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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Decomposition of Nonlinear Dynamical Networks via Comparison Systems

In analysis and control of large-scale nonlinear dynamical systems, a distributed approach is often an attractive option due to its computational tractability and usually low communication requirements. Success of the distributed control design relies on the separability of the network into weakly interacting subsystems such that minimal information exchange between subsystems is sufficient to achieve satisfactory control performance. While distributed analysis and control design for dynamical network have been well studied, decomposition of nonlinear networks into weakly interacting subsystems has not received as much attention. In this article we propose a vector Lyapunov functions based approach to quantify the energy-flow in a dynamical network via a model of a comparison system. Introducing a notion of power and energy flow in a dynamical network, we use sum-of-squares programming tools to partition polynomial networks into weakly interacting subsystems. Examples are provided to illustrate the proposed method of decomposition.

Maruf, Abdullah Al↗
DOE OSTI2022

Learning Latent Interactions for Event Identification via Graph Neural Networks and PMU Data

Phasor measurement units (PMUs) are being widely installed on power systems, providing a unique opportunity to enhance wide-area situational awareness. One essential application is the use of PMU data for real-time event identification. However, how to take full advantage of all PMU data in event identification is still an open problem. Thus, we propose a novel method that performs event identification by mining interaction graphs among different PMUs. The proposed interaction graph inference method follows an entirely data-driven manner without knowing the physical topology. Moreover, unlike previous works that treat interactive learning and event identification as two different stages, our method learns interactions jointly with the identification task, thereby improving the accuracy of graph learning and ensuring seamless integration between the two stages. Moreover, to capture multi-scale event patterns, a dilated inception-based method is investigated to perform feature extraction of PMU data. To test the proposed data-driven approach, a large real-world dataset from tens of PMU sources and the corresponding event logs have been utilized in this work. We report numerical results validate that our method has higher classification accuracy compared to previous methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Glutathione transferase P1‐1 as an arsenic drug‐sequestering enzyme

Abstract Arsenic‐based compounds are paradoxically both poisons and drugs. Glutathione transferase (GSTP1‐1) is a major factor in resistance to such drugs. Here we describe using crystallography, X‐ray absorption spectroscopy, mutagenesis, mass spectrometry, and kinetic studies how GSTP1‐1 recognizes the drug phenylarsine oxide (PAO). In conditions of cellular stress where glutathione (GSH) levels are low, PAO crosslinks C47 to C101 of the opposing monomer, a distance of 19.9 Å, and causes a dramatic widening of the dimer interface by approximately 10 Å. The GSH conjugate of PAO, which forms rapidly in cancerous cells, is a potent inhibitor ( K i = 90 n M ) and binds as a di‐GSH complex in the active site forming part of a continuous network of interactions from one active site to the other. In summary, GSTP1‐1 can detoxify arsenic‐based drugs by sequestration at the active site and at the dimer interface, in situations where there is a plentiful supply of GSH, and at the reactive cysteines in conditions of low GSH.

Parker, Lorien J.↗
DOE OSTI2013

Multiphase Resistivity Model for Magnetic Nanocomposites Developed for High Frequency, High Power Transformation

New power conversion systems that offer promise to transform electricity grids into unified interactive supply networks require high-resistivity soft-magnetic materials to allow for switching of magnetic materials at frequencies approaching 100 kHz for power transformation in the megawatt range. Amorphous and nanocomposite soft-magnetic materials, which represent the state of the art in terms of high power densities and low losses at high frequencies, have resistivities that depend on the structures and spatial distributions of multiple phases in thin ribbons. We present a multiphase resistivity model applicable to nanocomposite materials by considering an equivalent circuit approach considering paths through an amorphous, crystalline, and growth inhibitor shell phase. We detail: (a) identification of amorphous, crystalline, and shell phases; (b) consideration of the role of the morphology of each phase in an equivalent circuit model for the resistance; (c) a two-band model for the Fe/Co composition dependence of the resistivity in crystalline and amorphous phases; (d) a virtual bound state model for resistivity to explain increased resistivity due to early transition-metal growth inhibitors in the shell surrounding the nanocrystalline phase; and (e) disorder effects on amorphous phase resistivity. Experimental design and results for systems of interest in high-frequency power transformation are discussed in the context of our model including: (a) techniques for measurements of cross-section and density, (b) four-point probe and surface resistivity measurements, and (c) measurements in Fe- and Co-rich systems comparing amorphous and nanocomposite materials.

