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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unveiling a pervasive DNA adenine methylation regulatory network in the early-diverging fungus Rhizopus microsporus

Development of the DNA affinity purification and sequencing (DAP-seq) technique has allowed genome-scale studies of transcription factor (TF)-binding sites with high reproducibility. Here, we apply this technique to the human opportunistic pathogen Rhizopus microsporus, a mucoralean fungus belonging to the understudied group of early-diverging fungi. We characterize genome-wide binding sites of 58 TFs encoded by genes regulated through adenine methylation and representing major TF families. This analysis reveals their binding profiles and recognized sequences, expanding and diversifying the catalog of known fungal motifs. By integrating this data with DNA 6-methyladenine profiling, we uncover the extensive direct and indirect impact of this epigenetic modification on the regulation of gene expression. Furthermore, we use the generated data to identify TFs involved in biologically relevant processes such as zinc metabolism and light response. Our work enhances our understanding of regulatory mechanisms in R. microsporus and provides broader insights into gene regulation across the fungal kingdom.

Lax, Carlos [Universidad de Murcia (Spain)] (ORCID↗
DOE OSTI2019

Variational quantum state diagonalization

Abstract Variational hybrid quantum-classical algorithms are promising candidates for near-term implementation on quantum computers. In these algorithms, a quantum computer evaluates the cost of a gate sequence (with speedup over classical cost evaluation), and a classical computer uses this information to adjust the parameters of the gate sequence. Here we present such an algorithm for quantum state diagonalization. State diagonalization has applications in condensed matter physics (e.g., entanglement spectroscopy) as well as in machine learning (e.g., principal component analysis). For a quantum state ρ and gate sequence U , our cost function quantifies how far $$U\rho U^\dagger$$ U ρ U † is from being diagonal. We introduce short-depth quantum circuits to quantify our cost. Minimizing this cost returns a gate sequence that approximately diagonalizes ρ . One can then read out approximations of the largest eigenvalues, and the associated eigenvectors, of ρ . As a proof-of-principle, we implement our algorithm on Rigetti’s quantum computer to diagonalize one-qubit states and on a simulator to find the entanglement spectrum of the Heisenberg model ground state.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study

High-throughput sequencing technology has enabled researchers to profile microbial communities from a variety of environments, but analysis of multivariate taxon count data remains challenging. Here, we develop a Bayesian nonparametric (BNP) regression model with zero inflation to analyse multivariate count data from microbiome studies. A BNP approach flexibly models microbial associations with covariates, such as environmental factors and clinical characteristics. The model produces estimates for probability distributions which relate microbial diversity and differential abundance to covariates, and facilitates community comparisons beyond those provided by simple statistical tests. We compare the model to simpler models and popular alternatives in simulation studies, showing, in addition to these additional community-level insights, it yields superior parameter estimates and model fit in various settings. The model's utility is demonstrated by applying it to a chronic wound microbiome data set and a Human Microbiome Project data set, where it is used to compare microbial communities present in different environments.

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

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Slides]

The SCALE code package offers multiple nuclear data libraries supporting Monte Carlo transport, with sensitivity and uncertainty methods derived from MC transport solutions. Several libraries are multigroup, which introduce bias differing by system. Previous work has shown poor S/U results in several reflector materials: ICSBEP benchmark HMF-084 was selected to analyze biases and S/U method applicability to a variety of reflectors. Prior and ongoing work found inaccuracies in CSAS and TSUNAMI results, which were further investigated utilizing the HEU-MET-FAST-084 ICSBEP critical benchmark, chosen for its geometrical simplicity and variety of reflector materials. Perturbation of reflector thickness across various reflector materials allowed for an assortment of materials is to be tested swiftly for each sequence and method. Observation was an increasing bias of MG $k_{eff}$ relative to CE, in both direction and magnitude. IFP produced extremely reliable results. >85% of CLUTCH cases were found satisfactory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

