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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens

Abstract Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3–29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%–97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%–94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or “molecular tipping points” that are predictive of later-life health outcomes.

Hill, III,, Thomas↗
DOE OSTI2023

Modulation of polar auxin transport identifies the molecular determinants of source–sink carbon relationships and sink strength in poplar

Abstract Source-to-sink carbon (C) allocation driven by the sink strength, i.e., the ability of a sink organ to import C, plays a central role in tissue growth and biomass productivity. However, molecular drivers of sink strength have not been thoroughly characterized in trees. Auxin, as a major plant phytohormone, regulates the mobilization of photoassimilates in source tissues and elevates the translocation of carbohydrates toward sink organs, including roots. In this study, we used an ‘auxin-stimulated carbon sink’ approach to understand the molecular processes involved in the long-distance source–sink C allocation in poplar. Poplar cuttings were foliar sprayed with polar auxin transport modulators, including auxin enhancers (AE) (i.e., IBA and IAA) and auxin inhibitor (AI) (i.e., NPA), followed by a comprehensive analysis of leaf, stem and root tissues using biomass evaluation, phenotyping, C isotope labeling, metabolomics and transcriptomics approaches. Auxin modulators altered root dry weight and branching pattern, and AE increased photosynthetically fixed C allocation from leaf to root tissues. The transcriptome analysis identified highly expressed genes in root tissue under AE condition including transcripts encoding polygalacturonase and β-amylase that could increase the sink size and activity. Metabolic analyses showed a shift in overall metabolism including an altered relative abundance levels of galactinol, and an opposite trend in citrate levels in root tissue under AE and AI conditions. In conclusion, we postulate a model suggesting that the source–sink C relationships in poplar could be fueled by mobile sugar alcohols, starch metabolism-derived sugars and TCA-cycle intermediates as key molecular drivers of sink strength.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spirochaete genome identified in red abalone sample represents a novel genus Candidatus Haliotispira gen. nov. within the order Spirochaetales

A fully assembled spirochaete genome was identified as a contaminating scaffold in our red abalone ( Haliotis rufescens ) genome assembly. In this paper, we describe the analysis of this bacterial genome. The assembled spirochaete genome is 3.25 Mb in size with 48.5 mol% G+C content. The proteomes of 38 species were compared with the spirochaete genome and it was discovered to form an independent branch within the family Spirochaetaceae on the phylogenetic tree. The comparison of 16S rRNA sequences and average nucleotide identity scores between the spirochaete genome with known species of different families in Spirochaetia indicate that it is an unknown species. Further, the percentage of conserved proteins compared to neighbouring taxa confirm that it does not belong to a known genus within Spirochaetaceae . We propose the name Candidatus Haliotispira prima gen. nov., sp. nov. based on its taxonomic placement and origin. We also tested for the presence of this species in different species of abalone and found that it is also present in white abalone ( Haliotis sorenseni ). In addition, we highlight the need for better classification of taxa within the class Spirochaetia .

Microbiology↗
DOE OSTI2025

Charged-hadron and identified-hadron (𝐾$^{0}_{𝑆}$, Λ, $Ξ$ − ) yield measurements in photonuclear Pb + Pb and 𝑝 + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with ATLAS

This paper presents the measurement of charged-hadron and identified-hadron (𝐾$^{0}_{𝑆}$, Λ, $Ξ$ − ) yields in photonuclear collisions using 1.7nb −1 of $\sqrt{s_{NN}}$ = 5.02 TeV Pb + Pb data collected in 2018 with the ATLAS detector at the Large Hadron Collider. Candidate photonuclear events are selected using a combination of tracking and calorimeter information, including the zero-degree calorimeter. The yields as a function of transverse momentum and rapidity are measured in these photonuclear collisions as a function of charged-particle multiplicity. These photonuclear results are compared with 0.1 nb −1 of $\sqrt{s_{NN}}$ = 5.02 TeV p + Pb data collected in 2016 by ATLAS using similar charged-particle multiplicity selections. These photonuclear measurements shed light on potential quark-gluon plasma formation in photonuclear collisions via observables sensitive to radial flow, enhanced baryon-to-meson ratios, and strangeness enhancement. The results are also compared with the Monte Carlo generator and hydrodynamic calculations to test whether such photonuclear collisions may produce small droplets of quark-gluon plasma that flow collectively.