DeGeorge, V↗
DOE OSTI2019

In silico identification of key genes and signaling pathways targeted by a panel of signature microRNAs in prostate cancer

Accumulating evidence have suggested that some microRNAs are aberrantly expressed in prostate cancer. In our previous work, we had identified a panel of four differentially expressed microRNAs in prostate cancer. In the present study, we have investigated common molecular targets of this panel of miRNAs (DEMs) and key hub genes that can serve as potential candidate biomarkers in the pathogenesis and progression of prostate cancer. A joint bioinformatics approach was employed to identify differentially expressed genes (DEGs) in prostate cancer. Gene enrichment analysis followed by the protein–protein interaction (PPI) network construction and selection of hub genes was further performed using String and Cytoscape, respectively. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the identified hub genes was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. In total, 496 genes were identified to be common targets of DEMs in prostate cancer and 13 key hub genes were identified from three modules of the PPI network of the DEGs. Further top five genes viz Rhoa, PI3KCA, CDC42, MAPK3, TP53 were used for Enrichment analysis which revealed their association with vital cellular and functional pathways in prostate cancer indicating their potential as candidate biomarkers in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Structural Basis of Cooperative Ligand Binding by the Glycine Riboswitch

The glycine riboswitch regulates gene expression through the cooperative recognition of its amino acid ligand by a tandem pair of aptamers. A 3.6 {angstrom} crystal structure of the tandem riboswitch from the glycine permease operon of Fusobacterium nucleatum reveals the glycine binding sites and an extensive network of interactions, largely mediated by asymmetric A-minor contacts, that serve to communicate ligand binding status between the aptamers. These interactions provide a structural basis for how the glycine riboswitch cooperatively regulates gene expression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse post-translational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated ß-cells. We observed a swift response in global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-?B signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of a complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple co-localized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

proteomics, PTM, automation, SP3, cysteine thiol o↗
DOE OSTI2021

Mitochondrial integration and ovarian cancer chemotherapy resistance

Ovarian cancer has been nicknamed the “silent killer”. Most patients with ovarian cancer are diagnosed at an advanced stage of the disease for the first time because of its insignificant early clinical symptoms. In addition to the difficulty of early screening and delay in diagnosis, the high recurrence rate and relapsed refractory status of patients with ovarian cancer are also important factors for their high mortality. Patients with recurrent ovarian cancer often use neoadjuvant chemotherapy followed by surgery as the first choice. However, this is often accompanied by chemotherapy resistance, leading to treatment failure and a mortality rate of more than 90%. In the past, it was believed that the anti-tumor effect of chemotherapeutics represented by cisplatin was entirely attributable to its irreversible damage to DNA, but current research has found that it can inhibit cell growth and cytotoxicity via nuclear and cytoplasmic coordinated integration. As an important hub and integration platform for intracellular signal communication, mitochondria are responsible for multiple key factors during tumor occurrence and development, such as metabolic reprogramming, acquisition of metastatic ability, and chemotherapy drug response. The role of mitochondria in ovarian cancer chemotherapy resistance is becoming increasingly recognized. In this review, we discuss the cellular interactive regulatory network surrounding mitochondria, elucidate the mechanisms of tumor cell survival under chemotherapy, and discuss potential means of interfering with mitochondrial function as a novel anti-cancer therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

High-Dimensional Atomistic Neural Network Potentials for Molecule–Surface Interactions: HCl Scattering from Au(111)

