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NASA NTRS1979

Biological and Organic Chemical Decomposition of Silicates

The weathering of silicate rocks and minerals, an important concern of geologists and geochemists for many years, traditionally has been approached from strictly physical and chemical points of view. Biological effects were either unrecognized, ignored, or were mentioned in passing to account for such phenomena as the accumulation of organic matter in sediments or the generation of reducing environments. A major exception occurred in soil science where agricultural scientists, studying the factors important in the development of soils and their ability to nourish and sustain various crops, laid the foundation for much of what is known of the biological breakdown of silicate rocks and minerals. The advent of the space age accelerated the realization that many environmental problems and geochemical processes on Earth can only be understood in terms of ecosystems. This in turn, spurred renewed interest and activity among modem biologists, geologists and soil scientists attempting to unravel the intimate relations between biology and the weathering of silicate rocks and minerals of the earth's surface.

Sliverman, M. P.↗

NASA NTRSDate not supplied

Evaluating the Feasibility of Data Simulation for Radiation Research: Estimating RBE Values for HZE Radiation

As the drive for deep space exploration intensifies, a comprehensive understanding of the health effects of radiation exposure becomes paramount to the future of human space flight. However, epidemiological data for radiation exposure, particularly to high-energy (HZE) ions, is limited, partially due to the financial and logistical costs of radiation studies. As an alternative, this study aims to assess the viability of data simulation strategies to accurately model potential study parameters prior to utilizing laboratory conditions. This study estimates a relative biological effectiveness (RBE) factor based on the solid tumor data for outbred mice provided by Edmundson et al. 2020. Excess relative risk (ERR) models for HZE-Fe ions and gamma radiation were estimated using Poisson regression with Weibull models to represent the background solid tumor hazard without radiation. RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope. The parameters from these models were then applied to simulate iterations of 300 datasets across HZE-Fe doses of 0.05, 0.2, 0.4, and 0.75 Gy; gamma radiation doses of 0.75, 2, and 3 Gy, as well as an unirradiated control group. Sample size per dose varied from 100-500 mice across simulations (800-4000 mice total per dataset). 1500 datasets were generated total (300 each for sample sizes 800, 1600, 3200, and 4000). For each dataset, ERR per radiation type and RBE for HZE-Fe were calculated. The RBE from the Edmondson data was calculated to be 5.55. The RBEs from the simulated data converged around this value across the increasing sample sizes. For n = 4000, the mean RBE across the 300 datasets was 5.71 (95% CI: 5.47-5.95). These results suggest that RBEs calculated from simulated data are credible. Based on this exploration, data simulation is a viable method of testing radiation studies. It provides a method of testing study assumptions and refining research questions prior to embarking on costly laboratory experiments.

Sneha Mehta↗

NASA NTRS2001

NO, nitrotyrosine, and cyclic GMP in signal transduction

Over the past 25 years, the role of nitric oxide (NO) in biology has evolved from being recognized as an environmental pollutant to an endogenously produced substance involved in cell communication and signal transduction. NO is produced by a family of enzymes called nitric oxide synthases (NOSs), which can be stimulated by a variety of factors that mediate responses to various stimuli. NO can initiate its biological effects through activation of the heterodimeric enzyme, soluble guanylyl cyclase (sGC), or through several other chemical reactions. Activation of sGC results in the production of 3',5'-cyclic guanosine monophosphate (cGMP), an intracellular second messenger signaling molecule, which can subsequently mediate such diverse physiological events such as vasodilatation and immunomodulation. Chemically reactive NO can affect physiological changes through modifications to cellular proteins, one of which is tyrosine nitration. The demonstration that NO is involved in so many biological pathways indicates the importance of this endogenously produced substance, and suggests that there is much more to be discovered about its role in biology in years to come.

Non-NASA Center↗

NASA NTRS1992

Embryogenesis and organogenesis of Carausius morosus under space flight conditions (7-IML-1)

The experiment is part of a radiobiological space research program to obtain experimental data on the biological effectiveness of the structured component of cosmic radiation during spaceflight. In this proposed experiment, Carausius morosus embryos of different ages will develop under spaceflight conditions. The experiment is designed to determine the influence of galactic heavy ions of very high energy deposition in microgravity on developmental processes of different radiation sensitivity and regenerative capacity. Layers of Carausius morosus eggs are sandwiched between different track detectors (cellulose nitrate, CR39). This method allows the localization of the trajectory of each heavy ion in the biological layer and the identification of the site of the penetration inside the egg.

