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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simulated Microgravity Alters Gene Regulation Linked to Immunity and Cardiovascular Disease

Microgravity exposure induces a cephalad fluid shift and an overall reduction in physical activity levels which can lead to cardiovascular deconditioning in the absence of countermeasures. Future spaceflight missions will expose crew to extended periods of microgravity among other stressors, the effects of which on cardiovascular health are not fully known. In this study, we determined cardiac responses to extended microgravity exposure using the rat hindlimb unloading (HU) model. We hypothesized that exposure to prolonged simulated microgravity and subsequent recovery would lead to increased oxidative damage and altered expression of genes involved in the oxidative response. To test this hypothesis, we examined hearts of male (three and nine months of age) and female (3 months of age) Long–Evans rats that underwent HU for various durations up to 90 days and reambulated up to 90 days post-HU. Results indicate sex-dependent changes in oxidative damage marker 8-hydroxydeoxyguanosine (8-OHdG) and antioxidant gene expression in left ventricular tissue. Three-month-old females displayed elevated 8-OHdG levels after 14 days of HU while age-matched males did not. In nine-month-old males, there were no differences in 8-OHdG levels between HU and normally loaded control males at any of the timepoints tested following HU. RNAseq analysis of left ventricular tissue from nine-month-old males after 14 days of HU revealed upregulation of pathways involved in pro-inflammatory signaling, immune cell activation and differential expression of genes associated with cardiovascular disease progression. Taken together, these findings provide a rationale for targeting antioxidant and immune pathways and that sex differences should be taken into account in the development of countermeasures to maintain cardiovascular health in space.

Genetics & Heredity↗
DOE OSTI2018

Electron critical gradient scale length measurements of ICRF heated L-mode plasmas at Alcator C-Mod tokamak

A profile for the critical gradient scale length ( L c ) has been measured in L-mode discharges at the Alcator C-Mod tokamak, where electrons were heated by an ion cyclotron range of frequency through minority heating with the intention of simultaneously varying the heat flux and changing the local gradient. The electron temperature gradient scale length ( L Te -1 = |∇ T e |/ T e ) profile was measured via the B T -jog technique and it was compared with electron heat flux from power balance (TRANSP) analysis. The T e profiles were found to be very stiff and already above the critical values, however, the stiffness was found to be reduced near the q = 3/2 surface. The measured L c profile is in agreement with electron temperature gradient (ETG) models which predict the dependence of L c -1 on local , Z eff , T e /T i , and the ratio of the magnetic shear to the safety factor. The results from linear Gene gyrokinetic simulations suggest ETG to be the dominant mode of turbulence in the electron scale ( k ⊥ ρ s > 1), and ion temperature gradient/trapped electron mode modes in the ion scale ( k ⊥ ρ s > 1). Finally, the measured L c profile is in agreement with the profile of ETG critical gradients deduced from GENE simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Fabrication of DNA/Hydroxyapatite nanocomposites by simulated body fluid for gene delivery

The hydroxyapatite (HA) formation on the surface of DNA molecules in simulated body fluid (SBF) was examined. The osteoconductivity is estimated using SBF having ion concentrations approximately equal to those of human blood plasma. After immersion for 4 weeks in SBF at 36.5 °C, the HA crystallites possessing 1-14 micrometer in diameter grew on the surface of DNA molecules. The leaf flake-like and spherical shapes morphologies were observed through scanning electron microscopy analysis. Original peaks of both of DNA and HA were characterized by fourier transform infrared spectroscopy. The Ca/P ratio (1.1-1.5) in HA was estimated by energy dispersive X-ray analysis. After biomineralization, the calculated weight ratio of DNA/HA was 18/82 by thermogravimetry/differential thermal analysis. The molecular orbital computer simulation has been used to probe the interaction of DNA with two charge-balancing ions, CaOH{sup +} and CaH{sub 2}PO{sub 4}{sup +}. The adsorption enthalpy of the two ions on DNA having negative value was the evidence for the interface in mineralization of HA in SBF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

The interplay between chromosome stability and cell cycle control explored through gene–gene interaction and computational simulation

