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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Camelina circRNA landscape: Implications for gene regulation and fatty acid metabolism

Abstract Circular RNAs (circRNAs) are closed‐loop RNAs forming a covalent bond between their 3′ and 5′ ends, the back splice junction (BSJ), rendering them resistant to exonucleases and thus more stable compared to linear RNAs. Identification of circRNAs and distinction from their cognate linear RNA is only possible by sequencing the BSJ that is unique to the circRNA. CircRNAs are involved in the regulation of their cognate RNAs by increasing transcription rates, RNA stability, and alternative splicing. We have identified circRNAs from C. sativa that are associated with the regulation of germination, light response, and lipid metabolism. We sequenced light‐grown and etiolated seedlings after 5 or 7 days post‐germination and identified a total of 3447 circRNAs from 2763 genes. Most circRNAs originate from a single homeolog of the three subgenomes from allohexaploid camelina and correlate with higher ratios of alternative splicing of their cognate genes. A network analysis shows the interactions of select miRNA:circRNA:mRNAs for regulation of transcript stabilities where circRNA can act as a competing endogenous RNA. Several key lipid metabolism genes can generate circRNA, and we confirmed the presence of KASII circRNA as a true circRNA. CircRNA in camelina can be a novel target for breeding and engineering efforts.

Utley, Delecia [Department of Plant and Microbial ↗
DOE OSTI2019

The Mathematical Foundations of the Science of Cities

In this chapter, we describe graph-theoretic representations of infrastructure and social processes in urban environments and trace the development of these fields from the perspective of mathematics, social science, and urban planning. We follow the historical development of two different perspectives on cities and urban planning – one in which infrastructure and urban form is the primary focus and another which made people and social processes the primary focus. These perspectives can be traced through their application of concurrently developing mathematical techniques in graph theory, network science, and social network analysis. These different perspectives are now becoming integrated into a more mathematically grounded understanding of cities as coupled social and physical systems, in which the social life of a city shapes and defines the infrastructure that is built and a city’s infrastructure and physical form also shape the lives and communities of its residents.

Brelsford, Christa↗
DOE OSTI2026

Drought shifts dissolved organic matter sources from above- to belowground and stress-induced processes in Amazon white-sand forests

White-sand forests contribute significantly to dissolved organic matter (DOM) production in the central Amazon, forming blackwater rivers that dominate organic matter export from the Amazon basin to the ocean. Despite their importance in controlling DOM export, white-sand forests are understudied, and it remains unclear whether systematic changes in the formation of blackwater DOM occur and how seasonal variations and extremes like El Niño-associated droughts impact them. We collected soil porewater from two central Amazon white-sand forests for two years, spanning a wet La Niña year followed by an El Niño drought year. The molecular composition of DOM was analyzed using high-resolution mass spectrometry, and correlation network analysis was employed to identify ecologically meaningful DOM subsets. Using additional chemical characterization, database annotations, correlation with 14C-age of DOM and climatic variables, and ecological null modeling, we propose five distinct DOM sources: plant litter and throughfall, soil organic matter (SOM) decomposition, root exudation, and two drought response subsets of likely microbial and plant origin. During drought conditions, aboveground plant-derived compounds decreased, while SOM products, root exudates, and drought response compounds increased. These drought responses were qualitatively similar in both years but notably amplified in the drier El Niño year. Drought amplified deterministic control over DOM composition, indicating that DOM reflected directed biological responses and that future droughts are likely to generate similar shifts. Overall, drought substantially altered belowground carbon cycling by shifting DOM sources and inducing stress responses, effects expected to recur and potentially intensify under future climate scenarios.

Lange, Dan F.↗
DOE OSTI2019

PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite

Tensor methods have gained increasingly attention from various applications, including machine learning, quantum chemistry, healthcare analytics, social network analysis, data mining, and signal processing, to name a few. Sparse tensors and their algorithms become critical to further improve the performance of these methods and enhance the interpretability of their output. This work presents a sparse tensor algorithm benchmark suite (PASTA) for single- and multi-core CPUs. To the best of our knowledge, this is the first benchmark suite for sparse tensor world. PASTA targets on: 1) helping application users to evaluate different computer systems using its representative computational workloads; 2) providing insights to better utilize existed computer architecture and systems and inspiration for the future design. This benchmark suite will be publicly released.

