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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Predicting Cell Death and Mutation Frequency for a Wide Spectrum of LET by Assuming DNA Break Clustering Inside Repair Domains

Cosmic radiation, which is composed of high charged and energy (HZE) particles, is responsible for cell death and mutation, which may be involved in cancer induction. Mutations are consequences of mis-repaired DNA breaks – especially double-strand breaks (DSBs) – that induce inter- and intra-chromosomal rearrangements (translocations, deletions, inversion). In this study, a computer simulation model is used to investigate the clustering of DSBs in repair domains, previously evidenced by our group in human breast cells [1]. This model is calibrated with experimental data measuring persistent 53BP1 radiation-induced foci (RIF) and is used to explain the high relative biological effectiveness (RBE) of HZE for both cell death and DNA mutation frequencies. We first validate our DSB cluster model using a new track structure model deployed on a simple geometrical configuration for repair domains in the nucleus; then we extend the scope from cell death to mutation induction. This work suggests that mechanism based on DSB repair process can explain several biological effects induced by HZE particles on different type of living cells

Plante, Ianik↗
NASA NTRS2020

Smoking and Mortality Among US Astronauts

Astronauts have lower age-specific mortality risk than the U.S. general population from all natural causes of death, particularly cardiovascular disease and cancer. Yet, understanding if they are as healthy as their backgrounds predict they should be, requires that epidemiologists understand (and measure) all potentially confounding exposures in this cohort. Tobacco smoking prevalence has been measured in the U.S. astronaut cohort, but its impact on mortality has not been previously assessed. If smoking history has a negative impact on mortality, this could confound attempts to measure the relative health of astronauts.

Reynolds, Robert J.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16422-DND

The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Results from recent NAIRAS model updates and new data products are presented. In addition, current and ongoing radiation measurement campaigns and verification and validation efforts are discussed.

Christopher J Mertens↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10829-DND

Galactic cosmic rays (GCR) and solar energetic particles (SEP) are the primary sources of human exposure to high linear energy transfer (LET) radiation in the atmosphere. High-LET radiation is effective at directly breaking DNA strands in biological tissue, or producing chemically active radicals in tissue that alter the cell function, both of which can lead to cancer or other adverse health effects. A prototype operational nowcast model of air-crew radiation exposure is currently under development and funded by NASA. The model predicts air-crew radiation exposure levels from both GCR and SEP that may accompany solar storms. The new air-crew radiation exposure model is called the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) model. NAIRAS will provide global, data-driven, real-time exposure predictions of biologically harmful radiation at aviation altitudes. Observations are utilized from the ground (neutron monitors), from the atmosphere (the NCEP Global Forecast System), and from space (NASA/ACE and NOAA/GOES). Atmospheric observations characterize the overhead mass shielding and the ground- and space-based observations provide boundary conditions on the incident GCR and SEP particle flux distributions for transport and dosimetry calculations. Radiation exposure rates are calculated using the NASA physics-based HZETRN (High Charge (Z) and Energy TRaNsport) code. An overview of the NAIRAS model is given: the concept, design, prototype implementation status, data access, and example results. Issues encountered thus far and known and/or anticipated hurdles to research to operations transition are also discussed.

Christopher J Mertens↗
NASA NTRSDate not supplied

The Cosmic Radiation Symphony: Soundtrack for a Journey to Mars

Space radiation (SR) is a constant threat to astronauts who journey away from the Earth’s protective magnetosphere. Galactic cosmic rays (GCR) are atomic nuclei from remnants of supernovae and are omnipresent in outer space. These ionized particles travel close to the speed of light and when they traverse biological material,they leave behind a path of damage. Another space radiation threat is from our sun when solar particle events (SPEs), or bursts of energetic protons,occur. Exposure to space radiation can lead to cancer, cardiovascular disease,immune dysfunction, and cognitive and behavioral decrements. Yet humans cannot see, smell, taste, hear,or feel radiation, making it less tangible than other health threats and much more difficult to describe.This is an important gap in risk communication that the Space Radiation Element is working to close within NASA’s Human Research Program. Music and art are powerful means of communicating human emotions and feelings and are effective and creative ways to convey other types of information. In this work, the sonification process was used to transcribe or translate the physical nature of the SR environment on a 3-year mission to Mars into sound, a format perceptible to the human ear. A visual representation for the journey was also developed so the audience can both hear and envision the chronic presence of GCR and the acute and large bursts of energy present in SPEs. Data for this project were derived from the Radiation Assessment Detector on the NASA Curiosity Rover during its outbound cruise to Mars and on the Martian surface, as well as from models of the space radiation environment behind spacecraft shielding. Our data-driven audiovisual composition was realized using custom programmed digital signal processing and graphic design in the programming languages Pure Data and Processing. The data sonification was contextualized in time and space by calculating and visualizing the location of the spacecraft in relation to the other planets during the Mars mission. The finished work is a unique and powerful means of communicating the presence and risk of space radiation, accessible by people of all ages and scientific backgrounds

