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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Taxogenomic analysis of Pichia senei sp. nov. and new insights into hybridization events in the Pichia cactophila species complex

Three strains of a novel yeast species were isolated from necrotic cactus tissues of Cereus saddianus and Micranthocereus dolichospermaticus and from phytotelmata of Bromelia karatas. DNA sequence analysis of the Internal Transcribed Spacer (ITS) region and D1/D2 domains of the large subunit ribosomal RNA, along with whole genome phylogenomic analysis, showed that this yeast is most closely related to Pichia insulana, Pichia cactophila, and Pichia inconspicua. The new species differs by 10–13 nucleotide substitutions from these species in D1/D2 sequences and exhibits <90% genome-wide average nucleotide identity to them. The name Pichia senei sp. nov. is proposed for the novel species, which is homothallic and produces asci with one to four hat-shaped ascospores. The holotype is CBS 16311 (MycoBank MB 858723). Taxogenomic analyses of the P. cactophila species complex, including P. senei, provide new insights about the hybridizations events that shaped this group. Pichia insulana and P. inconspicua are identified as the parental lineages that originated P. cactophila, and P. senei also appears closely related to one of the progenitors of P. inconspicua. We assess phylogeny, heterozygosity, and ploidy to explore the processes shaping diversity, showing how genomic data support yeast species delimitation and reveal complex hybridization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2010

Structures of carbon catabolite protein A–(HPr-Ser46-P) bound to diverse catabolite response element sites reveal the basis for high-affinity binding to degenerate DNA operators

In Gram-positive bacteria, carbon catabolite protein A (CcpA) is the master regulator of carbon catabolite control, which ensures optimal energy usage under diverse conditions. Unlike other LacI-GalR proteins, CcpA is activated for DNA binding by first forming a complex with the phosphoprotein HPr-Ser46-P. Bacillus subtilis CcpA functions as both a transcription repressor and activator and binds to more than 50 operators called catabolite response elements (cres). These sites are highly degenerate with the consensus, WTGNNARCGNWW WCAW. How CcpA–(HPr-Ser46-P) binds such diverse sequences is unclear. To gain insight into this question, we solved the structures of the CcpA–(HPr-Ser46-P) complex bound to three different operators, the synthetic (syn) cre, ackA2 cre and gntR-down cre. Strikingly, the structures show that the CcpA-bound operators display different bend angles, ranging from 31 to 56. These differences are accommodated by a flexible linkage between the CcpA helix-turn-helix-loop-helix motif and hinge helices, which allows independent docking of these DNA-binding modules. This flexibility coupled with an abundance of non-polar residues capable of non-specific nucleobase interactions permits CcpA–(HPr-Ser46-P) to bind diverse operators. Indeed, biochemical data show that CcpA–(HPr-Ser46-P) binds the three cre sites with similar affinities. Thus, the data reveal properties that license this protein to function as a global transcription regulator.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Multi‐omics of the Soil Microbiome

TheArctic is characterized by vast amounts of carbon stored in permafrost and isan important focal point for the study of climate change as increasing temperature may accelerate microbially‐mediated release of carbon stored inpermafrost into the atmosphere as CO 2 and CH 4 . Yet surprisingly, very little is known about the vulnerability of permafrost andresponse of microorganisms in the permafrost to their changing environment. To address these knowledge gaps we used omics technologiesto explore permafrost microbial communities, to reveal hitherto unknown soilmicrobial populations and to link them to specific soil biogeochemical processes. For these projects we employed an omics pipeline that includes metagenomics, metatranscriptomics and metaproteomics to determine the phylogenetic and functional gene compositions and their expression in complex, non‐sterile soil samples collected from the field at several locations in Alaska. These studies have presented several challenges due to the unprecedented large size of the datasets and the insufficiency of available bioinformatic tools & databases to analyze, correlate and integrate thedata. To address these challenges we developed a novel functional gene databaseand used different assembly and analysis algorithms to determine key featuresin the datasets. The data reveal the microbial diversity, composition andfunctional potential in permafrost and how the microbial communities respond toclimate change impacts. Support or Funding Information Microbiomes in Transition, LDRD, Pacific Northwest National Laboratories, Richland, Washington