The emergence and transmission dynamics of HIV-1 CRF07_BC in Mainland China

A total of 1155 partial pol gene sequences of human immunodeficiency virus (HIV)-1 CRF07_BC were sampled between 1997 and 2015, spanning 13 provinces in Mainland China and risk groups [heterosexual, injecting drug users (IDU), and men who have sex with men (MSM)] to investigate the evolution, adaptation, spatiotemporal and risk group dynamics, migration patterns, and protein structure of HIV-1 CRF07_BC. Due to the unequal distribution of sequences across time, location, and risk group in the complete dataset (‘full1155’), subsampling methods were used. Maximum-likelihood and Bayesian phylogenetic analysis as well as discrete trait analysis of geographical location and risk group were carried out. To study mutations of a cluster of HIV-1 CRF07_BC (CRF07-1), we performed a comparative analysis of this cluster to the other CRF07_BC sequences (‘backbone_295’) and mapped the mutations observed in the respective protein structure. Our findings showed that HIV-1 CRF07_BC most likely originated among IDU in Yunnan Province between October 1992 to July 1993 [95 per cent hightest posterior density (HPD): May 1989–August 1995] and that IDU in Yunnan Province and MSM in Guangdong Province likely served as the viral sources during the early and more recent spread in Mainland China. We also revealed that HIV-1 CRF07-1 has been spreading for roughly 20 years and continues to cause local transmission in Mainland China and worldwide. Overall, our study sheds light on the dynamics of HIV-1 CRF07_BC distribution patterns in Mainland China. Our research may also be useful in formulating public health policies aimed at controlling acquired immune deficiency syndrome in Mainland China and globally.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

CD −24°17504 REVISITED: A NEW COMPREHENSIVE ELEMENT ABUNDANCE ANALYSIS

With [Fe/H] ∼ −3.3, CD −24°17504 is a canonical metal-poor main-sequence turn-off star. Though it has appeared in numerous literature studies, the most comprehensive abundance analysis for the star based on high-resolution, high signal-to-noise ratio (S/N) spectra is nearly 15 years old. We present a new detailed abundance analysis for 21 elements based on combined archival Keck-HIRES and Very Large Telescope-UVES spectra of the star that is higher in both spectral resolution and S/N than previous data. Our results are very similar to those of an earlier comprehensive study of the star, but we present for the first time a carbon abundance from the CH G-band feature as well as improved upper limits for neutron-capture species such as Y, Ba, and Eu. In particular, we find that CD −24°17504 has [Fe/H] = −3.41, [C/Fe] = +1.10, [Sr/H] = −4.68, and [Ba/H] ≤ −4.46, making it a carbon-enhanced metal-poor star with neutron-capture element abundances among the lowest measured in Milky Way halo stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

United States Department of Energy severe accident research following the Fukushima Daiichi accidents

The U.S. Department of Energy (DOE) has played a major role in the U.S. response to the events at Fukushima Daiichi. During the first several weeks following the accident, U.S. assistance efforts were guided by results from a significant and diverse set of analyses. In the months that followed, a coordinated analysis activity aimed at gaining a more thorough understanding of the accident sequence was completed using laboratory-developed, system-level best-estimate accident analysis codes, while a parallel analysis was conducted by U.S. industry. A comparison of predictions for Unit 1 from these two studies indicated significant differences between MAAP and MELCOR results for key plant parameters, such as in-core hydrogen production. On that basis, a crosswalk was completed to determine the key modeling variations that led to these differences. In parallel with these activities, it became clear that there was a need to perform a technology gap evaluation on accident-tolerant components and severe accident analysis methodologies with the goal of identifying any data and/or knowledge gaps that may exist given the current state of light water reactor (LWR) severe accident research and augmented by insights from Fukushima. In addition, there is growing international recognition that data from Fukushima could significantly reduce uncertainties related to severe accident progression, particularly for boiling water reactors. On these bases, a group of U. S. experts in LWR safety and plant operations was convened by the DOE Office of Nuclear Energy (DOE-NE) to complete technology gap analysis and Fukushima forensics data needs identification activities. The results from these activities were used as the basis for refining DOE-NE's severe accident research and development (R&D) plan. Finally, this paper provides a high-level review of DOE-sponsored R&D efforts in these areas, including planned activities on accident-tolerant components and accident analysis methods.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

RY AQUARIUS A BINARY SYSTEM WITH PULSATING δ-SCUTI PRIMARY COMPONENT

We present simultaneous new BVI light curves along with radial velocity curve analysis of the RY Aqr system, using the PHysics Of Eclipsing BinariEs code. The analysis indicates that while the primary is completely inside its Roche critical surface, the secondary has filled out its Roche surface. In addition, the positions of the system components on M–R, H–R diagrams are specified, which show that the primary is a main-sequence or nearly main-sequence star while the secondary is an evolved subgiant. In addition, analysis of the period and luminosity variations of the system were carried out. Fourier frequency analysis of light variation indicates that the primary is a pulsating, δ-scuti variable star. Moreover, O–C curve analysis shows that the period of the system is secularly decreasing with a rate of dp/dt = 0.074 s yr{sup −1}. This decrease in the orbital period variations was attributed to a mass and angular momentum loss from the system with a rate of 2.57×10{sup −10}M{sub ⊙} yr{sup −1}. Apart from the secular period decreases, the orbital period of the system is modulated by a cyclic period of 72.69 year, which was attributed to a third body orbiting around the barycenter of the system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Noise-gating to Clean Astrophysical Image Data

