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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Micro-Organ Devices

Micro-organ devices (MODs) are being developed to satisfy an emerging need for small, lightweight, reproducible, biological-experimentati on apparatuses that are amenable to automated operation and that imp ose minimal demands for resources (principally, power and fluids). I n simplest terms, a MOD is a microfluidic device containing a variety of microstructures and assemblies of cells, all designed to mimic a complex in vivo microenvironment by replicating one or more in vivo micro-organ structures, the architectures and composition of the extr acellular matrices in the organs of interest, and the in vivo fluid flows. In addition to microscopic flow channels, a MOD contains one or more micro-organ wells containing cells residing in microscopic e xtracellular matrices and/or scaffolds, the shapes and compositions o f which enable replication of the corresponding in vivo cell assembl ies and flows.

Gonda, Steven R.↗
NASA NTRS1986

Cooperation of catalysts and templates

In order to understand how self-reproducing molecules could have originated on the primitive Earth or extraterrestrial bodies, it would be useful to find laboratory models of simple molecules which are able to carry out processes of catalysis and templating. Furthermore, it may be anticipated that systems in which several components are acting cooperatively to catalyze each other's synthesis will have different behavior with respect to natural selection than those of purely replicating systems. As the major focus of this work, laboratory models are devised to study the influence of short peptide catalysts on template reactions which produce oligonucleotides or additional peptides. Such catalysts could have been the earliest protoenzymes of selective advantage produced by replicating oligonucleotides. Since this is a complex problem, simpler systems are also studied which embody only one aspect at a time, such as peptide formation with and without a template, peptide catalysis of nontemplated peptide synthesis, and model reactions for replication of the type pioneered by Orgel.

White, D. H.↗
DOE OSTI2025

Asymmetric loading of TnsE regulates Tn7 targeting of DNA replication structures

Abstract Tn7 transposable elements are known for their sophisticated target-site selection mechanisms. For the prototypical Tn7 element, dedicated transposon-encoded proteins direct insertions to either a conserved site in the chromosome or replicating DNA structures in conjugal plasmids, ensuring the vertical and horizontal spread of the element. While the pathway targeting the attTn7 site in the bacterial chromosome has been extensively studied, the pathway targeting DNA replication structures remains poorly understood. We have used an integrative structural biology approach to elucidate how the Tn7-encoded protein TnsE recognizes replication sites. Using native mass spectrometry, we found that TnsE forms 1:1 and 2:1 (TnsE:DNA) complexes on 3′-recessed DNA, with gain-of-function TnsE variants favoring the formation of 2:1 complexes. Structural characterization confirms that two TnsE molecules bind to DNA with the C-terminal domain of the protein recognizing duplex DNA, leaving the N-terminal domain to impose DNA substrate specificity and recruit the core transposition machinery. Collectively, our work is consistent with a model where TnsE-mediated target-site selection relies on the formation of an asymmetric TnsE:DNA complex to recruit the Tn7 transposase to DNA replication structures.

Biochemistry & Molecular Biology↗
NASA NTRS2000

Viral carcinogenesis: revelation of molecular mechanisms and etiology of human disease

The RNA and DNA tumor viruses have made fundamental contributions to two major areas of cancer research. Viruses were vital, first, to the discovery and analysis of cellular growth control pathways and the synthesis of current concepts of cancer biology and, second, to the recognition of the etiology of some human cancers. Transforming retroviruses carry oncogenes derived from cellular genes that are involved in mitogenic signalling and growth control. DNA tumor viruses encode oncogenes of viral origin that are essential for viral replication and cell transformation; viral oncoproteins complex with cellular proteins to stimulate cell cycle progression and led to the discovery of tumor suppressors. Viral systems support the concept that cancer development occurs by the accumulation of multiple cooperating events. Viruses are now accepted as bona fide etiologic factors of human cancer; these include hepatitis B virus, Epstein-Barr virus, human papillomaviruses, human T-cell leukemia virus type I and hepatitis C virus, plus several candidate human cancer viruses. It is estimated that 15% of all human tumors worldwide are caused by viruses. The infectious nature of viruses distinguishes them from all other cancer-causing factors; tumor viruses establish long-term persistent infections in humans, with cancer an accidental side effect of viral replication strategies. Viruses are usually not complete carcinogens, and the known human cancer viruses display different roles in transformation. Many years may pass between initial infection and tumor appearance and most infected individuals do not develop cancer, although immunocompromised individuals are at elevated risk of viral-associated cancers. Variable factors that influence viral carcinogenesis are reviewed, including possible synergy between viruses and environmental cofactors. The difficulties in establishing an etiologic role for a virus in human cancer are discussed, as well as the different approaches that proved viral links to cancer. Future directions for tumor virus studies are considered.