Buecker, D. H.↗

NASA NTRS1989

Radiation effects in Caenorhabditis elegans - Mutagenesis by high and low LET ionizing radiation

The nematode C. elegans was used to measure the effectiveness of high-energy ionized particles in the induction of three types of genetic lesions. Recessive lethal mutations in a 40-map unit autosomal region, sterility, and X-chromosome nondisjunction or damage were investigated. Induction rates were measured as a function of linear energy transfer, LET(infinity), for nine ions of atomic nunmber 1-57 accelerated at the BEVALAC accelerator. Linear kinetics were observed for all three types of lesions within the dose/fluence ranges tested and were found to vary strongly as a function of particle LET(infinity). Relative biological effectiveness (RBE) values of up to 4.2 were measured, and action cross sections were calculated and compared to mutagenic responses in other systems.

Nelson, Gregory A.↗

NASA NTRS2012

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗

NASA NTRS2015

Prototype Biology-Based Radiation Risk Module Project

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Terrier, Douglas↗

NASA NTRS2010

Non-Targeted Effects and the Dose Response for Heavy Ion Tumorigenesis

BACKGROUND: There is no human epidemiology data available to estimate the heavy ion cancer risks experienced by astronauts in space. Studies of tumor induction in mice are a necessary step to estimate risks to astronauts. Previous experimental data can be better utilized to model dose response for heavy ion tumorigenesis and plan future low dose studies. DOSE RESPONSE MODELS: The Harderian Gland data of Alpen et al.[1-3] was re-analyzed [4] using non-linear least square regression. The data set measured the induction of Harderian gland tumors in mice by high-energy protons, helium, neon, iron, niobium and lanthanum with LET s ranging from 0.4 to 950 keV/micron. We were able to strengthen the individual ion models by combining data for all ions into a model that relates both radiation dose and LET for the ion to tumor prevalence. We compared models based on Targeted Effects (TE) to one motivated by Non-targeted Effects (NTE) that included a bystander term that increased tumor induction at low doses non-linearly. When comparing fitted models to the experimental data, we considered the adjusted R2, the Akaike Information Criteria (AIC), and the Bayesian Information Criteria (BIC) to test for Goodness of fit.In the adjusted R2test, the model with the highest R2values provides a better fit to the available data. In the AIC and BIC tests, the model with the smaller values of the summary value provides the better fit. The non-linear NTE models fit the combined data better than the TE models that are linear at low doses. We evaluated the differences in the relative biological effectiveness (RBE) and found the NTE model provides a higher RBE at low dose compared to the TE model. POWER ANALYSIS: The final NTE model estimates were used to simulate example data to consider the design of new experiments to detect NTE at low dose for validation. Power and sample sizes were calculated for a variety of radiation qualities including some not considered in the Harderian Gland data set and with different background tumor incidences. We considered different experimental designs with varying number of doses and varying low doses dependant on the LET of the radiation. The optimal design to detect a NTE for an individual ion had 4 doses equally spaced below a maximal dose where bending due to cell sterilization was < 2%. For example at 100 keV/micron we would irradiate at 0.03 Gy, 0.065 Gy, 0.13 Gy, and 0.26 Gy and require 850 mice including a control dose for a sensitivity to detect NTE with 80% power. Sample sizes could be improved by combining ions similar to the methods used with the Harderian Gland data.

Chappelli, Lori J.↗

NASA NTRSDate not supplied

Data Sharing in Radiobiology; Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally „Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗

NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗

NASA NTRS2003

Growth and Metabolism of the Green Alga, Chlorella Pyrenoidosa, in Simulated Microgravity

The effect of microgravity on living organisms during space flight has been a topic of interest for some time, and a substantial body of knowledge on the subject has accumulated. Despite this, comparatively little information is available regarding the influence of microgravity on algae, even though it has been suggested for long duration flight or occupancy in space that plant growth systems, including both higher plants and algae, are likely to be necessary for bioregenerative life support systems. High-Aspect-Ratio Rotating-Wall Vessel or HARV bioreactors developed at Johnson Space Center provide a laboratory-based approach to investigating the effects of microgravity on cellular reactions. In this study, the HARV bioreactor was used to examine the influence of simulated microgravity on the growth and metabolism of the green alga, Chlorella pyrenoidosa. After the first 2 days of culture, cell numbers increased more slowly in simulated microgravity than in the HARV gravity control; after 7 days, growth in simulated microgravity was just over half (58%) that of the gravity control and at 14 days it was less than half (42%). Chlorophyll and protein were also followed as indices of cell competence and function; as with growth, after 2-3 days, protein and chlorophyll levels were reduced in modeled microgravity compared to gravity controls. Photosynthesis is a sensitive biochemical index of the fitness of photosynthetic organisms; thus, CO2-dependent O2 evolution was tested as a measure of photosynthetic capacity of cells grown in simulated microgravity. When data were expressed with respect to cell number, modeled microgravity appeared to have little effect on CO2 fixation. Thus, even though the overall growth rate was lower for cells cultured in microgravity, the photosynthetic capacity of the cells appears to be unaffected. Cells grown in simulated microgravity formed loose clumps or aggregates within about 2 days of culture, with aggregation increasing over time. Presently, the basis for, or significance of, the cell aggregation is unknown. The results from this study suggest that cell growth and morphological characteristics of green algae may be altered by culture in simulated microgravity. The data obtained to date should provide a solid basis for additional experimentation regarding the influence of modeled microgravity on cell morphology, physiological activity, protein production and possibly gene expression in algal and plant cell systems. The final aim of the study is to provide useful information to elucidate the underlying mechanism for the biological effects of microgravity on cells.