HPC, sparse tensor, benchmark↗
DOE OSTI2018

Profiling neuron-autonomous lncRNA changes upon ischemia/reperfusion injury

Highlights: • Tnxa-ps1 is up regulated after OGD/R. • Tnxa-ps1 knockdown promoted neuronal survival after OGD/R. • Tnxa-ps1 up-regulation is associated with the four mRNA changes after OGD/R. Extensive changes of neuronal transcriptome occur post ischemic stroke and during the following reperfusion. Although numerous studies focused on transcriptome changes of mRNAs associated with ischemic stroke, little is known about whether and how long non-coding RNAs (lncRNAs), which play critical roles in cellular homeostasis, are involved in this process. In this study, we performed high throughput screening to analyze expression changes of lncRNAs in primarily cultured hippocampal neurons under an oxygen-glucose deprivation/reperfusion (OGD/R) condition at 0 h, 6 h, 12 h, and 18 h, respectively. Knock down of one validated lncRNAs (Tnxa-ps1) promoted neuronal survival by inhibiting apoptosis. Coding non-coding co-expression network analysis revealed that the expression of Tnxa-ps1 was highly correlated with changes of a particular group of genes, many of which are associated with neural protection. Finally, we showed that down-regulation of Tnxa-ps1 reversed the expression changes of four mRNAs post OGD/R, revealing a regulatory effect between Tnxa-ps1 and selected genes. Together, our data revealed possible participation of lncRNAs in the pathophysiology of OGD/R and thereby provided new insights into the studies of potential therapeutic targets for ischemic stroke.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

CVID enteropathy is characterized by exceeding low mucosal IgA levels and interferon-driven inflammation possibly related to the presence of a pathobiont

Common variable immunodeficiency (CVID), the most common symptomatic primary antibody deficiency, is accompanied in some patients by a duodenal inflammation and malabsorption syndrome known as CVID enteropathy (E-CVID).The goal of this study was to investigate the immunological abnormalities in CVID patients that lead to enteropathy as well as the contribution of intestinal microbiota to this process.We found that, in contrast to noE-CVID patients (without enteropathy), E-CVID patients have exceedingly low levels of IgA in duodenal tissues. In addition, using transkingdom network analysis of the duodenal microbiome, we identified Acinetobacter baumannii as a candidate pathobiont in E-CVID. Finally, we found that E-CVID patients exhibit a pronounced activation of immune genes and down-regulation of epithelial lipid metabolism genes. We conclude that in the virtual absence of mucosal IgA, pathobionts such as A. baumannii , may induce inflammation that re-directs intestinal molecular pathways from lipid metabolism to immune processes responsible for enteropathy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Graphene oxide exposure alters gut microbial community composition and metabolism in an in vitro human model

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. Despite the increasing interest and the use of GO, assessments of its nanotoxicity have largely not interrogated its potential impact on the gut microbiome. This study addresses an important knowledge gap by investigating the impact of GO exposure- both at low (25 ppm) and high (250ppm) doses and fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial community structure and function, using an in vitro human colon bioreactor model. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 ppm GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 ppm GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 ppm GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes, suggesting that high concentrations of GO may interact with digestive enzymes to form protein coronas, causing their depletion in the gut environment. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 ppm GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism and different mechanisms are at play for low and high GO concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Effect of particle size on pore three-dimensional characteristics of SiCp preforms by X-ray micro-computed tomography

Highlights: • X-ray μ-CT was used to characterize 3D structures of the pores in SiCp preforms. • 3D pore network models of the pore structure were extracted and analyzed. • With the increase of particle size, the homogeneity of pore distribution decreased. • Small particles in large spaces of coarse particles decreased preform connectivity. - Abstract: Silicon-carbide particle (SiC{sub p}) preforms with particle sizes of 20, 50, 100 and 150 μm were prepared by compression mold forming and heat treatment. A high resolution (~ 1.0 μm) three-dimensional (3D) X-ray micro-computed tomography (X-ray μ-CT) combined with 3D pore-network models were used to study the effect of particle size on 3D characteristics and spatial structures of pores in the preforms. The results demonstrated that as the particle size increased, the gap expansion caused by burning of starch reduced. When the particle size increased from 20 to 100 μm, the average areal porosity, homogeneity of pore distribution, connectivity, the numbers of small pores and throats, and average pore coordination number decreased; the average effective sizes of pores and throats increased. When the particle size further increased to 150 μm, the large gaps were filled by small particles resulted from the broken coarse particles, which decreased the homogeneity and connectivity of pores. As a result, the pore-network analysis shows that the numbers of small pores and throats and average pore coordination number increased.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metabolic engineering of low-pH-tolerant non-model yeast, Issatchenkia orientalis , for production of citramalate

