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NASA NTRS2014

Simulation of the Formation of DNA Double Strand Breaks and Chromosome Aberrations in Irradiated Cells

The formation of DNA double-strand breaks (DSBs) and chromosome aberrations is an important consequence of ionizing radiation. To simulate DNA double-strand breaks and the formation of chromosome aberrations, we have recently merged the codes RITRACKS (Relativistic Ion Tracks) and NASARTI (NASA Radiation Track Image). The program RITRACKS is a stochastic code developed to simulate detailed event-by-event radiation track structure: [1] This code is used to calculate the dose in voxels of 20 nm, in a volume containing simulated chromosomes, [2] The number of tracks in the volume is calculated for each simulation by sampling a Poisson distribution, with the distribution parameter obtained from the irradiation dose, ion type and energy. The program NASARTI generates the chromosomes present in a cell nucleus by random walks of 20 nm, corresponding to the size of the dose voxels, [3] The generated chromosomes are located within domains which may intertwine, and [4] Each segment of the random walks corresponds to approx. 2,000 DNA base pairs. NASARTI uses pre-calculated dose at each voxel to calculate the probability of DNA damage at each random walk segment. Using the location of double-strand breaks, possible rejoining between damaged segments is evaluated. This yields various types of chromosomes aberrations, including deletions, inversions, exchanges, etc. By performing the calculations using various types of radiations, it will be possible to obtain relative biological effectiveness (RBE) values for several types of chromosome aberrations.

Plante, Ianik↗

NASA NTRS2013

Improving Sanitation and Health in Rural Alaska

In rural Alaskan communities personal health is threatened by energy costs and limited access to clean water, wastewater management, and adequate nutrition. Fuel-‐based energy systems are significant factors in determining local accessibility to clean water, sanitation and food. Increasing fuel costs induce a scarcity of access and impact residents' health. The University of Alaska Fairbanks (UAF) School of Natural Resources and Agricultural Sciences (SNRAS), NASA's Ames Research Center, and USDA Agricultural Research Service (ARS) have joined forces to develop high‐efficiency, low‐energy consuming techniques for water treatment and food production in rural circumpolar communities. Methods intended for exploration of space and establishment of settlements on the Moon or Mars will ultimately benefit Earth's communities in the circumpolar north. The initial phase of collaboration is completed. Researchers from NASA Ames Research Center and SNRAS, funded by the USDA‐ARS, tested a simple, reliable, low-energy sewage treatment system to recycle wastewater for use in food production and other reuse options in communities. The system extracted up to 70% of the water from sewage and rejected up to 92% of ions in the sewage with no carryover of toxic effects. Biological testing showed that plant growth using recovered water in the nutrient solution was equivalent to that using high‐purity distilled water. With successful demonstration that the low energy consuming wastewater treatment system can provide safe water for communities and food production, the team is ready to move forward to a full‐scale production testbed. The SNRAS/NASA team (including Alaska students) will design a prototype to match water processing rates and food production to meet rural community sanitation needs and nutritional preferences. This system would be operated in Fairbanks at the University of Alaska through SNRAS. Long‐term performance will be validated and operational needs of the system determined. The testbed will be a part of the university education and operator training program. The "Forgotten Alaska" has long awaited this technology to augment the traditional

Plant Growth↗

NASA NTRS2014

Induction of Chromosomal Aberrations at Fluences of Less Than One HZE Particle per Cell Nucleus

The assumption of a linear dose response used to describe the biological effects of high LET radiation is fundamental in radiation protection methodologies. We investigated the dose response for chromosomal aberrations for exposures corresponding to less than one particle traversal per cell nucleus by high energy and charge (HZE) nuclei. Human fibroblast and lymphocyte cells where irradiated with several low doses of <0.1 Gy, and several higher doses of up to 1 Gy with O (77 keV/ (long-s)m), Si (99 keV/ (long-s)m), Fe (175 keV/ (long-s)m), Fe (195 keV/ (long-s)m) or Fe (240 keV/ (long-s)m) particles. Chromosomal aberrations at first mitosis were scored using fluorescence in situ hybridization (FISH) with chromosome specific paints for chromosomes 1, 2 and 4 and DAPI staining of background chromosomes. Non-linear regression models were used to evaluate possible linear and non-linear dose response models based on these data. Dose responses for simple exchanges for human fibroblast irradiated under confluent culture conditions were best fit by non-linear models motivated by a non-targeted effect (NTE). Best fits for the dose response data for human lymphocytes irradiated in blood tubes were a NTE model for O and a linear response model fit best for Si and Fe particles. Additional evidence for NTE were found in low dose experiments measuring gamma-H2AX foci, a marker of double strand breaks (DSB), and split-dose experiments with human fibroblasts. Our results suggest that simple exchanges in normal human fibroblasts have an important NTE contribution at low particle fluence. The current and prior experimental studies provide important evidence against the linear dose response assumption used in radiation protection for HZE particles and other high LET radiation at the relevant range of low doses.