Chromosome stability models are usually qualitative models derived from molecular-genetic mechanisms for DNA repair, DNA synthesis, and cell division. While qualitative models are informative, they are also challenging to reformulate as precise quantitative models. In this report we explore how (A) laboratory experiments, (B) quantitative simulation, and (C) seriation algorithms can inform models of chromosome stability. Laboratory experiments were used to identify 19 genes that when over-expressed cause chromosome instability in the yeast Saccharomyces cerevisiae . To better understand the molecular mechanisms by which these genes act, we explored their genetic interactions with 18 deletion mutations known to cause chromosome instability. Quantitative simulations based on a mathematical model of the cell cycle were used to predict the consequences of several genetic interactions. These simulations lead us to suspect that the chromosome instability genes cause cell-cycle perturbations. Cell-cycle involvement was confirmed using a seriation algorithm, which was used to analyze the genetic interaction matrix to reveal an underlying cyclical pattern. The seriation algorithm searched over 10 14 possible arrangements of rows and columns to find one optimal arrangement, which correctly reflects events during cell cycle phases. To conclude, we illustrate how the molecular mechanisms behind these cell cycle events are consistent with established molecular interaction maps.

Biochemistry & Molecular Biology↗
NASA NTRS2007

High-LET Patterns of DSBs in DNA Loops, the HPRT Gene and Phosphorylation Foci

We present new results obtained with our model based on the track structure and chromatin geometry that predicts the DSB spatial and genomic distributions in a cell nucleus with the full genome represented. The model generates stochastic patterns of DSBs in the physical space of the nucleus filled with the realistic configuration of human chromosomes. The model was re-used to find the distribution of DSBs in a physical volume corresponding to a visible phosphorylation focus believed to be associated with a DSB. The data shows whether there must more than one DSB per foci due to finite size of the visible focus, even if a single DSB is radiochemically responsible for the phosphorylation of DNA in its vicinity. The same model can predict patterns of closely located DSBs in a given gene, or in a DNA loop, one of the large-scale chromatin structures. We demonstrated for the example of the HPRT gene, how different sorts of radiation lead to proximity effect in DSB locations, which is important for modeling gene deletions. The spectrum of intron deletions and total gene deletions was simulated for the HPRT gene. The same proximity effect of DSBs in a loop can hinder DSB restitutions, as parts of the loop between DSBs is deleted with a higher likelihood. The distributions of DSBs and deletions of DNA in a loop are presented.

Ponomarev, Artem L.↗
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↗
DOE OSTI2018

Validation of gyrokinetic simulations with measurements of electron temperature fluctuations and density-temperature phase angles on ASDEX Upgrade

Measurements of turbulent electron temperature fluctuation amplitudes, $δT_e⊥/T_e$, frequency spectra, and radial correlation lengths, $L_r(T_{e⊥}$), have been performed at ASDEX Upgrade using a newly upgraded Correlation ECE diagnostic in the range of scales $k_⊥<1.4 cm^{-1}, k_r < 3.5 cm^{-1} (k_⊥ρ_s < 0.28$ and $k_rρ_s < 0.7$). The phase angle between turbulent temperature and density fluctuations, α nT , has also been measured by using an ECE radiometer coupled to a reflectometer along the same line of sight. These quantities are used simultaneously to constrain a set of ion-scale non-linear gyrokinetic turbulence simulations of the outer core ( ρ tor = 0.75) of a low density, electron heated L-mode plasma, performed using the gyrokinetic simulation code, GENE. The ion and electron temperature gradients were scanned within uncertainties. It is found that gyrokinetic simulations are able to match simultaneously the electron and ion heat flux at this radius within the experimental uncertainties. The simulations were performed based on a reference discharge for which $δT_{e⊥}/T_e$ measurements were available, and $L_r(T_{e⊥}$) and α nT were then predicted using synthetic diagnostics prior to measurements in a repeat discharge. While temperature fluctuation amplitudes are overestimated by >50% for all simulations within the sensitivity scans performed, good quantitative agreement is found for $L_r(T_{e⊥}$) and α nT . Finally, a validation metric is used to quantify the level of agreement of individual simulations with experimental measurements, and the best agreement is found close to the experimental gradient values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2018

Gene Expression of Pathogens in Simulated Microgravity

Extended exposure to radiation and microgravity in space has been linked to astronauts developing chronic diseases upon returning to Earth. The Gram-negative pathogen Serratia marcescens has been shown to potentially cause significant infections in humans and in insect models on Earth. Our recent findings also showed that S. marcescens shows an increase in virulence after a short period of growth in the spaceflight environment, which raises initiatives to find the correlation between space environment and the increased virulence. Because we know that the health of astronauts is immunocompromised in space, it is possible that the combination of increased bacterial virulence and the weakened immune system will cause astronauts to be more susceptible to chronic diseases in extended spaceflight. With 75% of human disease genes being conserved in the fruit fly Drosophila melanogaster, these insects act as an ideal model organism to study the human immune system. The high accessibility, low cost, high rate of reproductivity, and short lifespans of D. melanogaster facilitate efficient, high-quality research that seeks to understand altered virulence of this opportunistic pathogen. In this ground-based study, we will use a rotating wall vessel apparatus to simulate microgravity and determine how pathogenicity changes by evaluating differences in gene expression for S. marcescens between bacteria grown in simulated microgravity conditions and controls. We will compare the results of our findings to gene expression patterns in actual spaceflight samples of S. marcescens grown on the ISS (International Space Station) during a recent validation mission, to see if there are common mechanisms across our simulated microgravity and actual spaceflight microgravity samples that both show increased virulence in the fruit fly. With extended space travel in the foreseeable future, understanding how human physiology will be affected by these different factors will help mitigate risks and deaths.