H & He induced nuclear reactions↗
DOE OSTI2022

Identifying Majorana vortex modes via nonlocal transport

The combination of two-dimensional Dirac surface states with s-wave superconductivity is expected to generate localized topological Majorana zero modes in vortex cores. Putative experimental signatures of these modes have been reported for heterostructures of proximitized topological insulators, iron-based superconductors or certain transition metal dichalcogenides. Despite these efforts, the Majorana nature of the observed excitation is still under debate. In this work, we propose to identify the presence of Majorana vortex modes using a nonlocal transport measurement protocol originally employed for one-dimensional settings. In the case of an isolated subgap state, the protocol provides a spatial map of the ratio of local charge- and probability-density which offers a clear distinction between Majorana and ordinary fermionic modes. We show that these distinctive features survive in the experimentally relevant case of hybridizing vortex core modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Centrality and transverse-momentum dependence of higher-order flow harmonics of identified hadrons in Au+Au collisions at s N N = 200 GeV

Here we present high-precision measurements of elliptic, triangular, and quadrangular flow v 2 , v 3 , and v 4 , respectively, at midrapidity for identified hadrons π, p, K, φ, K s , Λ as a function of centrality and transverse momentum in Au+Au collisions at the center-of-mass energy √ s NN = 200 GeV. We observe similar v n trends between light and strange mesons which indicates that the heavier strange quarks flow as strongly as the lighter up and down quarks. The number-of-constituent-quark scaling for v 2 , v 3 , and v 4 is found to hold within statistical uncertainty for 0–10%, 10–40%, and 40–80% collision centrality intervals. The results are compared to several viscous hydrodynamic calculations with varying initial conditions, and could serve as an additional constraint to the development of hydrodynamic models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Probing initial baryon stopping and equation of state with rapidity-dependent directed flow of identified particles

In this work, using a (3 + 1)-dimensional hybrid framework with parametric initial conditions, we study the rapidity-dependent directed flow $v_1 (y)$ of identified particles, including pions, kaons, protons, and lambdas in heavy-ion collisions. Cases involving Au + Au collisions are considered, performed at $\sqrt {^SNN}$ ranging from 7.7 to 200 GeV. The dynamics in the beam direction is constrained using the measured pseudo-rapidity distribution of charged particles and the net proton rapidity distribution. Within this framework, the directed flow of mesons is driven by the sideward pressure gradient from the tilted source, and that of baryons mainly due to the initial asymmetric baryon distribution with respect to the beam axis driven by the transverse expansion. Our approach successfully reproduces the rapidity- and beam energy-dependence of $v_1$ for both mesons and baryons. We find that the $v_1 (y)$ of baryons has strong constraining power on the initial baryon stopping, and together with that of mesons, the directed flow probes the equation of state of the dense nuclear matter at finite chemical potentials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Centrality dependence of identified particle elliptic flow in relativistic heavy ion collisions at s N N = 7.7 – 62.4 GeV

Here, elliptic flow (v 2 ) values for identified particles at midrapidity in Au + Au collisions measured by the STAR experiment in the Beam Energy Scan at the Relativistic Heavy Ion Collider at √s NN = 7.7–62.4 GeV are presented for three centrality classes. The centrality dependence and the data at √s NN = 14.5 GeV are new. Except at the lowest beam energies, we observe a similar relative v 2 baryon-meson splitting for all centrality classes which is in agreement within 15% with the number-of-constituent quark scaling. The larger v 2 for most particles relative to antiparticles, already observed for minimum bias collisions, shows a clear centrality dependence, with the largest difference for the most central collisions. Also, the results are compared with a multiphase transport (AMPT) model and fit with a blast wave model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Learning to identify electrons

