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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multimodal freezing model

Sea spray aerosol (SSA) is a widely recognized important source of ice-nucleating particles (INPs) in the atmosphere. However, composition-specific identification, nucleation processes, and ice nucleation rates of SSA-INPs have not been well constrained. Microspectroscopic characterization of ambient and laboratory-generated SSA confirms that water-borne exudates from planktonic microorganisms composed of a mixture of proteinaceous and polysaccharidic compounds act as ice-nucleating agents (INAs). These data and data from previously published mesocosm and wave channel studies are subsequently used to further develop the stochastic freezing model (SFM) producing ice nucleation rate coefficients for SSA-INPs. The SFM simultaneously predicts immersion freezing and deposition and homogeneous ice nucleation by SSA particles under tropospheric conditions. Predicted INP concentrations agree with ambient and laboratory measurements. In addition, this holistic freezing model is independent of the source and exact composition of the SSA particles, making it well suited for implementation in cloud and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Beyond low lignin: Identifying the primary barrier to plant biomass conversion by fermentative bacteria

Renewable alternatives for nonelectrifiable fossil-derived chemicals are needed and plant matter, the most abundant biomass on Earth, provide an ideal feedstock. However, the heterogeneous polymeric composition of lignocellulose makes conversion difficult. Lignin presents a formidable barrier to fermentation of nonpretreated biomass. Extensive chemical and enzymatic treatments can liberate fermentable carbohydrates from plant biomass, but microbial routes offer many advantages, including concomitant conversion to industrial chemicals. Here, testing of lignin content of nonpretreated biomass using the cellulolytic thermophilic bacterium,Anaerocellum bescii, revealed that the primary microbial degradation barrier relates to methoxy substitutions in lignin. This contrasts with optimal lignin composition for chemical pretreatment that favors high S/G ratio and low H lignin. Genetically modified poplar trees with diverse lignin compositions confirm these findings. In addition, poplar trees with low methoxy content achieve industrially relevant levels of microbial solubilization without any pretreatments and with no impact on tree fitness in greenhouse.

Science & Technology - Other Topics↗
DOE OSTI2025

Identifying a next-generation antimalarial trioxolane in a landscape of artemisinin partial resistance

For over two decades, artemisinin-based combination therapy (ACT) has been the standard of care for the treatment of uncomplicated falciparum malaria. However, artemisinin partial resistance (ART-R) is now prevalent in Southeast Asia and has emerged in eastern Africa, threatening ACT efficacy. Artefenomel, a synthetic 1,2,4-trioxolane, exhibits an extended pharmacokinetic exposure profile that predicts for efficacy against ART-R parasites. Unfortunately, the development of artefenomel was halted recently after almost a decade in the clinic. Here, we describe studies of an artefenomel-adjacent chemotype that combines potent in vitro activity against clinical ART-R parasites, an extended pharmacokinetic profile with single-exposure efficacy in a murine malaria model, and enhanced stability in human microsomes and hepatocytes. Overall, our studies reveal a heretofore underexplored trioxolane chemotype with the potential to address ART-R in a next-generation trioxolane development candidate.

Science & Technology - Other Topics↗
DOE OSTI2019

Dual gene expression analysis identifies factors associated with Staphylococcus aureus virulence in diabetic mice

Staphylococcus aureus is a major human pathogen of the skin. The global burden of diabetes is high, with S. aureus a major complication of diabetic wound infections. We investigated how the diabetic environment influences S. aureus skin infection and observed an increased susceptibility to infection in mouse models of both type I and type II diabetes. A dual gene expression approach was taken to investigate transcriptional alterations in both the host and bacterium after infection. While analysis of the host response revealed only minor changes between infected control and diabetic mice, we observed that S. aureus isolated from diabetic mice had significant increases in genes associated with translation, posttranslational modification and chaperones, and reductions in genes associated with amino acid transport and metabolism. One family of genes upregulated in S. aureus isolated from diabetic lesions encoded the Clp proteases associated with the misfolded protein response. The Clp proteases were found to be partially glucose regulated as well as influencing the hemolytic activity of S. aureus . Strains lacking the Clp proteases, ClpX, ClpC and ClpP were significantly attenuated in our animal model of skin infection, with significant reductions observed in dermonecrosis and bacterial burden. In particular, mutations in clpP and clpX were significantly attenuated and remained attenuation in both normal and diabetic mice. As a result, our data suggests that the diabetic environment also causes changes to occur in invading pathogens and one of these virulence determinants is the Clp protease system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

