Nano-scale simulation of neuronal damage by galactic cosmic rays

• Main Authors: Peter, Jonah S, Schuemann, Jan, Held, Kathryn D, McNamara, Aimee L
• Format: Journal Article
• Language: English
• Published: 15-02-2022
• Subjects: Physics - Medical Physics; Physics - Space Physics; Quantitative Biology - Quantitative Methods
• DOI: 10.48550/arxiv.2202.07547

The effects of complex, mixed-ion radiation fields on neuronal function
remain largely unexplored. Here, we present a complete analysis of the
nano-scale physics associated with broad-spectrum galactic cosmic ray (GCR)
irradiation in a realistic cornu ammonis 1 (CA1) pyramidal neuron geometry.
We simulate the entire 33 ion-energy beam fluence distribution currently in
use at the NASA Space Radiation Laboratory galactic cosmic ray simulator
(GCRSim). We use the TOol for PArticle Simulation (TOPAS) and TOPAS-nBio Monte
Carlo-based track structure simulation toolkits to assess the dosimetry,
physics processes, and fluence statistics of different neuronal compartments at
the nanometer scale. We also make comparisons between the full GCRSim
distribution and a simplified 6 ion-energy spectrum (SimGCRSim).
We show that across all physics processes, ionizations mediate the majority
of the energy deposition $(68 \pm 1\%)$, though vibrational excitations are the
most abundant ($70 \pm 2\%$ of all energy deposition events). We report that
neuronal energy deposition by proton and $\alpha$-particle tracks declines
approximately hyperbolically with increasing primary particle energy at
mission-relevant energies. We also demonstrate an inverted exponential
relationship between dendritic segment irradiation probability and neuronal
absorbed dose. Finally, we find that there are no significant differences in
the average physical responses between the GCRSim and SimGCRSim fluence
distributions.
To our knowledge, this is the first nano-scale simulation study of a
realistic neuron geometry using the GCRSim and SimGCRSim fluence distributions.
The results presented here are expected to aid in the interpretation of future
experimental results and help guide future study designs.