Richard Snow↗
NASA NTRSDate not supplied

Predicting cell death and mutation frequency for a wide spectrum of LET and across cell lines from DNA break clustering inside repair domains

Cosmic radiation, which is composed of high charged and energy (HZE) particles, is responsible for cell death and mutation, which may be involved in cancer induction. Mutations are consequences of mis-repaired DNA breaks – especially double-strand breaks (DSBs) – that induce inter- and intra-chromosomal rearrangements (translocations, deletions, inversion). In this study, a computer simulation model is used to investigate the clustering of DSBs in repair domains, previously evidenced by our group in human breast cells. This model is calibrated with experimental data measuring persistent 53BP1 radiation-induced foci (RIF) and is used to explain the high relative biological effectiveness (RBE) of HZE for both cell death and DNA mutation frequencies. We first validate our DSB cluster model using a new track structure model deployed on a simple geometrical configuration for repair domains in the nucleus; then we extend the scope from cell death to mutation induction. This work suggests that mechanism based on DSB repair process can explain several biological effects induced by HZE particles on different type of living cells.

Ianik Plante↗
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 NTRS2021

Comparison of Health and Performance Risk for Accelerated Mars Mission Scenarios

This document details the results for a quantitative estimate of the difference in human health and performance risk that crews would face for two hypothetical variations on Mars mission scenarios: an Accelerated Mars Mission (AMM) and a Standard Mars Mission(SMM).NASA goals for Mars mission concepts, duration, and tasks have varied over the years. While neither of the cases considered here are likely to accurately represent the initial mission to Mars, the exercise of evaluating significant differences in mission duration from an astronaut health perspective can provide bounding insight to the level of risk that is likely to be encountered in an eventual Mars mission. Medical Probabilistic Risk Assessment using the Integrated Medical Model (IMM)(1–3)and the NASA Space Radiation Cancer Risk Model (NSCR)(4,5) are used here to help mission planners gain the best insight currently available into the expected magnitude of impacts to astronaut health when undertaking a Mars mission. These impacts occur both in-mission as well as in the long-term health of the astronauts post-mission. These evaluations are currently the best available modeling estimates to characterize and bound the health risks in a proposed mission domain where humans have no experience.

Erik Antonsen↗
NASA NTRSDate not supplied

Radiocatalyst for Radiation Protection and Microbial Control

Radiocatalysts are materials that reduce the activation energy required to split water into hydrogen and reactive oxygen species (ROS). They are activated by radiation and can be used to improve the ability of water to act as a radiation barrier. This paper reports the results of an experimental evaluation of a gold radiocatalyst. This work provides a preliminary evaluation of the ability of these types of catalysts to increase the efficiency of water hydrolysis when exposed to different types of radiation (GCR). Although the radiation exposure devices used in this testing were not capable of generating radiation as diverse as is commonly found in space, the testing is useful in evaluating the function of these radiocatalytic nanoparticles when exposed to a a subset of the types of radiation that are found in GCR. The results are relevant to evaluating the use of this material for both space radiation protection and the production of useful byproducts, such as ROS, which can be used to maintain the sterility of stored water supplies. Radiocatalysts are materials typically used in radiation cancer therapy to improve the kill rate of tumors. These nanoparticles can be directly injected into tumors or functionalized to enter tumor cells via the blood stream. When they are exposed to radiation, they produce ROS. ROS are water hydrolysis products such as OH¯, O¯, O3, H2O2. This study used radiocatalytic 1.8 nm gold nanoparticles functionalized with citrate. These nanoparticles were tested through exposure to Xrays, 56Fe particles and gamma rays to demonstrate activity to a variety of radiation sources. The results demonstrate that radiocatalysts can improve the radiation absorption of water by a factor of 3 to 8 and can effectively kill bacteria at radiation levels above 1 Gy.

radiocatalyst radiation protection biocide↗
NASA NTRSDate not supplied

Overview of the Translational Radiation Research and Countermeasures (TRRaC) Project in Space Radiation

