Multiparametric radiobiological assays show that variation of X-ray energy strongly impacts relative biological effectiveness: comparison between 220 kV and 4 MV

International audienceBased on classic clonogenic assay, it is accepted by the scientific community that, whatever the energy, the relative biological effectiveness of X-rays is equal to 1. However, although X-ray beams are widely used in diagnosis, interventional medicine and radiotherapy, comparisons of their energies are scarce. We therefore assessed in vitro the effects of low- and high-energy X-rays using Human umbilical vein endothelial cells (HUVECs) by performing clonogenic assay, measuring viability/mortality, counting γ-H2AX foci, studying cell proliferation and cellular senescence by flow cytometry and by performing gene analysis on custom arrays. Taken together, excepted for γ-H2AX foci counts, these experiments systematically show more adverse effects of high energy X-rays, while the relative biological effectiveness of photons is around 1, whatever the quality of the X-ray beam. These results strongly suggest that multiparametric analysis should be considered in support of clonogenic assay

Analysis Methods for the preservation of Bologna Municipal Palace \u2013 Metodi di analisi per il restauro del palazzo Comunale di Bologna

Preservation requires a deep understanding of the artefact, using critical awareness to guide every intervention, from conservation to functional updating. Within the study of the complex organism of the Municipal Palace of Bologna, historic seat of political power, the deepening into the architectural history of the XIII-century reveals the opportunity to experience complex methods of analysis, which integrate a variety of direct and indirect readings. The highly articulated score of the fa\ue7ade shows an intimate superposition of various traces, openings, consolidations, extensions, floor divisions, turning the leitmotiv of a diachronic reconstruction of the entire artifact portion. The analysis of the results of trilaterations, laser scans, building site and notarial documents, drawings, literature sources, all is systematized elaborating a diachronic matrix of archaeological inspiration. Such results enable the interpretation of the unknown signs with physical and chronological relations up to reveal historical passages and constructive vulnerability, without invasive methods: each sign reveals itself as precious testimony, and it is compulsory to be enhanced by aware preservatio

New Bayesian contributions to radiation dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven or suspected radiation exposure. On the one hand, dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of proven radiation exposure. In this context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what were the estimated absorbed dose and its associated uncertainty?" and 2) "Was the radiation exposure total or partial?" On the other hand, dose estimation from dicentric counts can also be crucial to clarify unclear radiation exposure scenarios. In this context, one important additional question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems. Bayesian statistical approaches have also been recently proposed but, up to our knowledge, they do not allow answering question 3) and do not highlight clearly the pros and cons of using Bayesian statistics in biological retrospective dosimetry. Finally, no consensus has been reached so far on the best way to proceed to answer the above questions. In this work, we propose an alternative approach - based on the full Bayesian inference of a Poisson mixture model – that allows providing, in a unique and coherent framework, some rich probabilistic answers to the above three questions, simultaneously. Using simulation studies and cytogenetic data from real radiation accident victims and suspected exposed individuals, we highlight the pros and cons of using Bayesian statistics in biological retrospective dosimetry. A sensitivity analysis to the prior choice on the unknown quantities (e.g., the dose) is performed. Our work show that the benefits from using our Bayesian Poisson mixture model are more pronounced for small doses than for high doses

A Bayesian Poisson mixture model for model selection and dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven radiation accidents. In this specific context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what are the estimated absorbed dose and its associated uncertainty?"and 2) "Was the radiation exposure total or partial?" Dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of radiation exposure. Moreover, dose estimation from dicentric counts can be crucial to clarify unclear radiation exposure scenarios. In this context, one important question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems but no consensus has been reached so far on the best way to proceed. In this work, we propose an alternative approach based on the Bayesian inference of a Poisson mixture model. This approach allows providing, in a unique and coherent framework, some rich and simultaneous probabilistic answers to the above three questions. Particularly, our mixture model is used as a Bayesian model selection tool that is relevant to answer questions 2) and 3). A specific adaptive Metropolis-Hastings algorithm was implemented to avoid potential convergence difficulties when estimating the mixture weights. Using simulation studies and cytogenetic data from real radiation accident victims, we discuss the advantages of the proposed Bayesian approach compared to the classical ones. A sensitivity analysis to the prior choice on the unknown dose and the mixture weights was also performed