spaceflight analogue↗
DOE OSTI2020

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

we report a multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

A multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computationally expensive. This work proposes a context-aware multi-fidelity Monte Carlo method that optimally balances the costs of training low-fidelity models with the costs of Monte Carlo sampling. It generalizes the previously developed context-aware bi-fidelity Monte Carlo method to hierarchies of multiple models and to more general types of low-fidelity models. When training low-fidelity models, the proposed approach takes into account the context in which the learned low-fidelity models will be used, namely for variance reduction in Monte Carlo estimation, which allows it to find optimal trade-offs between training and sampling to minimize upper bounds of the mean-squared errors of the estimators for given computational budgets. This is in stark contrast to traditional surrogate modeling and model reduction techniques that construct low-fidelity models with the primary goal of approximating well the high-fidelity model outputs and typically ignore the context in which the learned models will be used in upstream tasks. Further, the proposed context-aware multi-fidelity Monte Carlo method applies to hierarchies of a wide range of types of low-fidelity models such as sparse-grid and deep-network models. Numerical experiments with the gyrokinetic simulation code Gene show speedups of up to two orders of magnitude compared to standard estimators when quantifying uncertainties in small-scale fluctuations in confined plasma in fusion reactors. This corresponds to a runtime reduction from 72 days to four hours on one node of the Lonestar6 supercomputer at the Texas Advanced Computing Center.

42 ENGINEERING↗
DOE OSTI2014

Genome-Based Metabolic Mapping and 13 C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides

We report that integrated and genome-based flux balance analysis, metabolomics, and 13 C-label profiling of phototrophic and heterotrophic metabolism in Chlorella protothecoides, an oleaginous green alga for biofuel. The green alga Chlorella protothecoides, capable of autotrophic and heterotrophic growth with rapid lipid synthesis, is a promising candidate for biofuel production. Based on the newly available genome knowledge of the alga, we reconstructed the compartmentalized metabolic network consisting of 272 metabolic reactions, 270 enzymes, and 461 encoding genes and simulated the growth in different cultivation conditions with flux balance analysis. Phenotype-phase plane analysis shows conditions achieving theoretical maximum of the biomass and corresponding fatty acid-producing rate for phototrophic cells (the ratio of photon uptake rate to CO 2 uptake rate equals 8.4) and heterotrophic ones (the glucose uptake rate to O 2 consumption rate reaches 2.4), respectively. Isotope-assisted liquid chromatography-mass spectrometry/mass spectrometry reveals higher metabolite concentrations in the glycolytic pathway and the tricarboxylic acid cycle in heterotrophic cells compared with autotrophic cells. We also observed enhanced levels of ATP, nicotinamide adenine dinucleotide (phosphate), reduced, acetyl-Coenzyme A, and malonyl-Coenzyme A in heterotrophic cells consistently, consistent with a strong activity of lipid synthesis. To profile the flux map in experimental conditions, we applied nonstationary 13 C metabolic flux analysis as a complementing strategy to flux balance analysis. We found that the result reveals negligible photorespiratory fluxes and a metabolically low active tricarboxylic acid cycle in phototrophic C. protothecoides. In comparison, high throughput of amphibolic reactions and the tricarboxylic acid cycle with no glyoxylate shunt activities were measured for heterotrophic cells. Lastly, taken together, the metabolic network modeling assisted by experimental metabolomics and 13 C labeling better our understanding on global metabolism of oleaginous alga, paving the way to the systematic engineering of the microalga for biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2019

Koopman Operators for Generalized Persistence of Excitation Conditions for Nonlinear Systems