The Translational Radiation Research and Countermeasures (TRRaC) Project was initiated by the Space Radiation (SR) Element within NASA’s Human Research Program (HRP) to support the SR mission to understand and characterize the space radiation environment, understand and quantify radiation-associated risks, and mitigate the impacts of radiation-induced adverse health outcomes to enable human space exploration. TRRaC’s mission is to translate radiation research results from experimental studies and epidemiological data to humans and astronauts using bioinformatics and computational modeling. TRRaC will leverage existing datasets such as those available from NASA’s GeneLab repository and human medical radiation exposure registries, along with relevant data generated from ground-based research at molecular, cellular, tissue, and system levels, to: (1) refine the radiation dose rate effectiveness factor, (2) characterize radiation quality effects to improve estimates of the risk of exposure-induced death (REID) from space-relevant radiation exposures, and (3) identify pathways and biomarkers for cancer, cardiovascular disease, and central nervous system changes that are impacted by space radiation exposure.

Parastou Eslami↗
NASA NTRSDate not supplied

An Open-Science Approach to Address Individual Response to Simulated GCR In Genetically Diverse Populations of Mice and Humans

This project addresses the challenge of understanding and predicting individual radiation sensitivity by integrating genetics, demographics and biomarker characteristics across species (mice and humans). We hypothesize that ex vivo DNA repair response to GCR components is a central determinant of cancer risk from space radiation and can serve as a biomarker of radiation risk in combination with genetics. Automated image quantification of 53BP1+ radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET in non-immortalized primary skin fibroblasts derived from 76 mice across 15 strains (5 inbred reference strains and 10 collaborative-cross strains) exposed to X rays (0.1, 1 and 4 Gy), 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm), as well as in peripheral blood mononuclear cells (PBMCs) from 768 healthy donors (matched ethnicity, 50/50 male/female, 18-70 years old) exposed to gamma rays (0.1 and 1 Gy), 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm). A genome-wide association study (GWAS) was performed on the mouse strains between DNA damage responses to space radiation and single nucleotide polymorphisms (SNPs). We found SNPs, which were significantly associated to the RIF phenotype, mapped to genes and pathways that are functionally linked to health hazards for deep space exploration (e.g. carcinogenesis, nervous system damage and immune dysfunction). Some of these SNPs were located within protein coding regions, potentially interfering with protein functions and providing promising genetic targets for countermeasures. We also found correlations between both spontaneous and radiation-induced DNA damage and SNPs mapped to pathways associated with cellular metabolism. GWAS is undergoing for the human data. All data have been made available via the NASA Space Biology Open-Science database (genelab.nasa.gov) and we will discuss how various genomic and transcriptomic datasets can be accessed for modeling and integrated using machine learning methods for discovering new radiation biology.

Sylvain V Costes↗
NASA NTRS2021

Predicting the Functional State of Protein Kinases Using Interpretable Graph Neural Networks

Kinases are a family of proteins that function as molecular switches, regulating several essential cellular activities such as cell proliferation. Dysfunctional kinases are implicated in several types of cancers and hence they are actively pursued as drug targets. Given the vast number of complex kinase structures that are available in the protein data bank (PDB), there is a necessity to develop methodologies that can identify structurally important moieties of the kinases in an automated fashion, for such techniques can be instrumental in identifying novel drug targets. In this work, we develop a graph neural network (GNN) based deep learning framework for classifying the functionally active and inactive states of a large set of eukaryotic protein kinases, making use of their 3D structure from the PDB. We show that GNN based machine learning models can classify protein states with an accuracy greater than 97%. We further use the GNN models to automatically identify regions of the kinases that are important for its function. For this purpose, Gradient-weighted Class Activation Mapping (Grad-CAM) was implemented on the protein graphs. Remarkably, Grad-CAM consistently identifies the highly conserved DFG motif as the most important part of the protein across the entire kinome, without any prior input. Other regions of the hydrophobic core such as the HRD motif were also identified by the interpretable GNN framework, consistent with the literature. We discuss the significance of each of these regions in detail.