RNA Sequencing Identifies New RNase III Cleavage Sites in Escherichia coli and Reveals Increased Regulation of mRNA

ABSTRACT Ribonucleases facilitate rapid turnover of RNA, providing cells with another mechanism to adjust transcript and protein levels in response to environmental conditions. While many examples have been documented, a comprehensive list of RNase targets is not available. To address this knowledge gap, we compared levels of RNA sequencing coverage of Escherichia coli and a corresponding RNase III mutant to expand the list of known RNase III targets. RNase III is a widespread endoribonuclease that binds and cleaves double-stranded RNA in many critical transcripts. RNase III cleavage at novel sites found in aceEF , proP , tnaC , dctA , pheM , sdhC , yhhQ , glpT , aceK , and gluQ accelerated RNA decay, consistent with previously described targets wherein RNase III cleavage initiates rapid degradation of secondary messages by other RNases. In contrast, cleavage at three novel sites in the ahpF , pflB , and yajQ transcripts led to stabilized secondary transcripts. Two other novel sites in hisL and pheM overlapped with transcriptional attenuators that likely serve to ensure turnover of these highly structured RNAs. Many of the new RNase III target sites are located on transcripts encoding metabolic enzymes. For instance, two novel RNase III sites are located within transcripts encoding enzymes near a key metabolic node connecting glycolysis and the tricarboxylic acid (TCA) cycle. Pyruvate dehydrogenase activity was increased in an rnc deletion mutant compared to the wild-type (WT) strain in early stationary phase, confirming the novel link between RNA turnover and regulation of pathway activity. Identification of these novel sites suggests that mRNA turnover may be an underappreciated mode of regulating metabolism. IMPORTANCE The concerted action and overlapping functions of endoribonucleases, exoribonucleases, and RNA processing enzymes complicate the study of global RNA turnover and recycling of specific transcripts. More information about RNase specificity and activity is needed to make predictions of transcript half-life and to design synthetic transcripts with optimal stability. RNase III does not have a conserved target sequence but instead recognizes RNA secondary structure. Prior to this study, only a few RNase III target sites in E. coli were known, so we used RNA sequencing to provide a more comprehensive list of cleavage sites and to examine the impact of RNase III on transcript degradation. With this added information on how RNase III participates in transcript regulation and recycling, a more complete picture of RNA turnover can be developed for E. coli . Similar approaches could be used to augment our understanding of RNA turnover in other bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Using DNA affinity purification sequencing (DAP-seq) to identify in vitro binding sites of potential Novosphingobium aromaticivorans DSM12444 transcription factors

Genome-wide binding sites of 44 putative transcription factors (TFs) from Novosphingobium aromaticivorans DSM12444 were analyzed using DNA affinity purification sequencing. We report that 32 of these TFs have at least one area of enrichment. These data will help better understand aromatic metabolism and other features of N. aromaticivorans biology.

DAP-seq↗
DOE OSTI2024

MVP: a modular viromics pipeline to identify, filter, cluster, annotate, and bin viruses from metagenomes

While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A High-Throughput Method for Identifying Novel Genes That Influence Metabolic Pathways Reveals New Iron and Heme Regulation in Pseudomonas aeruginosa

The ability to simultaneously and more directly correlate genes with metabolite levels on a global level would provide novel information for many biological platforms yet has thus far been challenging. Here, we describe a method to help address this problem, which we dub “Met-Seq” ( met abolite-coupled Tn seq uencing).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Identifying Rare Earth Elements and Thorium and Uranium in Iron Oxide–Apatite Deposit of Gazestan Bafgh, Southeast of Iran

The Gazestan magnetite-apatite deposit is one of Kiruna-type deposits located 78 km from Bafgh in the province of Yazd, in the Bafgh Posht-e-Badam district, southeast of Iran. In the mining region of Bafgh, volcanic rocks and Precambrian volcano-sedimentary are the main host of iron-apatite deposits. Iron deposits are essentially located in Bafgh region inside the green acidic metamorphic rocks. Volcanic rocks are basically rhyolite and rhyodacitic and the sedimentary units are mostly made of dolomite. Rock units of the region belong to the Rizzo series. The Bafgh apatite compounds are fluoride-type and seen in the monazite mineral. The similarity of the rare earth elements pattern in all samples indicates the magma source. The most amount of rare earth elements in the Gazestan deposit include 7766.25 ppm and the most amount of Th is equal to 65.1 ppm and U is equal to 8.33 ppm. The most amount of P2O5 s equal to 26.5 wt% and Fe is equal to 61.3 wt%. Also, it can be concluded that due to their high correlation with rare earth elements, the deposit is of Uranium Thorium-bearing type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