It is hard to identify nonlinear biological models strictly from data, with results that are often sensitive to experimental conditions. Automated experimental workflows and liquid handling enables unprecedented throughput, as well as the capacity to generate extremely large datasets. We seek to develop generalized identifiability conditions for informing the design of automated experiments to discover predictive nonlinear biological models. For linear systems, identifiability is characterized by persistence of excitation conditions. For nonlinear systems, no such persistence of excitation conditions exist. We use the input-Koopman operator method to model nonlinear systems and derive identifiability conditions for openloop systems initialized from a single initial condition. We show that nonlinear identifiability is intrinsically tied to the rank of a given dataset’s power spectral density, transformed through the lifted Koopman observable space. We illustrate these identifiability conditions with a simulated synthetic gene circuit model, the repressilator. We illustrate how rank degeneracy in datasets results in overfitted nonlinear models of the repressilator, resulting in poor predictive accuracy. Our findings provide novel experimental design criteria for discovery of globally predictive nonlinear models of biological phenomena.

Boddupalli, Nibodh↗
NASA NTRS2014

MicroRNA Expression Profiles in Cultured Human Fibroblasts in Space

Microgravity, or an altered gravity environment from the static 1g, has been shown to influence global gene expression patterns and protein levels in living organisms. However, it is unclear how these changes in gene and protein expressions are related to each other or are related to other factors regulating such changes. A different class of RNA, the small non-coding microRNA (miRNA), can have a broad effect on gene expression networks by mainly inhibiting the translation process. Previously, we investigated changes in the expression of miRNA and related genes under simulated microgravity conditions on the ground using the NASA invented bioreactor. In comparison to static 1 g, simulated microgravity altered a number of miRNAs in human lymphoblastoid cells. Pathway analysis with the altered miRNAs and RNA expressions revealed differential involvement of cell communication and catalytic activity, as well as immune response signaling and NGF activation of NF-kB pathways under simulated microgravity condition. The network analysis also identified several projected networks with c- Rel, ETS1 and Ubiquitin C as key factors. In a flight experiment on the International Space Station (ISS), we will investigate the effects of actual spaceflight on miRNA expressions in nondividing human fibroblast cells in mostly G1 phase of the cell cycle. A fibroblast is a type of cell that synthesizes the extracellular matrix and collagen, the structural framework for tissues, and plays a critical role in wound healing and other functions. In addition to miRNA expressions, we will investigate the effects of spaceflight on the cellular response to DNA damages from bleomycin treatment.

Wu, Honglu↗
NASA NTRS2003

Effect Of Simulated Microgravity On Activated T Cell Gene Transcription

Studies of T lymphocytes under the shear stress environment of clinorotation have demonstrated an inhibition of activation in response to TCR mediated signaling. These results mimic those observed during space flight. This work investigates the molecular signaling events of T lymphocyte activation with clinorotation. Purified human T lymphocytes and the T cell clone Jurkat exhibit an uncoupling of signaling as mediated through the TCR. Activation of the transcription factor AP-1 is inhibited while activation of NFAT occurs. NFAT dephosphorylation and activation is dependent on sustained Ca(++) influx. Alternatively, AP-1, which consists of two transcription factors, jun and fos, is activated by PKC and Ras mediated pathways. TCR signaling is known to be dependent on cytoskeletal rearrangements, in particular, raft aggregation is critical. Raft aggregation, as mediated through GM, crosslinking, overcomes the inhibition of T lymphocyte activation with clinorotation, indicating that the block is occurring upstream of raft aggregation. Clinorotation is shown to have an effect similar to a weak TCR signal.

Morrow, Maureen A.↗
NASA NTRS2014

Does Simulated Weightlessness Alter the Methylation Status of Gene Promoters During Bone Remodeling?

The skeleton interacts with its environment in a way that resembles a mechanostat - through a controlled process of bone remodeling, namely local formation and resorption, to maintain a healthy structure. During weightlessness, astronauts lose structure in weight-bearing bones due to decreased formation by osteoblasts and increased resorption by osteoclasts. In contrast, increased mechanical loading through exercise targets bone remodeling to remove and repair microdamage, improving structural integrity. In fact, recent advances in astronaut exercise regimens have prevented the deleterious changes in skeletal structure during spaceflight. However, knowledge of the molecular underpinnings of the skeletal response to spaceflight and to mechanical stimulation is limited. We propose that epigenetic modification, specifically DNA methylation, may influence osteoblast differentiation and activity during spaceflight and exercise. We hypothesize that simulated weightlessness hypermethylates pro-osteoblastogenic gene promoters and decreases expression of osteoblastogenic genes. Oppositely, we hypothesize that mechanical loading hypomethylates pro-osteoblastogenic gene promoters and increases expression of osteoblastogenic genes.

Stevick, Rebecca J.↗
DOE OSTI2021

Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model

Abstract Motivation The classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis. Results In this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