NASA Program Biomedical Research and Countermeasur↗
DOE OSTI2026

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗
DOE OSTI2025

scRNA seq of an F1 cross of Marek’s disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators

Abstract Marek’s disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek’s disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 6 3 (L6) and susceptible Line 7 2 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.

Science & Technology - Other Topics↗
DOE OSTI2024

Analyses of GWAS signal using GRIN identify additional genes contributing to suicidal behavior

Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN’s utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

Time-temperature-stress capabilities of composite materials for advanced supersonic technology application

Advanced composites will play a key role in the development of the technology for the design and fabrication of future supersonic vehicles. However, incorporating the material into vehicle usage is contingent on accelerating the demonstration of service capacity and design technology. Because of the added material complexity and lack of extensive data, laboratory replication of the flight service will provide the most rapid method to document the airworthiness of advanced composite systems. Consequently, a laboratory program was conducted to determine the time-temperature-stress capabilities of several high temperature composites. Tests included were thermal aging, environmental aging, fatigue, creep, fracture, tensile, and real-time flight simulation exposure. The program had two phases. The first included all the material property determinations and aging and simulation exposures up through 10,000 hours. The second continued these tests up to 50,000 cumulative hours. This report presents the results of the Phase 1 baseline and 10,000-hr aging and flight simulation studies, the Phase 2 50,000-hr aging studies, and the Phase 2 flight simulation tests, some of which extended to almost 40,000 hours.

Kerr, James R.↗
NASA NTRS2002

A Good Neighborhood for Cells: Bioreactor Demonstration System (BDS-05)

Good neighborhoods help you grow. As with a city, the lives of a cell are governed by its neighborhood connections Connections that do not work are implicated in a range of diseases. One of those connections - between prostate cancer and bone cells - will be studied on STS-107 using the Bioreactor Demonstration System (BDS-05). To improve the prospects for finding novel therapies, and to identify biomarkers that predict disease progression, scientists need tissue models that behave the same as metastatic or spreading cancer. This is one of several NASA-sponsored lines of cell science research that use the microgravity environment of orbit in an attempt to grow lifelike tissue models for health research. As cells replicate, they "self associate" to form a complex matrix of collagens, proteins, fibers, and other structures. This highly evolved microenvironment tells each cell who is next door, how it should grow arid into what shapes, and how to respond to bacteria, wounds, and other stimuli. Studying these mechanisms outside the body is difficult because cells do not easily self-associate outside a natural environment. Most cell cultures produce thin, flat specimens that offer limited insight into how cells work together. Ironically, growing cell cultures in the microgravity of space produces cell assemblies that more closely resemble what is found in bodies on Earth. NASA's Bioreactor comprises a miniature life support system and a rotating vessel containing cell specimens in a nutrient medium. Orbital BDS experiments that cultured colon and prostate cancers have been highly promising.