I present a family of algorithms to reduce noise in astrophysical images and image sequences, preserving more information from the original data than is retained by conventional techniques. The family uses locally adaptive filters (“noise gates”) in the Fourier domain to separate coherent image structure from background noise based on the statistics of local neighborhoods in the image. Processing of solar data limited by simple shot noise or by additive noise reveals image structure not easily visible in the originals, preserves photometry of observable features, and reduces shot noise by a factor of 10 or more with little to no apparent loss of resolution. This reveals faint features that were either not directly discernible or not sufficiently strongly detected for quantitative analysis. The method works best on image sequences containing related subjects, for example movies of solar evolution, but is also applicable to single images provided that there are enough pixels. The adaptive filter uses the statistical properties of noise and of local neighborhoods in the data to discriminate between coherent features and incoherent noise without reference to the specific shape or evolution of those features. The technique can potentially be modified in a straightforward way to exploit additional a priori knowledge about the functional form of the noise.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Nontargeted virus sequence discovery pipeline and virus clustering for metagenomic data

The analysis of large microbiome data sets holds great promise for the delineation of the biological and metabolic functioning of living organisms and their role in the environment. In the midst of this genomic puzzle, viruses, especially those that infect microbial communities, represent a major reservoir of genetic diversity with great impact on biogeochemical cycles and organismal health. Overcoming the limitations associated with virus detection directly from microbiomes can provide key insights into how ecosystem dynamics are modulated. Here, we present a computational protocol for accurate detection and grouping of viral sequences from microbiome samples. Our approach relies on an expanded and curated set of viral protein families used as bait to identify viral sequences directly from metagenomic assemblies. This protocol describes how to use the viral protein families catalog (~7 h) and recommended filters for the detection of viral contigs in metagenomic samples (~6 h), and it describes the specific parameters for a nucleotide-sequence-identity-based method of organizing the viral sequences into quasi-species taxonomic-level groups (~10 min).

Paez-Espino, David↗
DOE OSTI2015

Aquifer environment selects for microbial species cohorts in sediment and groundwater

Little is known about the biogeography or stability of sediment-associated microbial community membership because these environments are biologically complex and generally difficult to sample. High-throughput-sequencing methods provide new opportunities to simultaneously genomically sample and track microbial community members across a large number of sampling sites or times, with higher taxonomic resolution than is associated with 16 S ribosomal RNA gene surveys, and without the disadvantages of primer bias and gene copy number uncertainty. We characterized here a sediment community at 5 m depth in an aquifer adjacent to the Colorado River and tracked its most abundant 133 organisms across 36 different sediment and groundwater samples. We sampled sites separated by centimeters, meters and tens of meters, collected on seven occasions over 6 years. Analysis of 1.4 terabase pairs of DNA sequence showed that these 133 organisms were more consistently detected in saturated sediments than in samples from the vadose zone, from distant locations or from groundwater filtrates. Abundance profiles across aquifer locations and from different sampling times identified organism cohorts that comprised subsets of the 133 organisms that were consistently associated. The data suggest that cohorts are partly selected for by shared environmental adaptation.

58 GEOSCIENCES↗
DOE OSTI2017

Bacterial Community Dynamics in Dichloromethane-Contaminated Groundwater Undergoing Natural Attenuation

