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NASA NTRS · 20220006579

Space Radiation

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Martha Clowdsley. Space Radiation. https://ntrs.nasa.gov/citations/20220006579

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Long-term effects of acute irradiation and isolation on crew age-matched mice

The future of space missions beyond low-Earth orbit presents exciting opportunities but may come with formidable health challenges. Astronauts face a unique combination of space stressors capable of exerting effects on the central nervous system (CNS) with possible sex-dependent differences. The interaction of these combined spaceflight stressors may induce oxidative stress, thereby altering brain integrity and behavioral performance. Understanding these changes is critical for safeguarding astronaut health and enabling successful exploration. By understanding the physiological responses to the combined effects of ionizing radiation (IR) and social isolation in the brain through immunohistochemistry (IHC), proteomics and cytokine expression analyses, we aim to identify CNS pathways ripe for countermeasure development to mitigate adverse brain changes with future deep space exploration. Here, we study the combined effects of simulated 5-ion galactic cosmic radiation (GCRsim) at acute dosage (5, 15, and 50 cGy) and social isolation on crew age-matched male and female mice at 124 days post-irradiation. We conducted analyses of hippocampal cytokine biomarkers and proteomic profiling on hippocampal lysates. Our findings reveal sex-specific regulation of hippocampal cytokines and proteomic profiles. Ongoing immunohistochemistry findings on the hippocampus will provide qualitative information regarding key protein expression and cellular changes such as microglial activation, blood brain barrier integrity, and neuroinflammation. With future plans for long-duration space missions, such as Mars exploration, understanding CNS changes over extended periods in mice can provide insights into potential long-term health impacts on astronauts. This project will provide us with valuable insights into sex-differences in neurobiological processes and disease mechanisms impacting men and women in space.

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The space environment consists of a complex mixture of different types of ionizing radiation and altered gravity that represents a threat to humans during space missions. In particular, individual radiation sensitivity is strictly related to the risk of space radiation carcinogenesis. Therefore, in view of future missions to the Moon and Mars, there is an urgent need to estimate as accurately as possible the individual risk from space exposure to improve the safety of space exploration. In this review, we survey the combined effects from the two main physical components of the space environment, ionizing radiation and microgravity, to alter the genetics and epigenetics of human cells, considering both real and simulated space conditions. Data collected from studies on human cells are discussed for their potential use to estimate individual radiation carcinogenesis risk from space exposure.

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Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤ 15 cGy of individual Galactic Cosmic Radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in Attentional Set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the Simple Discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the Compound Discrimination (CD) stage. On a subject-based level, implementing Machine Learning (ML) classifiers such as the Gaussian Naïve Bayes, Support Vector Machine, and Artificial Neural Networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreenperformance scores as multidimensional input features to predict each rodent’s susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Feis the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4Hein SD and 28Siin CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for morerobust predictionsof cognitive decrements due to space radiation exposure.

space radiation