Hada, Megumi↗

NASA NTRS2015

NASA Space Radiation Risk Project: Overview and Recent Results

The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization.

Blattnig, Steve R.↗

NASA NTRS2017

Dependence of Early and Late Chromosomal Aberrations on Radiation Quality and Cell Types

Exposure to radiation induces different types of DNA damage, increases mutation and chromosome aberration rates, and increases cellular transformation in vitro and in vivo. The susceptibility of cells to radiation depends on genetic background and growth condition of cells, as well as types of radiation. Mammalian cells of different tissue types and with different genetic background are known to have different survival rate and different mutation rate after cytogenetic insults. Genomic instability, induced by various genetic, metabolic, and environmental factors including radiation, is the driving force of tumorigenesis. Accurate measurements of the relative biological effectiveness (RBE) is important for estimating radiation-related risks. To further understand genomic instability induced by charged particles and their RBE, we exposed human lymphocytes ex vivo, human fibroblast AG1522, human mammary epithelial cells (CH184B5F5/M10), and bone marrow cells isolated from CBA/CaH(CBA) and C57BL/6 (C57) mice to high energy protons and Fe ions. Normal human fibroblasts AG1522 have apparently normal DNA damage response and repair mechanisms, while mammary epithelial cells (M10) are deficient in the repair of DNA DSBs. Mouse strain CBA is radio-sensitive while C57 is radio-resistant. Metaphase chromosomes at different cell divisions after radiation exposure were collected and chromosome aberrations were analyzed as RBE for different cell lines exposed to different radiations at various time points up to one month post irradiation.

Lu, Tao↗

NASA NTRS2017

It's All Relative: A Validation of Radiation Quality Comparison Metrics

Historically, the relative biological effectiveness (RBE) has been calculated to quantify the difference between heavy ion and gamma ray radiation. The RBE is then applied to gamma ray data to predict the effects of heavy ions in humans. The RBE is an iso-effect dose-to-dose ratio which, due to its counterintuitive nature, has been commonly miscalculated as an iso-dose effect-to-effect ratio. A paper recently published by Shuryak et al described this second measure intentionally for the first time in 2017, referring to it as the radiation effects ratio (RER). In this study, we utilized simulations to test the ability of both the RBE and the RER to predict known heavy ion effects. RBEs and RERs were calculated using mouse data from Chang et al, and the ability of the RBE and RER to predict the heavy ion data from which they were calculated was verified. Statistical transformations often utilized during data analysis were applied to the gamma and heavy ion data to determine whether RBE and RER are each uniquely defined measures. Scale changes are expected when translating effects from mice to humans and between human populations; gamma and heavy ion data were transformed to represent potential scale changes. The ability of the RBE and RER to predict the transformed heavy ion data from the transformed gamma data was then tested. The RBE but not the RER was uniquely defined after all statistical transformations. The RBE correctly predicted the scale-transformed heavy ion data, while the RER did not. This presentation describes potential implications for both metrics in light of these findings.

Chappell, L. J.↗

NASA NTRS2017

It's All Relative: A Validation of Radiation Quality Comparison Metrics

The difference between high-LET and low-LET radiation is quantified by a measure called relative biological effectiveness (RBE). RBE is defined as the ratio of the dose of a reference radiation to that of a test radiation to achieve the same effect level, and thus, is described either as an iso-effector dose-to-dose ratio. A single dose point is not sufficient to calculate an RBE value; therefore, studies with only one dose point usually calculate an effect-to-effect ratio. While not formally used in radiation protection, these iso-dose values may still be informative. Shuryak, et al 2017 investigated the use of an iso-dose metric termed "radiation effects ratio" (RER) and used both RBE and RER to estimate high-LET risks. To apply RBE or RER to risk prediction, the selected metric must be uniquely defined. That is, the calculated value must be consistent within a model given a constant set of constraints and assumptions, regardless of how effects are defined using statistical transformations from raw endpoint data. We first test the RBE and the RER to determine whether they are uniquely defined using transformations applied to raw data. Then, we test whether both metrics can predict heavy ion response data after simulated effect size scaling between human populations or when converting animal to human endpoints.

