn can be controlled by gene expression networks. Here, we review important aspects of the biological response to ionizing radiation in which epigenetic mechanisms are, or could be, involved, focusing on the possible implications to the low dose issue in radiation protection. We examine in particular radiation-induced cancer, non-cancer diseases and transgenerational (hereditary) effects. We conclude that more realistic models of radiation-induced cancer should include epigenetic contribution, particularly in the initiation and progression phases, while the impact on hereditary risk evaluation is expected to be low. Epigenetic effects are also relevant in the dispute about possible "beneficial" effects at low dose and/or low dose-rate exposures, including those given by the natural background radiation. [ABSTRACT FROM AUTHOR]