The possibility of identifying the spatial location of single dislocations by topo-tomography on laboratory setups

The spatial arrangement of single linear defects in a Si single crystal (input surface (111)) has been investigated by X-ray topo-tomography using laboratory X-ray sources. The experimental technique and the procedure of reconstructing a 3D image of dislocation half-loops near the Si crystal surface are described. The sizes of observed linear defects with a spatial resolution of about 10 μm are estimated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Breaking of axial symmetry in excited heavy nuclei as identified in giant dipole resonance data

Here, a recent theoretical prediction of a breaking of axial symmetry in quasi all heavy nuclei is confronted to a new critical analysis of photon strength functions of nuclei in the valley of stability. For the photon strength in the isovector giant dipole resonance (IVGDR) regime a parameterization of GDR shapes by the sum of three Lorentzians (TLO) is extrapolated to energies below and above the IVGDR. The impact of non-GDR modes adding to the low energy slope of photon strength is discussed including recent data on photon scattering and other radiative processes. These are shown to be concentrated in energy regions where various model calculations predict intermediate collective strength; thus they are obviously separate from the IVGDR tail. The triple Lorentzian (TLO) ansatz for giant dipole resonances is normalized in accordance to the dipole sum rule. The nuclear droplet model with surface dissipation accounts well for positions and widths without local, nuclide specific, parameters. Very few and only global parameters are needed when a breaking of axial symmetry already in the valley of stability is admitted and hence a reliable prediction for electric dipole strength functions also outside of it is expected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Insight into particle production mechanisms via angular correlations of identified particles in pp collisions at $\sqrt{\mathrm{s}}=7$ TeV

We measured two-particle angular correlations in pp collisions at √s=7 TeV for pions, kaons, protons, and lambdas, for all particle/anti-particle combinations in the pair. Data for mesons exhibit an expected peak dominated by effects associated with mini-jets and are well reproduced by general purpose Monte Carlo generators. However, for baryon–baryon and anti-baryon–anti-baryon pairs, where both particles have the same baryon number, a near-side anti-correlation structure is observed instead of a peak. This effect is interpreted in the context of baryon production mechanisms in the fragmentation process. It currently presents a challenge to Monte Carlo models and its origin remains an open question.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Implementing and evaluating a Gaussian mixture framework for identifying gene function from TnSeq data

The rapid acceleration of microbial genome sequencing increases opportunities to understand bacterial gene function. Unfortunately, only a small proportion of genes have been studied. Recently, TnSeq has been proposed as a cost-effective, highly reliable approach to predict gene functions as a response to changes in a cell’s fitness before-after genomic changes. However, major questions remain about how to best determine whether an observed quantitative change in fitness represents a meaningful change. To address the limitation, we develop a Gaussian mixture model framework for classifying gene function from TnSeq experiments. In order to implement the mixture model, we present the Expectation-Maximization algorithm and a hierarchical Bayesian model sampled using Stan’s Hamiltonian Monte-Carlo sampler. We compare these implementations against the frequentist method used in current TnSeq literature. From simulations and real data produced by E.coli TnSeq experiments, we show that the Bayesian implementation of the Gaussian mixture framework provides the most consistent classification results.

Li, Kevin↗
DOE OSTI2019

A Novel Pruning Method for Convolutional Neural Networks Based off Identifying Critical Filters

Convolutional Neural Networks (CNNs) are one of the most extensively used tools in machine learning, but they are still not well understood and in many cases they are over-parameterized, leading to slow inference and impeding their deployment on low-power devices. In the last few years, many methods for decreasing the number of parameters in a network by pruning its output channels have been suggested, but a very recent work has argued that random pruning of channels performs on-par with state-of-the-art pruning methods. While random and other pruning methods might be effectively used for lowering the number of parameters in a CNN, none of these methods can be used to gain any further understanding of the model that the CNN has built. In this work, we propose a novel method for pruning a network, that at the same time can lead to a better understanding of what the individual filters of the network learn about the data. The method proposed aims to keep only the filters that are "important" for a class. We define a filter as important for a class if its removal has the highest negative impact on the accuracy for that class. We demonstrate that our method is better than random pruning on two networks used on the EMNIST and CIFAR10 datasets. By analyzing the important filters, we find that the important filters in the pruned networks learn features which are more general across classes. We demonstrate the importance and applicability of that observation in two transfer-learning tasks.

Dimovska, Mihaela↗