Optimized neuron models for estimation of charged particle energy deposition in hippocampus.

The study of evaluating radiation risk on the central nervous system induced by space-born charged particles is very complex and challenging task in space radiobiology and radiation protection. To overcome computational difficulties in this field, we developed simplified neuron models with properties equivalent to realistic neuron morphology. Three-dimensional structure and parameters of simplified and complex neuron models with realistic morphology were obtained from the experimental data. The models implement uniform random distribution of spines along the dendritic branches in typical hippocampal neurons. Both types of models were implemented and tested using Geant4 Monte Carlo radiation transport code. Track structure simulations were performed for ion beams with typical fluxes of galactic cosmic rays expected for long-term interplanetary missions. The distribution of energy deposition events and percentage of irradiated volumes were obtained to be similar in both simplified and realistic models of pyramidal and granule cells of the rat hippocampus following irradiation. Significant increase of computational efficiency for detailed microdosimetry simulations of hippocampus using simplified neuron models was achieved. Using designed neuron models we have constructed 3D model of the rat hippocampus, including pyramidal cells, mature and immature granular cells, mossy cells, and neural stem cells. Computed energy deposition in irradiated hippocampal neurons following a track of iron ion suggests that most of energy is accumulated by dense population of granular cells in the dentate gyrus. Proposed approach could serve as a complementary computation technique for studying radiation-induced effects in large scale brain networks.

Radiation damage to neuronal cells: Simulating the energy deposition and water radiolysis in a small neural network.

Radiation damage to the central nervous system (CNS) has been an on-going challenge for the last decades primarily due to the issues of brain radiotherapy and radiation protection for astronauts during space travel. Although recent findings revealed a number of molecular mechanisms associated with radiation-induced impairments in behaviour and cognition, some uncertainties exist in the initial neuronal cell injury leading to the further development of CNS malfunction. The present study is focused on the investigation of early biological damage induced by ionizing radiations in a sample neural network by means of modelling physico-chemical processes occurring in the medium after exposure. For this purpose, the stochastic simulation of incident particle tracks and water radiation chemistry was performed in realistic neuron phantoms constructed using experimental data on cell morphology. The applied simulation technique is based on using Monte-Carlo processes of the Geant4-DNA toolkit. The calculations were made for proton, 12C, and 56Fe particles of different energy within a relatively wide range of linear energy transfer values from a few to hundreds of keV/µm. The results indicate that the neuron morphology is an important factor determining the accumulation of microscopic radiation dose and water radiolysis products in neurons. The estimation of the radiolytic yields in neuronal cells suggests that the observed enhancement in the levels of reactive oxygen species may potentially lead to oxidative damage to neuronal components disrupting the normal communication between cells of the neural network.