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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Knowledge Network Embedding of Transcriptomic Data From Spaceflown Mice Uncovers Signs and Symptoms Associated With Terrestrial Diseases

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, SPOKE, a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab transcriptomic data from six studies. This integration identified critical symptoms and physiological changes incurred during spaceflight.

spaceflight↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2022

A framework to implement human reliability analysis during early design stages of advanced reactors

Nuclear power plants require human actions throughout their lifecycle from design, construction, operation, and decommissioning. However, for advanced reactors (e.g., Generation IV), the reliance on human intervention in safety-related actions is expected to be reduced or completely replaced by automated actions. The Probabilistic Risk Assessment (PRA) Standard for Advanced Non-LWR Nuclear Power Plants requires that the impacts of all operator actions are captured and incorporated in the risk of the modeled plant. Moreover, the Modernization of Technical Requirements for Licensing Advanced Reactors requires human reliability analysis (HRA) to be included throughout all design and PRA development stages. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in later design stages, though it may be adequate in capturing pre-, at-, and post-initiators comes short of informing the design itself in the iterative design lifecycle. Hence, this paper presents a framework to include HRA during the design's early stages, pre-conceptual or conceptual. The proposed framework provides a process for the removal of operator actions that do not contribute to the risk and the identification of all key operator actions that are critical to the safety of the design. The results of this framework are then used to inform the design of those safety-related operator actions to update the design further. Then, using information from the updated design, this framework can be reapplied to investigate the impact of the design update on human reliability. The PRA model of the X-energy's pre-conceptual Xe-100 high-temperature gas-cooled pebble-bed reactor (HTGR-PB) design is used to demonstrate the approach. In the pre-conceptual Xe-100 PRA model, also called Phase 0 PRA model, human actions were considered an integral part of analyzing the plant response to different initiating events. Hence, in this paper, all possible human actions in the Xe-100 PRA model are identified, analyzed, and removed to emulate a design relying only on the available automated control systems. The preliminary results of this assessment show how safe the Xe-100 design is even without crediting any human actions. The results also list necessary sequences in which operator actions are critical to the risk profile of the design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2020

Pattern Identification - A Foundation for Research in the Emphasis of Design Patterns in Systems Engineering and Knowledge Capture

Pattern Language describes the morphology and functionality of a system in the absence of design particulars. Harnessing this capability will provide the Systems Engineering discipline a means of managing the development of increasingly complex systems with increasingly distributed design teams while capturing and retaining knowledge for future generations. Pattern Language is a syntax for describing, and structurally relating, design patterns. Design patterns contextually describe the application of domain knowledge in the engineered solution to the force balance problem. The parallels between pattern recognition and application, as a fundamental stage of human learning, and pattern observation within a complex system, suggests pattern language may be a valuable tool in the capture and dissemination of knowledge. Pattern application has enjoyed considerable study over the last several decades, however much of this work has focused on the replication of design particulars. This work returns to the roots of Pattern Language and explores the utility of patterns as an architectural description and guide, and knowledge capture method, for complex system development beginning with the identification of a time proven design pattern.

Russell, Samuel P.↗
DOE OSTI2022

Burden of bacterial bloodstream infections and recent advances for diagnosis

Abstract Bloodstream infections (BSIs) and subsequent organ dysfunction (sepsis and septic shock) are conditions that rank among the top reasons for human mortality and have a great impact on healthcare systems. Their treatment mainly relies on the administration of broad-spectrum antimicrobials since the standard blood culture-based diagnostic methods remain time-consuming for the pathogen's identification. Consequently, the routine use of these antibiotics may lead to downstream antimicrobial resistance and failure in treatment outcomes. Recently, significant advances have been made in improving several methodologies for the identification of pathogens directly in whole blood especially regarding specificity and time to detection. Nevertheless, for the widespread implementation of these novel methods in healthcare facilities, further improvements are still needed concerning the sensitivity and cost-effectiveness to allow a faster and more appropriate antimicrobial therapy. This review is focused on the problem of BSIs and sepsis addressing several aspects like their origin, challenges, and causative agents. Also, it highlights current and emerging diagnostics technologies, discussing their strengths and weaknesses.

Costa, Susana P.↗
NASA NTRS1982

Structural assembly demonstration experiment

The experiment is of an operational variety, designed to assess crew capability in Large Space System (LSS) assembly. The six Structural Assembly Demonstration Experiment objectives include: (1) the establishment of a quantitative correlation between LSS neutral buoyancy simulation and on-orbit assembly operations in order to enhance the validity of those assembly simulations; (2) the quantitative study of the capabilities and mechanics of human assembly in an Extravehicular Activity environment; (3) the further corroboration of the LSS Assembly Analysis cost algorithm through the obtainment of hard data base information; (4) the verification of LSS assembly techniques and timeless, as well as the identification of crew imposed loads and assembly aid requirements and concepts; (5) verification of a Launch/Assembly Platform structure concept for other LSS missions; and (6) lastly, to advance thermal control concepts through a flexible heat pipe.