In this report we investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information. A deep convolutional neural network analysis of electromagnetic and hadronic calorimeter deposits is compared to the performance of typical features, revealing a ≈ 5% gap which indicates that these lower-level data do contain untapped classification power. To reveal the nature of this unused information, we use a recently developed technique to map the deep network into a space of physically interpretable observables. We identify two simple calorimeter observables which are not typically used for electron identification, but which mimic the decisions of the convolutional network and nearly close the performance gap.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Exploiting jet binning to identify the initial state of high-mass resonances

If a new high-mass resonance is discovered at the Large Hadron Collider, model-independent techniques to identify the production mechanism will be crucial to understand its nature and effective couplings to Standard Model particles. In this paper, we present a powerful and model-independent method to infer the initial state in the production of any high-mass color-singlet system by using a tight veto on accompanying hadronic jets to divide the data into two mutually exclusive event samples (jet bins). For a resonance of several hundred GeV, the jet binning cut needed to discriminate quark and gluon initial states is in the experimentally accessible range of several tens of GeV. It also yields comparable cross sections for both bins, making this method viable already with the small event samples available shortly after a discovery. Theoretically, the method is made feasible by utilizing an effective field theory setup to compute the jet cut dependence precisely and model independently and to systematically control all sources of theoretical uncertainties in the jet binning, as well as their correlations. Finally, we use a 750 GeV scalar resonance as an example to demonstrate the viability of our method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Search for supersymmetry in proton-proton collisions at 13 TeV using identified top quarks

A search for supersymmetry is presented based on proton-proton collision events containing identified hadronically decaying top quarks, no leptons, and an imbalance pTmiss in transverse momentum. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 35.9 fb−1. Search regions are defined in terms of the multiplicity of bottom quark jet and top quark candidates, the pTmiss, the scalar sum of jet transverse momenta, and the mT2 mass variable. No statistically significant excess of events is observed relative to the expectation from the standard model. Lower limits on the masses of supersymmetric particles are determined at 95% confidence level in the context of simplified models with top quark production. For a model with direct top squark pair production followed by the decay of each top squark to a top quark and a neutralino, top squark masses up to 1020 GeV and neutralino masses up to 430 GeV are excluded. For a model with pair production of gluinos followed by the decay of each gluino to a top quark-antiquark pair and a neutralino, gluino masses up to 2040 GeV and neutralino masses up to 1150 GeV are excluded. These limits extend previous results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Identifying structural changes with unsupervised machine learning methods

In this work, unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

42 ENGINEERING↗
DOE OSTI2019

Key Ne 19 States Identified Affecting γ -Ray Emission from F 18 in Novae

Detection of nuclear-decay γ rays provides a sensitive thermometer of nova nucleosynthesis. The most intense γ-ray flux is thought to be annihilation radiation from the β + decay of 18 F, which is destroyed prior to decay by the 18 F(p,α) 15 O reaction. Estimates of 18 F production had been uncertain, however, because key near-threshold levels in the compound nucleus, 19 Ne, had yet to be identified. We report the first measurement of the 19 F( 3 He, tγ ) 19 Ne reaction, in which the placement of two long-sought 3/2 + levels is suggested via triton-γ–γ coincidences. Furthermore, the precise determination of their resonance energies reduces the upper limit of the rate by a factor of 1.5–17 at nova temperatures and reduces the average uncertainty on the nova detection probability by a factor of 2.1.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Using Disorder to Identify Bogoliubov Fermi-Surface States

We argue that a superconducting state with a Fermi surface of Bogoliubov quasiparticles, a Bogoliubov Fermi surface (BG-FS), can be identified by the dependence of physical quantities on disorder. In particular, we show that a linear dependence of the residual density of states at weak disorder distinguishes a BG-FS state from other nodal superconducting states. We further demonstrate the stability of supercurrent against impurities and a characteristic Drude-like behavior of the optical conductivity. Our results can be directly applied to electron irradiation experiments on candidate materials of BG-FSs, including Sr 2 RuO 4 , FeSe 1-x S x , and UBe 13 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Using Direct Laboratory Measurements of Electron Temperature Anisotropy to Identify the Heating Mechanism in Electron-Only Guide Field Magnetic Reconnection