Mills, W. Ronald↗

NASA NTRS1995

Effects of alpha-particles on survival and chromosomal aberrations in human mammary epithelial cells

We have studied the radiation responses of a human mammary epithelial cell line, H184B5 F5-1 M/10. This cell line was derived from primary mammary cells after treatment with chemicals and heavy ions. The F5-1 M/10 cells are immortal, density-inhibited in growth, and non-tumorigenic in athymic nude mice and represent an in vitro model of the human epithelium for radiation studies. Because epithelial cells are the target of alpha-particles emitted from radon daughters, we concentrated our studies on the efficiency of alpha-particles. Confluent cultures of M/10 cells were exposed to accelerated alpha-particles [beam energy incident at the cell monolayer = 3.85 MeV, incident linear energy transfer (LET) in cell = 109 keV/microns] and, for comparison, to 80 kVp x-rays. The following endpoints were studied: (1) survival, (2) chromosome aberrations at the first postirradiation mitosis, and (3) chromosome alterations at later passages following irradiation. The survival curve was exponential for alpha-particles (D0 = 0.73 +/- 0.04 Gy), while a shoulder was observed for x-rays (alpha/beta = 2.9 Gy; D0 = 2.5 Gy, extrapolation number 1.6). The relative biological effectiveness (RBE) of high-LET alpha-particles for human epithelial cell killing was 3.3 at 37% survival. Dose-response curves for the induction of chromosome aberrations were linear for alpha-particles and linearquadratic for x-rays. The RBE for the induction of chromosome aberrations varied with the type of aberration scored and was high (about 5) for chromosome breaks and low (about 2) for chromosome exchanges.(ABSTRACT TRUNCATED AT 250 WORDS).

NASA Center JSC↗

NASA NTRS2017

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

The high relative biological effectiveness (RBE) of high charged and energy (HZE) particles for cell death, DNA mutations and cancer remain based on experimental data. In this work, we propose that the existence of DNA repair domains is sufficient to predict both cell death and mutation frequencies for any LET by only taking into account experimental data from low-LET, offering one mechanism for RBE across LET. We hypothesize that whenever multiple DNA double-strand breaks (DSBs) are generated within the same DNA repair domain, DSBs are actively regrouped for more efficient repair [1]. This hypothesis has been supported by the low-LET sublinear dose response observed at doses greater than ~1Gy for 53BP1 radiation-induced foci (RIF) reflecting increasing DSB/RIF with dose [2]. Previously, we modeled radiation-induced cell death of human breast cells by first inferring the size of these domains from the dose dependence of low-LET RIF, and by associating a lethality factor to the number of pairs of DSBs in each RIF [1]. In this work, we first integrate the new NASA computer models RITCARD (Relativistic Ion Tracks, Chromosome Aberrations, Repair, and Damage) [3] and BDSTracks (Biological Damage by Stochastic Tracks) for a more accurate microdosimetry and a better model of the nuclear organization to predict the location of DSBs. A large array of particles and energy are simulated, covering more than three orders of magnitude for LET (~1-1000 keV/Âµm). Next, we extend our previous model to predict mutation frequencies by assuming that clustered DSBs increase mutation probability, which is formalized by the mutation frequency being linearly dependent on both the number of DSBs and the number of pairs of DSBs inside individual RIF. Linear coefficients are estimated so that simulations predict accurately mutation frequencies observed in Chinese hamster cells exposed to low-LET. Keeping these coefficients unchanged, we then predict mutation frequencies induced by HZE by simulating DSBs and obtain RBEs for mutations and cell death following the expected experimental bell shape for LET dependence. We also observe an orientation effect that needs to be confirmed, showing different RBE depending on the angle of the HZE beam hitting the main axis of the cell.

Plante, Ianik↗

NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS and ISS ground control segments.