Stokes, J. W.↗
NASA NTRS1988

Gravitational independence of single-breath washout tests in recumbent dogs

The effect of gravitational orientation in the mechanism of lung filling and emptying in dogs was examined by conducting simultaneously Ar-bolus and N2 single-breath washout tests (SBWTs) in 10 anesthetized dogs (prone and supine), with three of the dogs subjected to body rotation. Transpulmonary pressure was measured simultaneously, allowing identification of the lung volume above residual volume at which there was an inflection point in the pressure-volume curve. Combined resident gas and bolus SBWTs in recumbent dogs were found to be different from such tests in humans; in dogs, the regional distribution of ventilation was not primarily determined by gravity. The measurements did not make it possible to discern exact mechanisms of filling and emptying, but both processes appear to be related to lung, thorax, and mediastinum interactions and/or differences in regional mechanical properties of the lungs.

Tomioka, Shinichi↗
NASA NTRS2017

Effects of Eye Measures on Human Controller Remnant and Control Behavior

The aim of the current research was to investigate the possible relation between changes in eye activity parameters, variations in human remnant at the perceptual level and changes in human operator model parameters. Fourteen subjects performed a pitch tracking task, in which the display brightness was varied by changing the background color around a simplified primary flight display, in order to create a controlled, quasilinear change in the pupil diameter through the pupillary light reflex. Pupil diameter, blink, eye opening, and opening and closing amplitudes and speeds were recorded using an eye tracker. Participants controlled single integrator-like and double integrator-like dynamics. The variation in pupil diameter did not introduce significant differences in neither remnant characteristics nor the human operator model parameters. An interesting effect occurred in the human controller’s time delay for the single integrator task, where the time delay was significantly higher for the darkest brightness compared to the other levels of brightness. This effect was not observed for the double integrator dynamics. Data suggested that the more difficult controlled dynamics induced a squinting effect, visible in smaller eye opening, and smaller eye opening and closing amplitudes. These results suggest that performance, and control behavior are invariant to the display brightness. Moreover, monitoring changes in the eye activity could represent a method of predicting variations in human remnant characteristics and human controller model parameters, introduced by task difficulty.

Eye tracking↗
DOE OSTI2024

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders. Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial. Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Exobiological exploration of Mars

Of all the other planets in the solar system, Mars remains the most promising for further elucidating concepts about chemical evolution and the origin of life. Strategies were developed to pursue three exobiological objectives for Mars exploration: determining the abundance and distribution of the biogenic elements and organic compounds, detecting evidence of an ancient biota on Mars, and determining whether indigenous organisms exist anywhere on the planet. The three strategies are quite similar and, in fact, share the same sequence of phases. In the first phase, each requires global reconnaissance and remote sensing by orbiters to select sites of interest for detailed in situ analyses. In the second phase, lander missions are conducted to characterize the chemical and physical properties of the selected sites. The third phase involves conducting 'critical' experiments at sites whose properties make them particularly attractive for exobiology. These critical experiments would include, for example, identification of organics, detection of fossils, and detection of extant life. The fourth phase is the detailed analysis of samples returned from these sites in Earth-based laboratories to confirm and extend previous discoveries. Finally, in the fifth phase, human exploration is needed to establish the geological settings for the earlier findings or to discover and explore sites that are not accessible to robotic spacecraft.

Klein, H. P.↗
NASA NTRS1994

Exobiological Exploration of Mars

Of all the other planets in the solar system, Mars remains the most promising for studying concepts about chemical evolution and the origin of life. Strategies were developed to pursue three exobiological objectives for Mars: determine abundance and distribution of biogenic elements and organic compounds, detect evidence of an ancient biota, and determine if organisms exist anywhere on the planet. The three strategies share the same sequence of phases. In the first phase, each requires global reconnaissance and remote sensing by orbiters to select sites of interest for detailed in situ analyses. In the second phase, lander missions are conducted to characterize the chemical and physical properties of the selected sites. The third phase involves conducting "critical" experiments at sites whose properties make them particularly attractive for exobiology. These critical experiments would include, for example, identification of organics, detection of fossils, and detection of extant life. The fourth phase is the detailed analysis of samples returned from these sites in Earth-based laboratories to confirm and extend previous discoveries. Finally, in the fifth phase, human exploration is needed to establish the geological context or to discover and explore sites that are not accessible to robotic spacecraft.

