A practical approach for continuous in situ characterization of radiation quality factors in space

A competing risks machine learning study of neutron dose, fractionation, age, and sex effects on mortality in 21,000 mice

This study explores the impact of densely-ionizing radiation on non-cancer and cancer diseases, focusing on dose, fractionation, age, and sex effects. Using historical mortality data from approximately 21,000 mice exposed to fission neutrons, we employed random survival forest (RSF), a powerful machine learning algorithm accommodating nonlinear dependencies and interactions, treating cancer and non-cancer outcomes as competing risks. Unlike traditional parametric models, RSF avoids strict assumptions and captures complex data relationships through decision tree ensembles. SHAP (SHapley Additive exPlanations) values and variable importance scores were employed for interpretation. The findings revealed clear dose-response trends, with cancer being the predominant cause of mortality. SHAP value dose-response shapes differed, showing saturation for cancer hazard at high doses (> 2 Gy) and a more linear pattern at lower doses. Non-cancer responses remained more linear throughout the entire dose range. There was a potential inverse dose rate effect for cancer, while the evidence for non-cancer was less conclusive. Sex and age effects were less pronounced. This investigation, utilizing machine learning, enhances our understanding of the patterns of non-cancer and cancer mortality induced by densely-ionizing radiations, emphasizing the importance of such approaches in radiation research, including space travel and radioprotection.

Galactic cosmic ray simulation at the NASA space radiation laboratory - Progress, challenges and recommendations on mixed-field effects

For missions beyond low Earth orbit to the moon or Mars, space explorers will encounter a complex radiation field composed of various ion species with a broad range of energies. Such missions pose significant radiation protection challenges that need to be solved in order to minimize exposures and associated health risks. An innovative galactic cosmic ray simulator (GCRsim) was recently developed at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL). The GCRsim technology is intended to represent major components of the space radiation environment in a ground analog laboratory setting where it can be used to improve understanding of biological risks and serve as a testbed for countermeasure development and validation. The current GCRsim consists of 33 energetic ion beams that collectively simulate the primary and secondary GCR field encountered by humans in space over the broad range of particle types, energies, and linear energy transfer (LET) of interest to health effects. A virtual workshop was held in December 2020 to assess the status of the NASA baseline GCRsim. Workshop attendees examined various aspects of simulator design, with a particular emphasis on beam selection strategies. Experimental results, modeling approaches, areas of consensus, and questions of concern were also discussed in detail. This report includes a summary of the GCRsim workshop and a description of the current status of the GCRsim. This information is important for future advancements and applications in space radiobiology.

Impact of Radiation Quality on Microdosimetry and Chromosome Aberrations for High-Energy (>250 MeV/n) Ions

Studying energy deposition by space radiation at the cellular scale provides insights on health risks to astronauts. Using the Monte Carlo track structure code RITRACKS, and the chromosome aberrations code RITCARD, we performed a modeling study of single-ion energy deposition spectra and chromosome aberrations for high-energy (>250 MeV/n) ion beams with linear energy transfer (LET) varying from 0.22 to 149.2 keV/µm. The calculations were performed using cells irradiated directly by mono-energetic ion beams, and by poly-energetic beams after particle transport in a digital mouse model, representing the radiation exposure of a cell in a tissue. To discriminate events from ion tracks directly traversing the nucleus, to events from δ-electrons emitted by distant ion tracks, we categorized ion contributions to microdosimetry or chromosome aberrations into direct and indirect contributions, respectively. The ions were either ions of the mono-energetic beam or secondary ions created in the digital mouse due to interaction of the beam with tissues. For microdosimetry, the indirect contribution is largely independent of the beam LET and minimally impacted by the beam interactions in mice. In contrast, the direct contribution is strongly dependent on the beam LET and shows increased probabilities of having low and high-energy deposition events when considering beam transport. Regarding chromosome aberrations, the indirect contribution induces a small number of simple exchanges, and a negligible number of complex exchanges. The direct contribution is responsible for most simple and complex exchanges. The complex exchanges are significantly increased for some low-LET ion beams when considering beam transport.