Chappell, Lori J.↗

NASA NTRS2019

How Do UTLS Jet and Tropopause Dynamics Influence Ozone Variability? Investigations Supporting the SPARC OCTAV-UTLS Activity

Understanding changes in UTLS ozone is exceptionally challenging because of large spatial and temporal variability and because of the difficulty of satellite measurements in the UTLS. It is also exceptionally important: for example, to understand climate impacts of radiatively active substances and to understand physical and biological effects of pollution transport and stratosphere-troposphere exchange (STE). Multi-decadal global observations of UTLS ozone are now available from numerous satellite platforms, as well as local and regional observations from aircraft, balloons, and lidar. The upper tropospheric (UT) jets and tropopauses are important drivers of composition variability in the UTLS, acting as transport barriers and controlling STE and long-range transport. We report here on investigations of relationships between extratropical UTLS ozone variability and dynamical diagnostics of mixing / transport barriers, Rossby Wave breaking, and stratosphere-troposphere exchange. We will view these relationships in the context of ozone mapped into dynamical coordinates with respect to the UTLS jets and / or the tropopause. This work will help provide direction for analyses within the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity, which aims to use dynamical coordinate mapping to help detect and attribute observed UTLS composition trends, and to project future data needs to better quantify those trends. The work we report on here will focus on satellite ozone observations (primarily from the Aura Microwave Limb Sounder, additionally from ACE-FTS and OSIRIS) and assimilated ozone and dynamical fields (from multiple reanalyses); we will also provide some examples of comparisons with aircraft and balloon observations.

Manney, Gloria L.↗

NASA NTRS2020

BioSentinel ISS Control Experiment Final Investigation Summary Form

Each payload has 18 fluidic cards and each fluidic card has 16 microfluidic wells, for a total of 288 wells. Card activation occurs at different time points throughout the 6-month mission and following ground commands. At each timepoint, two fluidic cards are filled with growth medium containing nutrients and a metabolic indicator dye. In addition to card filling, the temperature of the cards increases from ~4°C (stasis mode) to 23°C to allow for cell growth. The metabolic dye changes color from blue to pink, then pink to clearin the presence of metabolically active yeast cells. The colorimetric changes and cell growth are monitored using a 3-light-emitting diode(LED)optical detection system. The optical data determines how fast the cells are able to recover after accumulating radiation damage over time.After ground command initiation, all the fluidics, thermal and optical detection steps in BioSentinel are fully automated.The biosensor response data is compared to physical dosimetry data collected onboard the same payload. This dosimeter or linear energy transfer (LET)spectrometer is based on TimePix chip technology. This chip measures the total ionizing radiation dose in addition to calculating the LET of each particle that traverses its sensor, thus allowing researchers to characterize the radiation environment around the payload.The biological response (and physical dosimetry) on ISS over time is compared to the deep space mission and to data obtained on the ground.This analysis provides insight on the biological effects of the space radiation exposure in preparation for future long-duration missions to space and inhabitation beyond low-Earth orbit (LEO).

BioSentinel↗

NASA NTRSDate not supplied

Impact of Radiation Quality on Microdosimetry Calculation

Microdosimetry consists of studying energy deposition events in irradiated targets of volume typically of the order of a cell. The probability density 𝑓(𝑧,𝐷) of energy deposition𝑧(specific energy) in a target, exposed to an irradiation dose 𝐷,can be used to correlate inhomogeneous energy deposition events at the micro-scale(track structure)with biological responses(e.g., cell injury)[1]. Microdosimetry studies allow a better understanding of basic mechanisms of the biological response, such as the origin of the increased biological effectiveness of high Linear Energy Transfer (LET) ions, partly responsible of radiation-exposure induced cancer risks of astronauts [2].

F. Poignant↗

NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to outbred mice data

Accurately quantifying the differences in radiation quality between space and terrestrial environments is important for predicting health risks for astronauts.Recently, Edmundson et al. 2020[1] provided valuable new results from out-bred mice linking tumor induction and genetic background aer exposure to low and high-LET radiation. The goal of the current study is to more rigorously estimate a relative biological effectiveness (RBE) factor by leveraging the solid tumor data from Edmundson et al. 2020. Excess relative risk (ERR) models and excess absolute risk (EAR) models were fit using Poisson regression similar to the models that the Radiation Effects Research Foundation uses to fit atomic bomb survivor data. Linear ERR and EAR slopes were simulated usingBayesian analyses, and RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope using the full posterior distribution.