Ashwin Ravichandran↗
NASA NTRSDate not supplied

Retrospectives: Current State of Knowledge on the Intersection of Spaceflight Stressors and Microbial Risks to Crew and Craft

OVERVIEW The spaceflight environment has several unique stressors that affect the health of both the crew and the spacecraft. An area of continued, albeit incomplete, study is the interaction of these stressors on microbial populations inherent to both astronauts and spacecraft surfaces and systems. A primary concern is the potential for the spaceflight environment to perturb the phenotype of these populations towards negative outcomes for crew and craft. In order to effectively mitigate these potential risks, they must first be characterized. We performed a retrospective literature analysis to assess the current state of knowledge regarding the affects of ionizing radiation and elevated CO2 on relevant microbial populations. The results of these retrospectives will guide next steps in the decisions of what (if any) further studies should be pursued and to guide decisions of the need for countermeasures. STRESSORS Ionizing radiation. The health risk involved with increased exposure to cosmic radiation has been studied in crew for 35+ years, with human health and cancer risk being the main focus. However, space radiation could also affect both the resident microorganisms aboard the ISS and the normal, healthy astronaut microbiomes that are of direct concern for crew health. A retrospective review of over 250 publications was accomplished looking at the impact of cumulative ionizing radiation doses lower than 3 Gy (chronic or acute) on microbial populations. Elevated CO2. The health risk involved with elevated atmospheric CO2 in spacecraft, primarily focusing on human toxicological risks, is understudied. The current Spaceflight Maximum Allowance Concentration for 24-hour average CO2 is 0.4% (3 mm Hg), which is significantly higher than terrestrial levels (0.04%). Whether these elevated ambient CO2 levels aboard spacecraft influence the diversity and phenotypic responses of the resident microbial communities from both the spacecraft environment (air, surface, water) and crew members (gut, nasal, skin microbiomes) is not known. A retrospective review was accomplished looking at the impact of chronic CO2 exposure up to 0.7% (5 mm Hg) for up to 6 months and acute exposure up to 2.6% (20 mm Hg) for up to 24 hours. CONCLUSIONS: MICROBIOME OF THE BUILT ENVIRONMENT The microbiome of the built spacecraft environment has been sampled consistently over the course of human spaceflight and significant advancements have been made in identifying microbial populations on the ISS. The dominant source of microbes on spacecraft surfaces are human-derived. Once in the spacecraft built environment, the extreme environment selects for features that enhance survival. While efforts to understand potential antibiotic resistance and pathogenicity of ISS isolates is robust, there is little to no understanding of which spaceflight environmental stressors, to include ionizing radiation or elevated CO2, drive the evolutionary trajectory of spacecraft-associated microbial populations. CONCLUSIONS: MICROBE-HOST INTERACTIONS The host-microbiome field has emerged as an important factor in human health on Earth as well in spaceflight. The field is struggling with the complexity of the system under investigation as there is substantial taxonomic and functional heterogeneity in these communities, making it difficult to establish clear stimulus-response dynamics. Taxonomic characterization is the norm; however, the functional role of each community member is key to linking environmental perturbations to potential dysbiosis. For both ionizing radiation and elevated CO2, the likely target of the perturbation is the host tissue, not the microbes themselves.. Any resulting changes to the microbial community composition and/or function is likely a result of adapting to those changes in the host physiology. RECOMMENDATIONS Emphasize functional characterization as opposed to taxonomic characterization of microbial communities. Increase the number of investigations using chronic, spaceflight-relevant doses of ionizing radiation. MoBE studies should move away from observational studies towards predictive modeling of community dynamics. Continue to develop scale-down models, such as tissues-on-a-chip & defined microbial communities. Focus on the crew response to elevated CO2 over MoBE considerations. Assess how direct contact with the hypercapnic environment affects skin microbiome dynamics.

retrospective↗
NASA NTRS2021

Oncogenic Integration of Nucleotide Metabolism via Fatty Acid Synthase in Non-Hodgkin Lymphoma

Metabolic dysfunctions enabling increased nucleotide biosynthesis are necessary for supporting malignant proliferation. Our investigations indicate that upregulation of fatty acid synthase (FASN) and de novo lipogenesis, commonly observed in many cancers, are associated with nucleotide metabolic dysfunction in lymphoma. The results from our experiments showed that ribonucleotide and deoxyribonucleotide pool depletion, suppression of global RNA/DNA synthesis, and cell cycle inhibition occurred in the presence of FASN inhibition. Subsequently, we observed that FASN inhibition caused metabolic blockade in the rate-limiting step of the oxidative branch of the pentose phosphate pathway (oxPPP) catalyzed by phosphogluconate dehydrogenase (PGDH). Furthermore, we determined that FASN inhibitor treatment resulted in NADPH accumulation and inhibition of PGDH enzyme activity. NADPH is a cofactor utilized by FASN, also a known allosteric inhibitor of PGDH. Through cell-free enzyme assays consisting of FASN and PGDH, we delineated that the PGDH-catalyzed ribulose-5-phosphate synthesis is enhanced in the presence of FASN and is suppressed by increasing concentrations of NADPH. Additionally, we observed that FASN and PGDH were colocalized in the cytosol. The results from these experiments led us to conclude that NADP–NADPH turnover and the reciprocal stimulation of FASN and PGDH catalysis are involved in promoting oxPPP and nucleotide biosynthesis in lymphoma. Finally, a transcriptomic analysis of non-Hodgkin’s lymphoma (n = 624) revealed the increased expression of genes associated with metabolic functions interlinked with oxPPP, while the expression of genes participating in oxPPP remained unaltered. Together we conclude that FASN–PGDH enzymatic interactions are involved in enabling oxPPP and nucleotide metabolic dysfunction in lymphoma tumors.