A Bayesian Poisson mixture model for model selection and dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven radiation accidents. In this specific context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what are the estimated absorbed dose and its associated uncertainty?"and 2) "Was the radiation exposure total or partial?" Dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of radiation exposure. Moreover, dose estimation from dicentric counts can be crucial to clarify unclear radiation exposure scenarios. In this context, one important question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems but no consensus has been reached so far on the best way to proceed. In this work, we propose an alternative approach based on the Bayesian inference of a Poisson mixture model. This approach allows providing, in a unique and coherent framework, some rich and simultaneous probabilistic answers to the above three questions. Particularly, our mixture model is used as a Bayesian model selection tool that is relevant to answer questions 2) and 3). A specific adaptive Metropolis-Hastings algorithm was implemented to avoid potential convergence difficulties when estimating the mixture weights. Using simulation studies and cytogenetic data from real radiation accident victims, we discuss the advantages of the proposed Bayesian approach compared to the classical ones. A sensitivity analysis to the prior choice on the unknown dose and the mixture weights was also performed

Bayesian contributions to radiation dose estimation in biological retrospective dosimetry.

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven or suspected radiation exposure. On the one hand, dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of proven radiation exposure. In this context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what were the estimated absorbed dose and its associated uncertainty?" and 2) "Was the radiation exposure total or partial?" On the other hand, dose estimation from dicentric counts can also be crucial to clarify unclear radiation exposure scenarios. In this context, one important additional question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems. Bayesian statistical approaches have also been recently proposed but, up to our knowledge, they do not allow answering question 3) and do not highlight clearly the pros and cons of using Bayesian statistics in biological retrospective dosimetry. Finally, no consensus has been reached so far on the best way to proceed to answer the above questions. In this work, we propose an alternative approach - based on the full Bayesian inference of a Poisson mixture model – that allows providing, in a unique and coherent framework, some rich probabilistic answers to the above three questions, simultaneously. Using simulation studies and cytogenetic data from real radiation accident victims and suspected exposed individuals, we highlight the pros and cons of using Bayesian statistics in biological retrospective dosimetry. A sensitivity analysis to the prior choice on the unknown quantities (e.g., the dose) is performed. Our work show that the benefits from using our Bayesian Poisson mixture model are more pronounced for small doses than for high doses

Characterizing the DNA damage signaling response of cell populations exposed to mixed radiation fields from monoenergetic neutrons

International audienceThe most prevalent type of ionizing radiation to which humans are exposed consists of mixed ionizing radiation fields. While exposure to a specific type of radiation (X and γ rays, α particles, among others) on cells and whole organisms has been widely studied, less is known about the biological effects following mixed ionizing radiation fields. This requires more information on the likelihood of subcellular effects, mainly DNA damage, according to the way energy is deposited within cells by ionizing particle tracks of different qualities. Due to their physical characteristics and the variety of nuclear atomic reactions, neutron exposures are of interest as they induce a mixed ionizing radiation field of secondary particles such as protons, alphas and electrons with very broad energy spectra.Therefore, we investigated, in situ, the evolution of DNA damage repair signaling, i.e. 53BP1 and γ-H2AX foci, in primary endothelial cells following complex irradiation with mixed radiation qualities by exposing cells to monoenergetic neutron fields of 2.5 or 15.1 MeV. The cells were placed on a human-mimicking water phantom positioned close to the source to maximize the absorbed dose. The assessment of the dose received by the cells was performed from primary neutrons fluence measurements and using Monte Carlo simulations with the Geant4 toolkit. The results shed light on the spatial rearrangement of a sub-set of foci 30 min post exposure, in the form of a linear pattern which occurred in 4 to 18% of cell nuclei depending on the neutrons energy and the irradiation configuration. These signatures were linked to realistic topologies of radiation-induced DNA damage at the cell population level, and their origin was analyzed by combining microdosimetric and nanodosimetric methods using the new MINAS TIRITH simulation tool which allowed its own validation.Our findings enabled us to study energy deposition and early cell damage from mixed radiation fields and obtain more accurate estimates of interaction probabilities that induce foci formation. This is crucial for assessing radiation therapy risk, where mixed radiation fields increase side effects and protecting space travelers from eventual health issues during long-duration space missions