Anisotropic electron heating during electron-only magnetic reconnection with a large guide magnetic field is directly measured in a laboratory plasma through in situ measurements of electron velocity distribution functions. Electron heating preferentially parallel to the magnetic field is localized to one separatrix, and anisotropies of 1.5 are measured. The mechanism for electron energization is identified as the parallel reconnection electric field because of the anisotropic nature of the heating and spatial localization. These characteristics are reproduced in a 2D particle-in-cell simulation and are also consistent with numerous magnetosheath observations. A measured increase in the perpendicular temperature along both separatrices is not reproduced by our 2D simulations. Here, this work has implications for energy partition studies in magnetosheath and laboratory reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Association between optically identified galaxy clusters and the underlying dark matter halos

Clusters of galaxies trace massive dark matter halos in the Universe, but they can include multiple halos projected along lines of sight. Here, we study the halos contributing to clusters using the Cardinal simulation, which mimics the Dark Energy Survey data. We use the red-sequence-based cluster finding algorithm redMaPPer as a case study. For each cluster, we identify the halos hosting its member galaxies, and we define the main halo as the one contributing the most to the cluster's richness ($λ$, the estimated number of member galaxies). At $z=0.3$, for clusters with $λ> 60$, the main halo typically contributes to $92\%$ of the richness, and this fraction drops to $67\%$ for $λ\approx 20$. Defining "clean" clusters as those with $\geq50\%$ of the richness contributed by the main halo, we find that $100\%$ of the $λ> 60$ clusters are clean, while $73\%$ of the $λ\approx 20$ clusters are clean. Three halos can usually account for more than $80\%$ of the richness of a cluster. The main halos associated with redMaPPer clusters have a completeness ranging from $98\%$ at virial mass $10^{14.6}~h^{-1}M_{\odot}$ to $64\%$ at $10^{14}~h^{-1}M_{\odot}$. In addition, we compare the inferred cluster centers with true halo centers, finding that $30\%$ of the clusters are miscentered with a mean offset $40\%$ of the cluster radii, in agreement with recent X-ray studies. These systematics worsen as redshift increases, but we expect that upcoming surveys extending to longer wavelengths will improve the cluster finding at high redshifts. Our results affirm the robustness of the redMaPPer algorithm and provide a framework for benchmarking other cluster-finding strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Crystallization and X-ray diffraction analysis of the HMG domain of the chondrogenesis master regulator Sox9 in complex with a ChIP-Seq-identified DNA element

Sox9 is a fundamental sex-determining gene and the master regulator of chondrogenesis, and is involved in the development of various vital organs such as testes, kidney, heart and brain, and in skeletal development. Similar to other known Sox transcription factors, Sox9 recognizes and binds DNA with the consensus sequence C(T/A)TTG(T/A)(T/A) through the highly conserved HMG domain. Nonetheless, the molecular basis of the functional specificity of Sox9 in key developmental processes is still unclear. As an initial step towards a mechanistic understanding of Sox9 transcriptional regulation, the current work describes the details of the purification of the mouse Sox9 HMG domain (mSox9HMG), its crystallization in complex with a ChIP-Seq-identified FOXP2 promoter DNA element and the X-ray diffraction data analysis of this complex. The mSox9HMG–FOXP2 promoter DNA complex was crystallized by the hanging-drop vapour-diffusion method using 20% PEG 3350 in 200 m M sodium/potassium phosphate with 100 m M bis-tris propane at pH 8.5. The crystals diffracted to 2.7 Å resolution and the complex crystallized in the tetragonal space group P 4 1 2 1 2, with unit-cell parameters a = b = 99.49, c = 45.89 Å. Crystal-packing parameters revealed that asymmetric unit contained one mSox9HMG–FOXP2 promoter DNA complex with an estimated solvent content of 64%.

62 RADIOLOGY AND NUCLEAR MEDICINE↗