Jansson, Janet K.↗
DOE OSTI2014

Comparative validation of the D. melanogaster modENCODE transcriptome annotation

Accurate gene model annotation of reference genomes is critical for making them useful. The modENCODE project has improved the D. melanogaster genome annotation by using deep and diverse high-throughput data. Since transcriptional activity that has been evolutionarily conserved is likely to have an advantageous function, we have performed large-scale interspecific comparisons to increase confidence in predicted annotations. To support comparative genomics, we filled in divergence gaps in the Drosophila phylogeny by generating draft genomes for eight new species. For comparative transcriptome analysis, we generated mRNA expression profiles on 81 samples from multiple tissues and developmental stages of 15 Drosophila species, and we performed cap analysis of gene expression in D. melanogaster and D. pseudoobscura. We also describe conservation of four distinct core promoter structures composed of combinations of elements at three positions. Overall, each type of genomic feature shows a characteristic divergence rate relative to neutral models, highlighting the value of multispecies alignment in annotating a target genome that should prove useful in the annotation of other high priority genomes, especially human and other mammalian genomes that are rich in noncoding sequences. We report that the vast majority of elements in the annotation are evolutionarily conserved, indicating that the annotation will be an important springboard for functional genetic testing by the Drosophila community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions

High-order finite element methods (HO-FEM) are gaining popularity in the simulation community due to their success in solving complex flow dynamics. There is an increasing need to analyze the data produced as output by these simulations. Simultaneously, topological analysis tools are emerging as powerful methods for investigating simulation data. Yet, most of the current approaches to topological analysis have had limited application to HO-FEM simulation data for two reasons. First, the current topological tools are designed for linear data (polynomial degree one), but the polynomial degree of the data output by these simulations is typically higher (routinely up to polynomial degree six). Second, the simulation data and derived quantities of the simulation data have discontinuities at element boundaries, and these discontinuities do not match the input requirements for the topological tools. One solution to both issues is to transform the high-order data to achieve low-order, continuous inputs for topological analysis. Nevertheless, there has been little work evaluating the possible transformation choices and their downstream effect on the topological analysis. We perform an empirical study to evaluate two commonly used data transformation methodologies along with the recently introduced L-SIAC filter for processing high-order simulation data. Our findings indicate diverse behaviors are possible. We offer some guidance about how best to consider a pipeline of topological analysis of HO-FEM simulations with the currently available implementations of topological analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Design of composite inhibitors targeting glutamate carboxypeptidase II: the importance of effector functionalities

Inhibitors targeting human glutamate carboxypeptidase II (GCPII) typically consist of a P1' glutamate-derived binding module, which warrants the high affinity and specificity, linked to an effector function that is positioned within the entrance funnel of the enzyme. In this paper we present a comprehensive structural and computational study aimed at dissecting the importance of the effector function for GCPII binding and affinity. To this end we determined crystal structures of human GCPII in complex with a series of phosphoramidate-based inhibitors harboring effector functions of diverse physicochemical characteristics. Our data show that higher binding affinities of phosphoramidates, compared to matching phosphonates, are linked to the presence of additional hydrogen bonds between Glu424 and Gly518 of the enzyme and the amide group of the phosphoramidate. While the positioning of the P1' glutamate-derived module within the S1' pocket of GCPII is invariant, interaction interfaces between effector functions and residues lining the entrance funnel are highly varied, with the positively charged arginine patch defined by Arg463, Arg534 and Arg536 being the only ‘hot-spot’ common to several studied complexes. This variability stems in part from the fact that the effector/GCPII interfaces generally encompass isolated areas of nonpolar residues within the entrance funnel and resulting van der Waals contacts lack the directionality typical for hydrogen bonding interactions. The presented data unravel a complexity of binding modes of inhibitors within non-prime site(s) of GCPII and can be exploited for the design of novel GCPII-specific compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Reverse Logistics Ev Battery Recycling Agent Base Model

This represents the initial regional tier of the electric vehicle (EV) battery recycling agent base model. Through this model, we can ascertain the number of EV purchases at both the state and regional levels. We employ census data to develop a diverse household profile to inform decisions regarding the acquisition of new or used EVs. The number of EV purchases at the state level will affect the future demand for recycling, reuse, and repurposing of end-of-life EV batteries. Additionally, tax credits, EV rebate programs, and the financial capacity of households will influence the number of EV purchases, thereby further impacting the demand for EV battery recycling.