Ab initio molecular dynamics (AIMD) simulations of molecule–surface scattering allow first-principles characterization of the dynamics. However, the large number of density functional theory calculations along the trajectories is very costly, limiting simulations of long-time events and giving rise to poor statistics. To avoid this computational bottleneck, we report here the development of a high-dimensional molecule–surface interaction potential energy surface (PES) with movable surface atoms, using a machine learning approach. With 60 degrees of freedom, this PES allows energy transfer between the energetic impinging molecule and thermal surface atoms. Classical trajectory calculations for the scattering of DCl from Au(111) on this PES are found to agree well with AIMD simulations, with ~105-fold acceleration. Scattering of HCl from Au(111) is further investigated and compared with available experimental results.

Kolb, Brian↗
DOE OSTI2016

Crystal structure of the human sterol transporter ABCG5/ABCG8

ATP binding cassette (ABC) transporters play critical roles in maintaining sterol balance in higher eukaryotes. The ABCG5/ABCG8 heterodimer (G5G8) mediates excretion of neutral sterols in liver and intestines. Mutations disrupting G5G8 cause sitosterolaemia, a disorder characterized by sterol accumulation and premature atherosclerosis. Here we use crystallization in lipid bilayers to determine the X-ray structure of human G5G8 in a nucleotide-free state at 3.9 Å resolution, generating the first atomic model of an ABC sterol transporter. The structure reveals a new transmembrane fold that is present in a large and functionally diverse superfamily of ABC transporters. Here, the transmembrane domains are coupled to the nucleotide-binding sites by networks of interactions that differ between the active and inactive ATPases, reflecting the catalytic asymmetry of the transporter. The G5G8 structure provides a mechanistic framework for understanding sterol transport and the disruptive effects of mutations causing sitosterolaemia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Development and crystal structures of a potent second-generation dual degrader of BCL-2 and BCL-xL

Overexpression of BCL-xL and BCL-2 play key roles in tumorigenesis and cancer drug resistance. Advances in PROTAC technology facilitated recent development of the first BCL-xL/BCL-2 dual degrader, 753b, a VHL-based degrader with improved potency and reduced toxicity compared to previous small molecule inhibitors. Here, we determine crystal structures of VHL/753b/BCL-xL and VHL/753b/BCL-2 ternary complexes. The two ternary complexes exhibit markedly different architectures that are accompanied by distinct networks of interactions at the VHL/753b-linker/target interfaces. The importance of these interfacial contacts is validated via functional analysis and informed subsequent rational and structure-guided design focused on the 753b linker and BCL-2/BCL-xL warhead. This results in the design of a degrader, WH244, with enhanced potency to degrade BCL-xL/BCL-2 in cells. Using biophysical assays followed by in cell activities, we are able to explain the enhanced target degradation of BCL-xL/BCL-2 in cells. Most PROTACs are empirically designed and lack structural studies, making it challenging to understand their modes of action and specificity. Our work presents a streamlined approach that combines rational design and structure-based insights backed with cell-based studies to develop effective PROTAC-based cancer therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Interconnected nanoconfining pore networks enhance catalyst CO 2 interaction in electrified reactive capture

Systems that sequentially capture and upgrade CO 2 from air to fuels/fuel-intermediates, such as syngas and ethylene, rely on an energy-intensive CO 2 release process. Electrified reactive capture systems transform CO 2 obtained directly from carbonate capture liquid into products. Previous reactive capture systems show a decline in Faradaic efficiencies (FE) at current densities above 200 mA/cm 2 . Here we show the chemical origins of this problem, finding that prior electrocatalyst designs failed to arrest, activate, and reduce in situ-generated CO 2 (i-CO 2 ) before it traversed the catalyst layer and entered the tailgas stream. We develop a templated synthesis to define pore structures and the sites of Ni single atoms, and find that carbon-nitrogen-based nanopores are effective in accumulating i-CO 2 via short-range, non-electrostatic interactions between CO 2 molecules and the nanochannel walls. These interactions confine and enrich i-CO 2 within the pores, enhancing its binding and activation. We report as a result carbonate electrolysis at 300 mA/cm 2 with FE to CO of 50% ± 3%, and with <1% CO 2 in the tailgas outlet stream. This corresponds to a projected energy efficiency (EE) to 2:1 syngas of 46% at 300 mA/cm 2 when H 2 is added using a water electrolyzer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Single-cell stable isotope probing in microbial ecology