BioSentinel↗

NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

BioSentinel↗

NASA NTRS2024

Enhancing the Payload Development Process for Lunar Gateway and Lunar Surface Science & Exploration: Space Biology Beyond Low-Earth-Orbit Instrumentation and Science Series (BLISS) Science Working Group 2023-2024 Annual Report

Space biology BLEO research is inherently driven by the differences between the LEO and BLEO environments, which can be broadly characterized by the five-hazard “RIDGE” paradigm (Radiation, Isolation, Distance, Gravity, Environment, e.g., similar to Figure 2 in (1)). Thus, the envisioned goals over the next decade will include using the cislunar and lunar surface environments to (A) characterize deep-space environments including biological effects of radiation and other stressors, (B) gain experience from isolation of very small groups in very small enclosures, (C) learn to compensate for distance from Earth via in situ resource utilization (ISRU) and bioregenerative life support, (D) gain assurance that all aspects of deep-space exploration can proceed in altered or artificial gravity environments, (E) develop essential adaptation scenarios for the built (e.g., low pressure) and external (e.g., temperature extremes, dust) environments.

Biology↗

NASA NTRS2010

Human Research Program Space Radiation Standing Review Panel (SRP)

The Space Radiation Standing Review Panel (SRP) met at the NASA Johnson Space Center (JSC) on December 9-11, 2009 to discuss the areas of current and future research targeted by the Space Radiation Program Element (SRPE) of the Human Research Program (HRP). Using evidence-based knowledge as a background for identified risks to astronaut health and performance, NASA had identified gaps in knowledge to address those risks. Ongoing and proposed tasks were presented to address the gaps. The charge to the Space Radiation SRP was to review the gaps, evaluate whether the tasks addressed these gaps and to make recommendations to NASA s HRP Science Management Office regarding the SRP's review. The SRP was requested to evaluate the practicality of the proposed efforts in light of the demands placed on the HRP. Several presentations were made to the SRP during the site visit and the SRP spent sufficient time to address the SRP charge. The SRP made a final debriefing to the HRP Program Scientist, Dr. John B. Charles, on December 11, 2009. The SRP noted that current SRPE strategy is properly science-based and views this as the best assurance of the likelihood that answers to the questions posed as gaps in knowledge can be found, that the uncertainty in risk estimates can be reduced, and that a solid, cost-effective approach to risk reduction solutions is being developed. The current approach of the SRPE, based on the use of carefully focused research solicitations, requiring thorough peer-review and approaches demonstrated to be on the path to answering the NASA strategic questions, addressed to a broad extramural community of qualified scientists, optimally positioned to take advantage of serendipitous discoveries and to leverage scientific advances made elsewhere, is sound and appropriate. The SRP viewed with concern statements by HRP implying that the only science legitimately deserving support should be "applied" or, in some instances that the very term "research" might be frowned upon. We understand the desire of management to ensure that research stay focused on mission objectives, but the terms used are code words fraught with different meaning for scientists. Such expressions, taken at face value, convey a profoundly flawed view of science, can easily lead down counterproductive paths, and have the potential to irretrievably corrupt NASA requirements. The SRP understands and endorses the mandate to keep research efforts focused on the mission needs. However, thoughtful application of knowledge gained by understanding the mechanisms and pathways of biological effects cannot be replaced.

Woloschak, Gayle↗

NASA NTRSDate not supplied

RadLab: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on multiple spacecraft in and beyond low Earth orbit continuously monitor and collect space radiation data and transmit it back to Earth. These data are of vast importance to space biology research, as ionizing radiation affects living organisms—astronauts and non-human experiment subjects alike—placing them at higher risk of carcinogenesis, degenerative diseases, and radiation sickness. Therefore, knowledge of the biological effects of space radiation is essential for planning future crewed missions beyond low Earth orbit. The RadLab project, initiated by GeneLab and ALSDA (the Open Science Data Repository; OSDR) and sponsored by the NASA Human Research Program, is a new effort aimed at connecting dosimetry data from radiation detectors located on the International Space Station (ISS), as well as other spacecraft. To date, access to these data has been fragmented across space agencies and databases; to address this issue, we have developed an application programming interface (API) and an associated graphical user interface (GUI) designed to provide a single point of access to the data. As of now, OSDR has focused on the detectors located on the ISS, with the long-term goal to establish a self-sustained portal receiving continuous updates through APIs connecting to multiple radiation databases of varying scope, as well as individual investigator contributions. The RadLab API implements a request syntax enabling users to query data by craft, sensor type, timespan, etc, allowing for arbitrary combinations of original source data, thus providing programmatic access for use in computational pipelines, while the GUI facilitates data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