Methyl methacrylate (MMA) is an important petrochemical with many applications. However, its manufacture has a large environmental footprint. Combined biological and chemical synthesis (semisynthesis) may be a promising alternative to reduce both cost and environmental impact, but strains that can produce the MMA precursor (citramalate) at low pH are required. A non-conventional yeast, Issatchenkia orientalis, may prove ideal, as it can survive extremely low pH. Here, we demonstrate the engineering of I. orientalis for citramalate pro- duction. Using sequence similarity network analysis and subsequent DNA synthesis, we selected a more active citramalate synthase gene (cimA) variant for expression in I. orientalis. We then adapted a piggyBac transposon system for I. orientalis that allowed us to simultaneously explore the effects of different cimA gene copy numbers and integration locations. A batch fermentation showed the genome-integrated-cimA strains produced 2.0 g/L citramalate in 48 h and a yield of up to 7% mol citramalate/mol consumed glucose. These results demonstrate the potential of I. orientalis as a chassis for citramalate production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Subsurface microbial communities as a tool for characterizing regional-scale groundwater flow

Subsurface microbial community distribution patterns are influenced by biogeochemical and groundwater fluxes and may inform hydraulic connections along groundwater-flow paths. This study examined the regional-scale microbial community of the Death Valley Regional Flow System and evaluated whether subsurface communities can be used to identify groundwater-flow paths between recharge and discharge areas. Samples were collected from 36 sites in three groundwater basins: Pahute Mesa–Oasis Valley (PMOV), Ash Meadows (AM), and Alkali Flat–Furnace Creek Ranch (AFFCR). Microbial diversity within and between communities varied by location, and communities were separated into two overall groups that affiliated with the AM and PMOV/AFFCR basins. Network analysis revealed patterns between clusters of common microbes that represented groundwaters with similar geochemical conditions and largely corroborated hydraulic connections between recharge and discharge areas. Null model analyses identified deterministic and stochastic ecological processes contributing to microbial community assemblages. Most communities were more different than expected and governed by dispersal limitation, geochemical differences, or undominating processes. However, certain communities from sites located within or near the Nevada National Security Site were more similar than expected and dominated by homogeneous dispersal or selection. Overall, the (dis)similarities between the microbial communities of DVRFS recharge and discharge areas supported previously documented hydraulic connections between: (1) Spring Mountains and Ash Meadows; (2) Frenchman and Yucca Flat and Amargosa Desert; and (3) Amargosa Desert and Death Valley. However, only a portion of the flow path between Pahute Mesa and Oasis Valley could be supported by microbial community analyses, likely due to well-associated artifacts in samples from the two Oasis Valley sites. This study demonstrates the utility of combining microbial data with hydrologic, geologic, and water-chemistry information to comprehensively characterize groundwater systems, highlighting both strengths and limitations of this approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Structural Correlations and Percolation in Twisted Perylene Diimides Using a Simple Anisotropic Coarse-Grained Model

Large, twisted, and fused conjugated molecular architectures have begun to appear more prominently in the organic semiconductor literature. From a modeling perspective, such structures present a challenge to conventional simulation techniques; atomistic resolutions are computationally inefficient, while traditional isotropic coarse-grained models do not capture the inherent anisotropies of the molecules. In this work, we develop a simple coarse-grained model that explicitly incorporates the anisotropy of these molecular architectures, thereby providing a route toward analyzing pi-stacking, and thus qualitative electronic structure, at a computationally efficient coarse-grained resolution. Our simple coarse-grained model maintains relative orientations of conjugated rings, as well as inter-ring dihedrals, that are critical for understanding electronic and excitonic transport in bulk systems. We apply this model to understand structural correlations in several recently synthesized perylene diimide (PDI)-based organic semiconductors. Twisted and nonplanar molecular architectures are found to promote amorphous morphologies while maintaining local pi-stacking. In conclusion, a graph theoretical network analysis demonstrates that these twisted molecules are more likely to form percolating three-dimensional pathways for charge motion than strictly planar molecules, which show connectivity in only one dimension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Understanding Electric Double-Layer Gating Based on Ionic Liquids: from Nanoscale to Macroscale