The uncontrolled release of the industrial solvent methylene chloride, also known as dichloromethane (DCM), has resulted in widespread groundwater contamination in the United States. Here we investigate the role of groundwater bacterial communities in the natural attenuation of DCM at an undisclosed manufacturing site in New Jersey. Here, we investigate the bacterial community structure of groundwater samples differentially contaminated with DCM to better understand the biodegradation potential of these autochthonous bacterial communities. Bacterial community analysis was completed using high-throughput sequencing of the 16S rRNA gene of groundwater samples (n = 26) with DCM contamination ranging from 0.89 to 9,800,000 μg/L. Significant DCM concentration-driven shifts in overall bacterial community structure were identified between samples, including an increase in the abundance of Firmicutes within the most contaminated samples. And across all samples, a total of 6,134 unique operational taxonomic units (OTUs) were identified, with 16 taxa having strong correlations with increased DCM concentration. Putative DCM degraders such as Pseudomonas, Dehalobacterium and Desulfovibrio were present within groundwater across all levels of DCM contamination. Interestingly, each of these taxa dominated specific DCM contamination ranges respectively. Potential DCM degrading lineages yet to be cited specifically as a DCM degrading organisms, such as the Desulfosporosinus, thrived within the most heavily contaminated groundwater samples. Co-occurrence network analysis revealed aerobic and anaerobic bacterial taxa with DCM-degrading potential were present at the study site. Our 16S rRNA gene survey serves as the first in situ bacterial community assessment of contaminated groundwater harboring DCM concentrations ranging over seven orders of magnitude. Diversity analyses revealed known as well as potentially novel DCM degrading taxa within defined DCM concentration ranges, indicating niche-specific responses of these autochthonous populations. Altogether, our findings suggest that monitored natural attenuation is an appropriate remediation strategy for DCM contamination, and that high-throughput sequencing technologies are a robust method for assessing the potential role of biodegrading bacterial assemblages in the apparent reduction of DCM concentrations in environmental scenarios.

16S rRNA↗
DOE OSTI2016

‘ Candidatus Dichloromethanomonas elyunquensis’ gen. nov., sp. nov., a dichloromethane-degrading anaerobe of the Peptococcaceae family

Taxonomic assignments of anaerobic dichloromethane (DCM)-degrading bacteria remain poorly constrained but are important for understanding the microbial diversity of organisms contributing to DCM turnover in environmental systems. Here, we describe the taxonomic classification of a novel DCM degrader in consortium RM obtained from pristine Rio Mameyes sediment. Phylogenetic analysis of full-length 16S rRNA gene sequences demonstrated that the DCM degrader was most closely related to members of the genera Dehalobacter and Syntrophobotulus, but sequence similarities did not exceed 94% and 93%, respectively. Genome-aggregate average amino acid identities against Peptococcaceae members did not exceed 66%, suggesting that the DCM degrader does not affiliate with any described genus. Phylogenetic analysis of conserved single-copy functional genes supported that the DCM degrader represents a novel clade. Growth strictly depended on the presence of DCM, which was consumed at a rate of 160 ± 3 μmol L -1 d -1 . The DCM degrader attained 5.25 × 10 7 ± 1.0 × 10 7 cells per μmol DCM consumed. Fluorescence in situ hybridization revealed rod-shaped cells 4 ± 0.8 μm long and 0.4 ± 0.1 μm wide. Furthermore, based on the unique phylogenetic, genomic, and physiological characteristics, we propose that the DCM degrader represents a new genus and species, ‘Candidatus Dichloromethanomonas elyunquensis’.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗
DOE OSTI2018

Generating a high-confidence reference genome map of the Greater Duckweed by integration of cytogenomic, optical mapping, and Oxford Nanopore technologies

Duckweeds are the fastest growing angiosperms and have the potential to become a new generation of sustainable crops. Although a seed plant, Spirodela polyrhiza clones rarely flower and multiply mainly through vegetative propagation. Whole-genome sequencing using different approaches and clones yielded two reference maps. One for clone 9509, supported in its assembly by optical mapping of single DNA molecules, and one for clone 7498, supported by cytogenetic assignment of 96 fingerprinted bacterial artificial chromosomes (BACs) to its 20 chromosomes. However, these maps differ in the composition of several individual chromosome models. We validated both maps further to resolve these differences and addressed whether they could be due to chromosome rearrangements in different clones. For this purpose, we applied sequential multicolor fluorescence in situ hybridization (mcFISH) to seven S. polyrhiza clones, using 106 BACs that were mapped onto the 39 pseudomolecules for clone 7498. Furthermore we integrated high-depth Oxford Nanopore (ON) sequence data for clone 9509 to validate and revise the previously assembled chromosome models. We found no major structural rearrangements between these seven clones, identified seven chimeric pseudomolecules and Illumina assembly errors in the previous maps, respectively. A new S. polyrhiza genome map with high contiguity was produced with the ON sequence data and genome-wide synteny analysis supported the occurrence of two Whole Genome Duplication events during its evolution. This work generated a high confidence genome map for S. polyrhiza at the chromosome scale, and illustrates the complementarity of independent approaches to produce whole-genome assemblies in the absence of a genetic map.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Crewmember microbiome may influence microbial composition of ISS habitable surfaces