Chung, Leland W. K.↗
NASA NTRS2017

Development of Solid-State Nanopore Technology for Life Detection

Biomarkers for life on Earth are an important starting point to guide the search for life elsewhere. However, the search for life beyond Earth should incorporate technologies capable of recognizing an array of potential biomarkers beyond what we see on Earth, in order to minimize the risk of false negatives from life detection missions. With this in mind, charged linear polymers may be a universal signature for life, due to their ability to store information while also inherently reducing the tendency of complex tertiary structure formation that significantly inhibit replication. Thus, these molecules are attractive targets for biosignature detection as potential "self-sustaining chemical signatures." Examples of charged linear polymers, or polyelectrolytes, include deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) as well as synthetic polyelectrolytes that could potentially support life, including threose nucleic acid (TNA) and other xenonucleic acids (XNAs). Nanopore analysis is a novel technology that has been developed for singlemolecule sequencing with exquisite single nucleotide resolution which is also well-suited for analysis of polyelectrolyte molecules. Nanopore analysis has the ability to detect repeating sequences of electrical charges in organic linear polymers, and it is not molecule- specific (i.e. it is not restricted to only DNA or RNA). In this sense, it is a better life detection technique than approaches that are based on specific molecules, such as the polymerase chain reaction (PCR), which requires that the molecule being detected be composed of DNA.

Bywaters, K. B.↗
NASA NTRS1980

Time-temperature-stress capabilities of composite materials for advanced supersonic technology application, phase 1

Implementation of metal and resin matrix composites into supersonic vehicle usage is contingent upon accelerating the demonstration of service capacity and design technology. Because of the added material complexity and lack of extensive service data, laboratory replication of the flight service will provide the most rapid method of documenting the airworthiness of advanced composite systems. A program in progress to determine the time temperature stress capabilities of several high temperature composite materials includes thermal aging, environmental aging, fatigue, creep, fracture, and tensile tests as well as real time flight simulation exposure. The program has two parts. The first includes all the material property determinations and aging and simulation exposures up through 10,000 hours. The second continues these tests up to 50,000 cumulative hours. Results are presented of the 10,000 hour phase, which has now been completed.

Kerr, J. R.↗
NASA NTRSDate not supplied

On the Interaction Between a Flow Instability and Inertial Particles in Supersonic Jet Plume-Surface Interaction

Extraterrestrial landings often require spacecraft to deploy supersonic jets directed at dusty planetary surfaces to ensure controlled descents. This interaction, termed plume-surface interaction (PSI), critically influences crater formation and the dynamics of ejected particles, which can obscure vision, damage onboard sensors, and impact nearby infrastructure with significant particle velocities. The physics of PSI remain poorly understood due to the complexities in simulating the involved multiphysics and experimentally replicating reduced atmospheric pressure conditions. This article discusses a collaborative effort to investigate PSI in reduced atmospheric pressure environments using a Mach 5.3 jet impinging on a granular bed. The results highlight observations of an azimuthal pattern in the ejecta distribution, characterized by alternating ejecta streaks of varying particle concentrations. This phenomenon suggests the presence of a low Reynolds number instability, a notable discovery given the supersonic nature of the jet.

PSI↗
DOE OSTI2025

Proteome-wide characterization of PTMs reveals host cell responses to viral infection and identifies putative antiviral drug targets

Post-translational modifications (PTMs) are biochemical modifications that can significantly alter protein structure, function, stability, localization, and interactions with other molecules, thereby activating or inactivating intracellular processes. A growing body of research has begun to highlight the role of PTMs, including phosphorylation, ubiquitination, acetylation, and redox modifications, during virus-host interactions. Collectively, these PTMs regulate key steps in mounting the host immune response and control critical host pathways required for productive viral replication. This has led to the conception of antiviral therapeutics that focus on controlling host protein PTMs, potentially offering pathogen-agnostic treatment options and revolutionizing our capacity to prevent virus transmission. On the other hand, viruses can hijack the host cellular PTM machinery to modify viral proteins in promoting viral replication and evading immune surveillance. PTM regulation during virus-host interactions is complex and poorly mapped, and the development of effective PTM-targeted antiviral drugs will require a more comprehensive understanding of the cellular pathways essential for virus replication. In this review, we discuss the roles of PTMs in virus infection and how technological advances in mass spectrometry-based proteomics can capture systems-level PTM changes during viral infection. Additionally, we explore how such knowledge is leveraged to identify PTM-targeted candidates for developing antiviral drugs. Looking ahead, studies focusing on the discovery and functional elucidation of PTMs, either on the host or viral proteins, will not only deepen our understanding of molecular pathology but also pave the way for developing better drugs to fight emerging viruses.