In electric double-layer transistors (EDLTs), it is well known that the EDL formed by ionic liquids (ILs) can induce an ultrahigh carrier density at the semiconductor surface, compared to solid dielectric. However, the mechanism of device performance is still not fully understood, especially at a molecular level. In this study, we evaluate the gating performance of amorphous indium gallium zinc oxide (a-IGZO) transistor coupled with a series of imidazolium-based ILs, using an approach combining of molecular dynamics simulation and finite element modeling. Results reveal that the EDL with different ion structures could produce inhomogeneous electric fields at the solid–electrolyte interface, and the heterogeneity of electric field-induced charge distributions at semiconductor surface could reduce the electrical conductance of a-IGZO during gating process. Meanwhile, a resistance network analysis was adopted to bridge the nanoscopic data with the macroscopic transfer characteristics of IL-gated transistor, and showed that our theoretical results could well estimate the gating performance of practical devices. Finally, our findings could provide both new concepts and modeling techniques for IL-gated transistors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2017

Germline Chd8 haploinsufficiency alters brain development in mouse

The chromatin remodeling gene CHD8 represents a central node in neurodevelopmental gene networks implicated in autism. In this paper, we examined the impact of germline heterozygous frameshift Chd8 mutation on neurodevelopment in mice. Chd8 + / del5 mice displayed normal social interactions with no repetitive behaviors but exhibited cognitive impairment correlated with increased regional brain volume, validating that phenotypes of Chd8 + / del5 mice overlap pathology reported in humans with CHD8 mutations. We applied network analysis to characterize neurodevelopmental gene expression, revealing widespread transcriptional changes in Chd8 + / del5 mice across pathways disrupted in neurodevelopmental disorders, including neurogenesis, synaptic processes and neuroimmune signaling. We identified a co-expression module with peak expression in early brain development featuring dysregulation of RNA processing, chromatin remodeling and cell-cycle genes enriched for promoter binding by Chd8, and we validated increased neuronal proliferation and developmental splicing perturbation in Chd8 + / del5 mice. Finally, this integrative analysis offers an initial picture of the consequences of Chd8 haploinsufficiency for brain development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Oral microbiota of periodontal health and disease and their changes after nonsurgical periodontal therapy

This study examined the microbial diversity and community assembly of oral microbiota in periodontal health and disease and after nonsurgical periodontal treatment. The V4 region of 16S rRNA gene from DNA of 238 saliva and subgingival samples of 21 healthy and 48 diseased subjects was amplified and sequenced. Among 1979 OTUs identified, 28 were overabundant in diseased plaque. Six of these taxa were also overabundant in diseased saliva. Twelve OTUs were overabundant in healthy plaque. There was a trend for disease-associated taxa to decrease and health-associated taxa to increase after treatment with notable variations among individual sites. Network analysis revealed modularity of the microbial communities and identified several health- and disease-specific modules. Ecological drift was a major factor that governed community turnovers in both plaque and saliva. Dispersal limitation and homogeneous selection affected the community assembly in plaque, with the additional contribution of homogenizing dispersal for plaque within individuals. Homogeneous selection and dispersal limitation played important roles, respectively, in healthy saliva and diseased pre-treatment saliva between individuals. Our results revealed distinctions in both taxa and assembly processes of oral microbiota between periodontal health and disease. Furthermore, the community assembly analysis has identified potentially effective approaches for managing periodontitis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M↗
DOE OSTI2020

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems

To increase the utility of Gene Ontology (GO) annotations for interpretation of genome-wide experimental data, we have developed GO-CAM, a structured framework for linking multiple GO annotations into an integrated model of a biological system. Here, we expect that GO-CAM will enable new applications in pathway and network analysis, as well as improve standard GO annotations for traditional GO-based applications.

59 BASIC BIOLOGICAL SCIENCES↗