Non-Hodgkin lymphoma↗
NASA NTRSDate not supplied

Space Radiation Technologies for Human Missions beyond Low-Earth-Orbit

Ionizing radiation exposure is a pervasive occupational risk to astronauts and remains a major health risk associated with human exploration beyond low-Earth-orbit. Sustained lunar and Mars exploration crew will be at increased risk of radiogenic cancers and cardiovascular disease, as well as, the potential for in-mission performance decrements, immune system decrements, and late neurodegenerative conditions impacting crew health. Optimizing astronaut space radiation protection will incorporate both physical and biological radiological aspects and will implement protection strategies that span pre-mission, in-flight, and post mission timelines. Major facets of physical risk mitigation include accuracy in predicting the space radiation solar environment, monitoring environmental and human exposures, and minimizing exposure through vehicle shielding and design. Biological mitigation facets include understanding and predicting biological response to the space environment, developing advanced medical countermeasures, and identifying appropriate surveillance strategies to preserve long-term health. Coordinated investments in these major capability areas will support development of an integrated radiation protection solution to minimize astronaut risk for moon to Mars exploration missions.

Lisa C Simonsen↗
NASA NTRSDate not supplied

My Journey to NASA and role as a (Molecular) Biologist…

My journey to NASA started in undergrad, where I performed microbiology research and became hooked in the STEM fields. From there I earned a Ph.D. in Biochemistry and Molecular Biology from Mayo Graduate school where I performed Pancreatic Cancer research and then went on to perform postdoctoral research in Developmental Biology at the University of Miami. Trained as a biologist, I landed my first job at NASA as a mission scientist on the Rodent Research project. As a mission scientist, I led science activities associated with development, flight, and post-flight analysis of rodent research missions on the ISS in consultation with project engineers, operational specialists, mission PI(s), and mission Implementation Partner(s). I also assessed the feasibility of scientific experiments as a technical and scientific expert in rodent research on the ISS. Eager to learn more about the molecular changes that occur as a result of spaceflight exposure, I transitioned to the NASA GeneLab project where I eventually became the data processing lead. NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. To maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. During the CA Space Grant Women in STEM Panel event, I will provide an overview of my journey to NASA including my work at NASA on both the Rodent Research and GeneLab projects. I will conclude by providing resources for opportunities to work with GeneLab and NASA at large followed by links to programs designed specifically to engage women in STEM fields.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗
NASA NTRSDate not supplied

My Journey to NASA and Role as a (Molecular) Biologist…

My journey to NASA started in undergrad, where I performed microbiology research and became hooked in the STEM fields. From there I earned a Ph.D. in Biochemistry and Molecular Biology from Mayo Graduate school where I performed Pancreatic Cancer research and then went on to perform postdoctoral research in Developmental Biology at the University of Miami. Trained as a biologist, I landed my first job at NASA as a mission scientist on the Rodent Research project. As a mission scientist, I led science activities associated with development, flight, and post-flight analysis of rodent research missions on the ISS in consultation with project engineers, operational specialists, mission PI(s), and mission Implementation Partner(s). I also assessed the feasibility of scientific experiments as a technical and scientific expert in rodent research on the ISS. Eager to learn more about the molecular changes that occur as a result of spaceflight exposure, I transitioned to the NASA GeneLab project where I eventually became the data processing lead. NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. To maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. During the NASA Ames ECN at Lincoln HS Virtual Panel event, I will provide an overview of my journey to NASA including my work at NASA on both the Rodent Research and GeneLab projects. I will conclude by providing resources for opportunities to work with GeneLab and NASA at large followed by links to programs designed specifically to engage women in STEM fields.

Amanda M Saravia-Butler↗