The International Space Station (ISS) is a complex built environment physically isolated from Earth. Assessing the interplay between the microbial community of the ISS and its crew is important for preventing biomedical and structural complications for long term human spaceflight missions. In this study, we describe one crewmember’s microbial profile from body swabs of mouth, nose, ear, skin and saliva that were collected at eight different time points pre-, during and post-flight. Additionally, environmental surface samples from eight different habitable locations in the ISS were collected from two flights. Environmental samples from one flight were collected by the crewmember and samples from the next flight were collected after the crewmember departed. The microbial composition in both environment and crewmember samples was measured using shotgun metagenomic sequencing and processed using the Livermore Metagenomics Analysis Toolkit. Ordination of sample to sample distances showed that of the eight crew body sites analyzed, skin, nostril, and ear samples are more similar in microbial composition to the ISS surfaces than mouth and saliva samples; and that the microbial composition of the crewmember’s skin samples are more closely related to the ISS surface samples collected by the crewmember on the same flight than ISS surface samples collected by other crewmembers on different flights. In these collections, species alpha diversity in saliva samples appears to decrease during flight and rebound after returning to Earth. This is the first study to compare the ISS microbiome to a crewmember’s microbiome via shotgun metagenomic sequencing. We observed that the microbiome of the surfaces inside the ISS resemble those of the crew’s skin. These data support future crew and ISS microbial surveillance efforts and the design of preventive measures to maintain crew habitat onboard spacecraft destined for long term space travel.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Full core LOCA analysis for BWR/6 - Methodology and first results

As part of collaboration between the Paul Scherrer Institute (PSI) and the Swiss regulator ENSI, a study aimed at core-wide estimates of the fuel rod behaviour during large-break loss-of-coolant-accidents (LB-LOCA) in BWR/6 plants was recently conducted on the basis of a Swiss reactor. To perform such full core LOCA analysis, a methodology consisting of a multi-physics sequence of interfaced best-estimate models and codes was established: CASMO-4E/SIMULATE-3 (C4/S3) for the core modelling, TRACE for the plant system analysis and FALCON for the fuel thermomechanical calculations during base irradiation (BI) as well as for the transient analyses (TA). As starting point, reference C4/S3 models validated for all operated cycles of the given plant were used to select as situation target, a recent cycle representative of modern BWR core loadings and fuel assembly designs. Based on the selected C4/S3 cycle model, PSI in-house computational modules were developed or updated in order to set up the TRACE full core model with regards to assembly geometries, fuel rods thermophysical properties and initial 3-D power distributions. Also, an interface to FALCON BI models was established for the transfer of the irradiation history, including primarily linear heat generation rates (LHGR), for an equivalent fuel pin. For each assembly, the power of the equivalent pin is defined with the maximum power of all pins at each axial position. However, in order to reduce the computational time of the fuel performance analyses, the whole core was subdivided into groups of assemblies, each represented by the most powerful assembly within the group. On this basis, the FALCON BI analyses were conducted with coupling to the PSI advanced model for gas release and swelling (GRWS-A) and an interface was developed to transfer the calculated fuel rod characteristics at end of irradiation to initialize the core fuel rods heat structures in the TRACE model. Subsequently, double-ended recirculation line rupture scenarios at hot-full-power (HFP) conditions were investigated with TRACE in order to determine a conservative transient case as function of cycle burnup, single failure criterion and availability of safety systems. For the most conservative case of this study, an interface was set-up to transfer the TRACE results as boundary conditions to the FALCON TA models, including thus primarily time and axial distributions of the clad outer temperatures. As final step, the FALCON TA were conducted for the representative assemblies in order to infer core-wide estimates of the fuel rod behaviour with specific focus on equivalent cladding reacted levels, hoop strains as well as margins to failure criteria. The objective of this paper is to present this methodology along with the obtained first results. Regarding the latter, it is found that principally, even for the most conservative LOCA scenario of this study, the clad temperature excursion remains mild enough at all core locations such that no significant rod ballooning and no cladding failure is predicted, something in line with corresponding analyses conducted earlier for BWR/4 plants. (authors)

42 ENGINEERING↗