Abstract Environmental and host-associated microbiomes are typically diverse assemblages of organisms performing myriad activities and engaging in a network of interactions that play out in spatially structured contexts. As the sum of these activities and interactions give rise to overall microbiome function, with important consequences for environmental processes and human health, elucidating specific microbial activities within complex communities is a pressing challenge. Single-cell stable isotope probing (SC-SIP) encompasses multiple techniques that typically utilize Raman microspectroscopy or nanoscale secondary ion mass spectrometry (NanoSIMS) to enable spatially resolved tracking of isotope tracers in cells, cellular components, and metabolites. SC-SIP techniques are uniquely suited for illuminating single-cell activities in microbial communities and for testing hypotheses about cellular functions generated for example from meta-omics datasets. Here, we illustrate the insights enabled by SC-SIP techniques by reviewing selected applications in microbiology and offer a perspective on their potential for future research.

Alcolombri, Uria (ORCID:0000000335615091)↗
DOE OSTI2014

Statistical investigations on nitrogen-vacancy center creation

Quantum information technologies require networks of interacting defect bits. Color centers, especially the nitrogen vacancy (NV{sup −}) center in diamond, represent one promising avenue, toward the realisation of such devices. The most successful technique for creating NV{sup −} in diamond is ion implantation followed by annealing. Previous experiments have shown that shallow nitrogen implantation (<10 keV) results in NV{sup −} centers with a yield of 0.01%–0.1%. We investigate the influence of channeling effects during shallow implantation and statistical diffusion of vacancies using molecular dynamics and Monte Carlo simulation techniques. Energy barriers for the diffusion process were calculated using density functional theory. Our simulations show that 25% of the implanted nitrogens form a NV center, which is in good agreement with our experimental findings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Crystal structure of an orthomyxovirus matrix protein reveals mechanisms for self-polymerization and membrane association

Many enveloped viruses encode a matrix protein. In the influenza A virus, the matrix protein M1 polymerizes into a rigid protein layer underneath the viral envelope to help enforce the shape and structural integrity of intact viruses. The influenza virus M1 is also known to mediate virus budding as well as the nuclear export of the viral nucleocapsids and their subsequent packaging into nascent viral particles. Despite extensive studies on the influenza A virus M1 (FLUA-M1), only crystal structures of its N-terminal domain are available. Here we report the crystal structure of the full-length M1 from another orthomyxovirus that infects fish, the infectious salmon anemia virus (ISAV). The structure of ISAV-M1 assumes the shape of an elbow, with its N domain closely resembling that of the FLUA-M1. The C domain, which is connected to the N domain through a flexible linker, is made of four α-helices packed as a tight bundle. In the crystal, ISAV-M1 monomers form infinite 2D arrays with a network of interactions involving both the N and C domains. Results from liposome flotation assays indicated that ISAV-M1 binds membrane via electrostatic interactions that are primarily mediated by a positively charged surface loop from the N domain. Furthemore, cryoelectron tomography reconstruction of intact ISA virions identified a matrix protein layer adjacent to the inner leaflet of the viral membrane. The physical dimensions of the virion-associated matrix layer are consistent with the 2D ISAV-M1 crystal lattice, suggesting that the crystal lattice is a valid model for studying M1–M1, M1–membrane, and M1–RNP interactions in the virion.

59 BASIC BIOLOGICAL SCIENCES↗