Immunology↗
NASA NTRS2013

Advanced Colloids Experiment (ACE) Science Overview

The Advanced Colloids Experiment is being conducted on the International Space Station (ISS) using the Light Microscopy Module (LMM) in the Fluids Integrated Rack (FIR). Work to date will be discussed and future plans and opportunities will be highlighted. The LMM is a microscope facility designed to allow scientists to process, manipulate, and characterize colloidal samples in micro-gravity where the absence of gravitational settling and particle jamming enables scientists to study such things as:a.The role that disordered and ordered-packing of spheres play in the phase diagram and equation of state of hard sphere systems,b.crystal nucleation and growth, growth instabilities, and the glass transition, c.gelation and phase separation of colloid polymer mixtures,d.crystallization of colloidal binary alloys,e.competition between crystallization and phase separation,f.effects of anisotropy and specific interactions on packing, aggregation, frustration and crystallization,g.effects of specific reversible and irreversible interactions mediated in the first case by hybridization of complementary DNA strands attached to separate colloidal particles,h.Lock and key interactions between colloids with dimples and spheres which match the size and shape of the dimples,i.finding the phase diagrams of isotropic and interacting particles,j.new techniques for complex self-assembly including scenarios for self-replication, k.critical Casimir forces,l.biology (real and model systems) in microgravity,m.etc. By adding additional microscopy capabilities to the existing LMM, NASA will increase the tools available for scientists that fly experiments on the ISS enabling scientists to observe directly what is happening at the particle level. Presently, theories are needed to bridge the gap between what is being observed (at a macroscopic level when photographing samples) with what is happening at a particle (or microscopic) level. What is happening at a microscopic level will be directly accessible with the availability of the Light Microscopy Module (LMM) on ISS. To meet these goals, the ACE experiment is being built-up in stages, with the availability of confocal microscopy being the ultimate objective. Supported by NASAs Physical Sciences Research Program, ESAESTEC, and the authors respective governments.

Microgravity Biology Research↗
DOE OSTI2025

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

New Results on Communication- and Memory-Aware Load Balancing Model and Algorithms

While load balancing in distributed-memory computing has been well-studied, we present an innovative approach to this problem: a unified, reduced-order model that combines three key components to describe “work” in a distributed system: computation, communication, and memory. Our model enables an optimizer to explore complex tradeoffs in task placement, such as augmented parallelism, at the expense of data replication increasing memory usage. We propose a fully distributed, heuristic-based load balancing optimization algorithm, and demonstrate that it quickly finds close-to-optimal solutions. We formalize the complex optimization problem as a mixed-integer linear program, and compare it to our strategy. Finally, we show that when applied to an electromagnetics code, our approach obtains up to 2.3x speedups for the imbalanced execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Structure analysis of the telomere resolvase from the Lyme disease spirochete Borrelia garinii reveals functional divergence of its C-terminal domain

Borrelia spirochetes are the causative agents of Lyme disease and relapsing fever, two of the most common tick-borne illnesses. A characteristic feature of these spirochetes is their highly segmented genomes which consists of a linear chromosome and a mixture of up to approximately 24 linear and circular extrachromosomal plasmids. The complexity of this genomic arrangement requires multiple strategies for efficient replication and partitioning during cell division, including the generation of hairpin ends found on linear replicons mediated by the essential enzyme ResT, a telomere resolvase. Using an integrative structural biology approach employing advanced modelling, circular dichroism, X-ray crystallography and small-angle X-ray scattering, we have generated high resolution structural data on ResT from B. garinii. Our data provides the first high-resolution structures of ResT from Borrelia spirochetes and revealed active site positioning in the catalytic domain. We also demonstrate that the C-terminal domain of ResT is required for both transesterification steps of telomere resolution, and is a requirement for DNA binding, distinguishing ResT from other telomere resolvases from phage and bacteria. These results advance our understanding of the molecular function of this essential enzyme involved in genome maintenance in Borrelia pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler [National Renewable Energy Lab. (NR↗