RadPhysBio: A Radiobiological Database for the Prediction of Cell Survival upon Exposure to Ionizing Radiation.

Based on the need for radiobiological databases, in this work, we mined experimental ionizing radiation data of human cells treated with X-rays, γ-rays, carbon ions, protons and α-particles, by manually searching the relevant literature in PubMed from 1980 until 2024. In order to calculate normal and tumor cell survival α and ß coefficients of the linear quadratic (LQ) established model, as well as the initial values of the double-strand breaks (DSBs) in DNA, we used WebPlotDigitizer and Python programming language. We also produced complex DNA damage results through the fast Monte Carlo code MCDS in order to complete any missing data. The calculated α/ß values are in good agreement with those valued reported in the literature, where α shows a relatively good association with linear energy transfer (LET), but not ß. In general, a positive correlation between DSBs and LET was observed as far as the experimental values are concerned. Furthermore, we developed a biophysical prediction model by using machine learning, which showed a good performance for α, while it underscored LET as the most important feature for its prediction. In this study, we designed and developed the novel radiobiological 'RadPhysBio' database for the prediction of irradiated cell survival (α and ß coefficients of the LQ model). The incorporation of machine learning and repair models increases the applicability of our results and the spectrum of potential users.

A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality.

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the 'MultiScale Approach (MSA)' model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with 11Β, 12C, 14Ν, 16Ο, 20Νe, 40Αr, 28Si and 56Fe ions by using only three input parameters (particle's LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.

Construction and evaluation of an α-particle-irradiation exposure apparatus.

PURPOSE: The development of an exposure apparatus for in situ α-irradiation studies of cells. The construction of the apparatus is simple and the apparatus is maintenance free, easy to use and of low cost. This small device can be placed in an incubator, where the exposure environment is controlled. Moreover the vapor saturated incubator protects the cells from drying out, allowing long irradiation intervals. MATERIALS AND METHODS: The system includes a 234U alpha (α)-source of total activity 0.77 ± 0.03 MBq in the form of a thin disk deposited on an aluminum substrate. The α-particles emitted in the air have a mean energy of 4.9 MeV at the disk surface. Source homogeneity has been studied via Rutherford Backscattering Spectrometry. Using SRIM 2013 and Monte Carlo (MC) simulations via the MCNP6.1 code, LET and energy deposition values have been calculated for various filling gasses. Furthermore, based on these simulations, the assembly's dimensions and equivalent irradiation rate have been determined. With respect to the aforementioned dimensions, the experimental setup is constructed in a way to provide uniform irradiation of the sample. Using Sacalc3v1.4 irradiation radial homogeneity has been studied. In order to evaluate biologically our apparatus, a well-established chromosomal aberration assay has been utilized, applied in exponentially growing hamster (CHO) cells. Furthermore, immunofluorescence gamma-H2AX/53BP1 foci assay has been performed as a 'biological detector', in order to validate α-particles surface density. RESULTS: Source surface homogeneity: emission deviations do not exceed 10-15%. The optimal distance between the source and the cells for irradiation is determined to be 14.8 mm. Irradiation radial homogeneity: a deviation of 5% occurs at the first 8 mm from the center of the irradiation area, and a 10% deviation occurs after 12 mm. Chromosomal aberrations were found in good agreement with the corresponding in bibliography. CONCLUSIONS: The current technical report describes analytically the development and evaluation stages of this experimental housing; from MC simulations to the irradiation of mammalian cells and data analysis. Moreover, guidance is provided as well as a report of the variables on which critical parameters are depended, so as to make this work useful to anyone who wants to construct a similar in-house α-irradiation apparatus for radiobiological studies using mammalian cells.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations.

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance.

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.