DeVincenzi, Donald L.↗
NASA NTRS1996

Exercise as a countermeasure for physiological adaptation to prolonged spaceflight

Exercise represents the primary countermeasure used during spaceflight to maintain or restore maximal aerobic capacity (VO2max), musculoskeletal structure, and orthostatic function. However, no single exercise or combination of prescriptions has proven entirely effective in restoring cardiovascular and musculoskeletal functions to preflight levels following prolonged spaceflight. As human spaceflight exposures increase in duration, assessment and development of various effective exercise-based protective procedures become paramount. This must involve improvement in specific countermeasure prescription as well as development of additional approaches that will allow space travelers greater flexibility and medical safety during long flights. Effective exercise prescription will be based on identification of basic physiological stimuli that maintain normal function in terrestrial gravity and understanding of how specific combinations of exercise characteristics e.g., duration, frequency, intensity, mode) can mimic these stimuli and affect the overall process of adaptation to microgravity. This can be accomplished only with greater emphasis of research on ground-based experiments. Future attention must be directed to improving exercise compliance while minimizing both crew time and the impact of the exercise on life-support resources.

Skylab Project↗
DOE OSTI2022

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

An expanded registry of candidate cis -regulatory elements

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, the ENCODE consortium mapped biochemical signals across hundreds of cell types and tissues and integrated these data to develop a registry containing 0.9 million human and 300,000 mouse candidate cis-regulatory elements (cCREs) annotated with potential functions. Here we have expanded the registry to include 2.37 million human and 967,000 mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays such as STARR-seq, massively parallel reporter assay, CRISPR perturbation and transgenic mouse assays have profiled more than 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer and silencer roles in different cellular contexts. Integrating the registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by the identification of KLF1 as a novel causal gene for red blood cell traits. This expanded registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

Moore, Jill E. [Univ. of Massachusetts, Worchester↗
DOE OSTI2022

Identifying Transient Candidates in the Dark Energy Survey Using Convolutional Neural Networks

The ability to discover new transient candidates via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine learning techniques such as Convolutional Neural Networks (CNNs) have shown remarkable success. In this work, we present the results of an automated transient candidate identification on images with CNNs for an extant data set from the Dark Energy Survey Supernova program, whose main focus was on using Type Ia supernovae for cosmology. By performing an architecture search of CNNs, we identify networks that efficiently select non-artifacts (e.g., supernovae, variable stars, AGN, etc.) from artifacts (image defects, mis-subtractions, etc.), achieving the efficiency of previous work performed with random Forests, without the need to expend any effort in feature identification. The CNNs also help us identify a subset of mislabeled images. Performing a relabeling of the images in this subset, the resulting classification with CNNs is significantly better than previous results, lowering the false positive rate by 27% at a fixed missed detection rate of 0.05.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

High LET Radiation Can Enhance TGF(Beta) Induced EMT and Cross-Talk with ATM Pathways

The TGF(Beta) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation in mammary epithelial cells. We investigated possible interactions between the TGF(Beta) and ATM pathways following simulated space radiation using hTERT immortalized human esophageal epithelial cells (EPC-hTERT), mink lung epithelial cells (Mv1lu), and several human fibroblast cell lines. TGF(Beta) is a key modulator of the Epithelial-Mesenchymal Transition (EMT), important in cancer progression and metastasis. The implication of EMT by radiation also has several lines of developing evidence, however is poorly understood. The identification of TGF(Beta) induced EMT can be shown in changes to morphology, related gene over expression or down regulation, which can be detected by RT-PCR, and immunostaining and western blotting. In this study, we have observed morphologic and molecular alternations consistent with EMT after Mv1lu cells were treated with TGF(Beta) High LET radiation enhanced TGF(Beta) mediated EMT with a dose as low as 0.1Gy. In order to consider the TGF(Beta) interaction with ATM we used a potent ATM inhibitor Ku55933 and investigated gene expression changes and Smad signaling kinetics. Ku559933 was observed to reverse TGF(Beta) induced EMT, while this was not observed in dual treated cells (radiation+TGF(Beta)). In EPC-hTERT cells, TGF(Beta) alone was not able to induce EMT after 3 days of application. A combined treatment with high LET, however, significantly caused the alteration of EMT markers. To study the function of p53 in the process of EMT, we knocked down P53 through RNA interference. Morphology changes associated with EMT were observed in epithelial cells with silenced p53. Our study indicates: high LET radiation can enhance TGF(Beta) induced EMT; while ATM is triggering the process of TGF(Beta)-induced EMT, p53 might be an essential repressor for EMT phenotypes.

Wang, Minli↗
DOE OSTI2026

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