The advancement of multidisciplinary research fields dealing with ionising radiation induced biological damage-radiobiology, radiation physics, radiation protection and, in particular, medical physics-requires a clear mechanistic understanding of how cellular damage is induced by ionising radiation. Monte Carlo (MC) simulations provide a promising approach for the mechanistic simulation of radiation transport and radiation chemistry, towards the in silico simulation of early biological damage. We have recently developed a fully integrated MC simulation that calculates early single strand breaks (SSBs) and double strand breaks (DSBs) in a fractal chromatin based human cell nucleus model. The results of this simulation are almost equivalent to past MC simulations when considering direct/indirect strand break fraction, DSB yields and fragment distribution. The simulation results agree with experimental data on DSB yields within 13.6% on average and fragment distributions agree within an average of 34.8%.
Biological experiments conducted in underground laboratories over the last decade have shown that life can respond to relatively small changes in the radiation background in unconventional ways. Rapid changes in cell growth, indicative of hormetic behaviour and long‐term inheritable changes in antioxidant regulation have been observed in response to changes in the radiation background that should be almost undetectable to cells. Here, we summarize the recent body of underground experiments conducted to date, and outline potential mechanisms (such as cell signalling, DNA repair and antioxidant regulation) that could mediate the response of cells to low radiation backgrounds. We highlight how multigenerational studies drawing on methods well established in studying evolutionary biology are well suited for elucidating these mechanisms, especially given these changes may be mediated by epigenetic pathways. Controlled evolution experiments with model organisms, conducted in underground laboratories, can highlight the short‐ and long‐term differences in how extremely low‐dose radiation environments affect living systems, shining light on the extent to which epimutations caused by the radiation background propagate through the population. Such studies can provide a baseline for understanding the evolutionary responses of microorganisms to ionizing radiation, and provide clues for understanding the higher radiation environments around uranium mines and nuclear disaster zones, as well as those inside nuclear reactors.
At very low radiation dose rates, the effects of energy depositions in cells by ionizing radiation is best understood stochastically, as ionizing particles deposit energy along tracks separated by distances often much larger than the size of cells. We present a thorough analysis of the stochastic impact of the natural radiative background on cells, focusing our attention on E. coli grown as part of a long term evolution experiment in both underground and surface laboratories. The chance per day that a particle track interacts with a cell in the surface laboratory was found to be 6 × 10−5 day−1, 100 times less than the expected daily mutation rate for E. coli under our experimental conditions. In order for the chance cells are hit to approach the mutation rate, a gamma background dose rate of 20 μGy hr−1 is predicted to be required.
While radon in soil gases has been identified for decades as a potential precursor of volcanic eruptions, there has been a recent interest for monitoring radon in air on active volcanoes. We present here the first network of outdoor air radon sensors that was installed successfully on Mt. Etna volcano, Sicily, Italy in September 2019. Small radon sensors designed for workers and home dosimetry were tropicalized in order to be operated continuously in harsh volcanic conditions with an autonomy of several months. Two stations have been installed on the south flank of the volcano at ~3000 m of elevation. A private network has been deployed in order to transfer the measurements from the stations directly to a server located in France, using a low-power wide-area transmission technology from Internet of Things (IoT) called LoRaWAN. Data finally feed a data lake, allowing flexibility in data management and sharing. A first analysis of the radon datasets confirms previous observations, while adding temporal information never accessed before. The observed performances confirm IoT solutions are very adapted to active volcano monitoring in terms of range, autonomy, and data loss.
Abstract. Aiming to explore how biological systems respond to ultra-low background environments, we report here our background studies for biological experiments in the Modane Underground Laboratory. We find that the minimum radioactive background for biology experiments is limited by the potassium content of the biological sample itself, coming from its nutritive medium, which we find in our experimental set-up to be 26 nGy hr -1 . Compared to our reference radiation environment in Clermont-Ferrand, biological experiments can be conducted in the Modane laboratory with a radiation background 8.2 times lower than the reference above-ground level. As the radiation background may be further reduced by using different nutritive media, we also provide measurements of the potassium concentration by gamma spectroscopy of yeast extract (63.3 ± 1.2 mg g -1 ) and tryptone (2.5 ± 0.2 mg g -1 ) in order to guide media selection in future experiments.Afin d'examiner la manière avec laquelle les systèmes biologiques répondent aux environnements caractérisés par un bas niveau de radioactivité, nous avons mesuré le bruit de fond des expériences de biologie menées au Laboratoire Souterrain de Modane. Nous montrons que le bruit de fond est limité par le contenu en potassium au travers des échantillons biologiques euxmêmes, dans leurs milieux nutritifs. Dans le cadre des expériences examinées ici, le bruit de fond de potassium contribue à hauteur de 26 nGy hr -1 . Par rapport à notre environnement de référence à Clermont-Ferrand, des expériences biologiques peuvent être conduites dans le laboratoire souterrain avec une réduction du bruit de fond de 8.2 fois le niveau de la surface. Du fait que le milieu nutritif apporte le plus grand impact au bruit de fond radiatif, nous recommandons la mesure par spectrométrie gamma de la concentration de potassium dans l'extrait de levure (63.3 ± 1.2 mg g -1 ) et le tryptone (2.5 ± 0.2 mg g -1 ) afin de guider la sélection du milieu des futures expériences.
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