Nanodosimetric calculations of radiation-induced DNA damage in a new nucleus geometrical model based on the isochore theory

International audienceDouble strand breaks (DSB) in nuclear DNA are one type of radiation-induced damage identified as being particularly deleterious. The calculation of these damages using Monte Carlo track structure modelling, which is made possible by the Geant4-DNA toolkit, could be a good indicator to better appreciate and anticipate the side effects of radiation therapy. However, in order to obtain accurate simulated results, a cell nucleus geometry as realistic as possible must be used. In this work, we present simulation results with a new model of an endothelial cell nucleus in which the levels of chromatin compaction are distributed along the genome according to the isochore theory. In a comparative study with a previous nuclear geometry, simulations are conducted for proton LET of 4.29 keV/µm, 19.51 keV/µm and 43.25 keV/µm. The organization of the chromatin fiber into different levels of compaction linked to isochore families leads to an increase of 3-10% in DSB yield and makes it possible to identify the most affected part of the genome. New results indicate that, the genome core is more radiosensitive than the genome desert. This study highlights the importance of an advanced modelling of the distribution of the chromatin compaction levels for the calculation of the radio-induced damage

Breast cancer stem cell-like cells generated during TGFβ-induced EMT are radioresistant

International audienceFailure of conventional antitumor therapy is commonly associated with cancer stem cells (CSCs), which are often defined as inherently resistant to radiation and chemotherapeutic agents. However, controversy about the mechanisms involved in the radiation response remains and the inherent intrinsic radioresistance of CSCs has also been questioned. These discrepancies observed in the literature are strongly associated with the cell models used. In order to clarify these contradictory observations, we studied the radiosensitivity of breast CSCs using purified CD24−/low/CD44+ CSCs and their corresponding CD24+/CD44low non-stem cells. These cells were generated after induction of the epithelial-mesenchymal transition (EMT) by transforming growth factor β (TGFβ) in immortalized human mammary epithelial cells (HMLE). Consequently, these 2 cellular subpopulations have an identical genetic background, their differences being related exclusively to TGFβ-induced cell reprogramming. We showed that mesenchymal CD24−/low/CD44+ CSCs are more resistant to radiation compared with CD24+/CD44low parental cells. Cell cycle distribution and free radical scavengers, but not DNA repair efficiency, appeared to be intrinsic determinants of cellular radiosensitivity. Finally, for the first time, we showed that reduced radiation-induced activation of the death receptor pathways (FasL, TRAIL and TNF-α) at the transcriptional level was a key causal event in the radioresistance of CD24−/low/CD44+ cells acquired during EMT

MINAS TIRITH: a new tool for simulating radiation-induced DNA damage at the cell population level

International audienceObjective. The mechanisms of radiation-induced DNA damage can be understood via the fundamental acquisition of knowledge through a combination of experiments and modeling. Currently, most biological experiments are performed by irradiating an entire cell population, whereas modeling of radiation-induced effects is usually performed via Monte Carlo simulations with track structure codes coupled to realistic DNA geometries of a single-cell nucleus. However, the difference in scale between the two methods hinders a direct comparison because the dose distribution in the cell population is not necessarily uniform owing to the stochastic nature of the energy deposition. Thus, this study proposed the MINAS TIRITH tool to model the distribution of radiation-induced DNA damage in a cell population. Approach. The proposed method is based on precomputed databases of microdosimetric parameters and DNA damage distributions generated using the Geant4-DNA Monte Carlo Toolkit. First, a specific energy was assigned to each cell of an irradiated population for a particular absorbed dose following microdosimetric formalism. Then, each cell was assigned a realistic number of DNA damage events according to the specific energy respecting the stochastic character of its occurrence. Main results. This study validated the MINAS TIRITH tool by comparing its results with those obtained using the Geant4-DNA track structure code and a Geant4-DNA based simulation chain for DNA damage calculation. The different elements of comparison indicated consistency between MINAS TIRITH and the Monte Carlo simulation in case of the dose distribution in the population and the calculation of the amount of DNA damage. Significance. MINAS TIRITH is a new approach for the calculation of radiation-induced DNA damage at the cell population level that facilitates reasonable simulation times compared to those obtained with track structure codes. Moreover, this tool enables a more direct comparison between modeling and biological experimentation