Lori J. Chappell↗

NASA NTRSDate not supplied

NASA’s Ground-Based Microgravity Simulation Facility

Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogs have been widely used in space biology ground studies. Even though microgravity simulators do not produce all of the biological effects observed in the true microgravity environment, they provide alternative test platforms that are effective, affordable, and readily available to facilitate microgravity research. The Microgravity Simulation Support Facility (MSSF) at the National Aeronautics and Space Administration (NASA) John F. Kennedy Space Center (KSC) has been established for conducting short duration experiments, typically less than 1 month, utilizing a variety of microgravity simulation devices for research at different gravity levels. The simulators include, but are not limited to, 2D Clinostats, 3D Clinostats, Random Positioning Machines, and Rotating Wall Vessels. In this presentation, we will provide an overview of current MSSF capabilities, research conducted in MSSF, new technology developments, customized sample holder designs, and the physical characteristics of these microgravity simulators.

Ye Zhang↗

NASA NTRS2022

Evaluation of Multiple Methods for Calculating Gray Equivalent

The assessment of different algorithms to determine the Gray-Equivalent as defined in NASA-STD-3001 from a source of space radiation has been evaluated in this paper. The Gray-Equivalent applies an RBE (Relative Biological Effectiveness) to the dose seen at the organ of interest in a human phantom. The current design basis solar particle event was used in the assessments along with the August 1972 event modeled by J.H. King and with idealized spheres and two vehicle designs. Three different algorithms were used and compared. One of the algorithms was the current OLTARIS algorithm. This algorithm is astronaut orientation averaged, which is not what happens in a storm shelter during a solar particle event. Two other algorithms were proposed to eliminate this issue. It is clear that either algorithm will be adequate to satisfy NASA-STD-3001 requirements. This work recommends the algorithm which applies the RBEs to the phantom points instead of at the surface of the phantom as with the current OLTARIS algorithm.

Gray Equivalent↗

NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Radiation health risks are predominantly derived from low linear energy transfer (LET) terrestrial exposures; however, space radiation includes exposure to high-LET and high-charge, high-energy (HZE) particles. Accurately quantifying the differences in radiation quality between the space and terrestrial radiation environments is important for assessing and predicting health risks for astronauts. Weil et al. 2009 and 2014 used two different inbred mouse strains to study differences in hepatocellular carcinoma (HCC) tumorigenesis after exposures to low- and high- LET radiation. More recently, Edmundson et al. 2020 provided valuable new tumor data in outbred mice that were exposed to low- and high-LET radiation. The present study aims to rigorously investigate a relative biological effectiveness (RBE) factor by leveraging the HCC tumor data from Weil et al. 2009, Weil et al. 2014, and Edmundson et al. 2020. The three experiments were similarly designed, allowing the raw data to be combined into a pooled dataset to estimate excess relative risk (ERR) and excess absolute risk (EAR) models using Bayesian Poisson regression. These effect estimates from the pooled data provide greater power to calculate a data driven RBE. Extensive sensitivity analyses test the robustness of RBE estimates to various model assumptions. The following questions will be explored through the sensitivity analyses: • Is the shape of the dose response different for low-LET radiation and HZE radiation, indicating that RBE is a function of dose? • Does attained age modify the effect estimates differently for low-LET radiation and HZE radiation, indicating RBE is a function of attained age? • Are the effect estimates and RBE estimates different for inbred mouse strains and outbred mouse strains? • Do assumptions about differences in ERR models and EAR models change the estimated RBE? Additional studies would be needed to validate the findings from these exploratory analyses.

Lori J. Chappell↗

NASA NTRS2022

BioSentinel: Build your own BioSentinel Model!

BioSentinel will conduct the first study of the biological response to space radiation outside LEO since the Apollo missions. The project will investigate the biological effects of space radiation, and will provide an adaptable platform to perform human relevant measurements in multiple space environments in the future, including on lunar and Mars landers and orbiters.

BioSentinel↗

NASA NTRSDate not supplied

NASA's Ground-Based Microgravity Simulation Facility

Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogs have been widely used in space biology ground studies. Even though microgravity simulators do not produce all of the biological effects observed in the true microgravity environment, they provide alternative test platforms that are effective, affordable, and readily available to facilitate microgravity research. The Microgravity Simulation Support Facility (MSSF) at the National Aeronautics and Space Administration (NASA) John F. Kennedy Space Center (KSC) has been established for conducting short duration experiments, typically less than 1 month, utilizing a variety of microgravity simulation devices for research at different gravity levels. The simulators include, but are not limited to, 2D Clinostats, 3D Clinostats, Random Positioning Machines, and Rotating Wall Vessels. In this chapter, we will discuss current MSSF capabilities, development concepts, customized sample holder designs, and the physical characteristics of these microgravity simulators.

Ye Zhang↗

NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Lori J. Chappell↗

NASA NTRSDate not supplied

BioSentinel

Develop a deep space tool with autonomous life support technologies to study the biological effects of the space radiation environment.

BioSentinel↗