Alam, Lamia [Idaho National Laboratory (INL), Idah↗
DOE OSTI2021

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

Abstract Background Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. Results We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. Conclusions Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

How AI Predicts the Untrained and Unseen

Focus Area: Model predictability improvements (Primary); Data optimization (secondary); Data complexity insights (secondary). The Scientific Challenge: If we believe that a future under extreme conditions will look very differently from today, we can likely agree that ML/AI models trained on past and present datasets will not be adequate to make reliable predictions into the future. This is true for water cycling, as well as biogeochemistry and other Earth system components and behaviors. Additionally, ML/AI models are inherently non-physical. Despite the flourishing success of ML/AI in many applications, such as computer vision, natural language process, and gaming, even the most sophisticated AI models don’t understand the very basic physical laws. Therefore, a natural question is: Can we trust ML/AI based predictions of Earth system behaviors that are fundamentally driven by physical laws? So, are physics models with meticulous process representation a better choice? Not exactly. Physical models, when firmly rooted in first principles, work great at predicting behaviors of systems with a well-defined set of boundary conditions and variables. However, as a complex system, the number of parameters and the degree of complexity and dynamics in processes, coupling, and scale dependent emergent behaviors make the Earth system behaviors very challenging to predict with physical models composed of deterministic laws. In addition, due to the lack of fundamental understandings, physical models often implement empirical correlations derived from observations with biases from locality of data generation. Because correlation is not necessarily causation or comply with first principles, scaling of model predictions beyond locality is often invalid. Beyond the limitation of models, physics or AI, our knowledge of the Earth system is limited by the lack of observational technologies and resources. Insufficient data density, dimensionality and diversity only offer a sliced (or projected) view of the Earth system, e.g. Plato’s Cave analogy, limiting our capability to better understand and represent fundamental processes in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

IER 498: Godiva-IV CAAS benchmark [Slides]

This presentation discusses the benchmark of the IER 498: Godiva-IV criticality accident alarm system (CAAS). It details the goal of the project which is to create a CAAS benchmark capability for Godiva-IV in order to create a shielding benchmark for NCSP software and data, to add geometrically diverse benchmark/benchmarks to the ICSBEP Handbook, to enable more precise measurements at NCERC, and to help assure CAAS performance is as-stated. It also states that work was completed on CED-1 in 2019 and that future work includes the completion of CED-2 in 2020.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Pull Force Evaluation of CCS Insulated End Caps

Insulated end caps installed on DC pins of Combined Charging System (CCS) inlets have been identified as potential debris sources within electric vehicle supply equipment (EVSE) connectors, increasing the risk of electric shock and fire hazards. Although standards such as IEC 62196-1:2022 specify mechanical pull-force requirements for these end caps, it remains unclear whether these requirements provide adequate robustness under real-world conditions. To address this concern, the National Charging Experience (ChargeX) Consortium's Hardware Task Force conducted evaluations of insulated end caps used in OEM CCS inlets. This study assesses the performance of insulated end caps used in OEM CCS inlets, specifically those installed on DC pins, using the procedures defined in IEC 62196-1:2022 (Section Sign) 26.7 and SAE J3400, supplemented by additional experimental conditioning. To ensure relevance to real-world conditions, NLR collaborated with charging network operators (CNOs) to guide the selection of charging inlet samples. Material analyses of the insulated end cap samples were conducted to confirm that the tested materials reflected the types and properties commonly observed in the field. The selected samples underwent temperature and humidity conditioning followed by pull-force testing to evaluate the end-cap integrity. Although SAE J3400 inlets were not directly tested due to limited diversity in available field data, the underlying end-cap principles between CCS and SAE J3400 are comparable, allowing the study's insights to be relevant to both technologies. Overall, this study provides a structured evaluation framework to inform potential refinements to mechanical pull-force requirements in charging standards.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗
DOE OSTI2016

A Keck adaptive optics survey of a representative sample of gravitationally lensed star-forming galaxies: High spatial resolution studies of kinematics and metallicity gradients

We discuss spatially resolved emission line spectroscopy secured for a total sample of 15 gravitationally lensed star-forming galaxies at a mean redshift of z≃2 based on Keck laser-assisted adaptive optics observations undertaken with the recently improved OSIRIS integral field unit (IFU) spectrograph. By exploiting gravitationally lensed sources drawn primarily from the CASSOWARY survey, we sample these sub-L{sup ∗} galaxies with source-plane resolutions of a few hundred parsecs ensuring well-sampled 2D velocity data and resolved variations in the gas-phase metallicity. Such high spatial resolution data offer a critical check on the structural properties of larger samples derived with coarser sampling using multiple-IFU instruments. We demonstrate how kinematic complexities essential to understanding the maturity of an early star-forming galaxy can often only be revealed with better sampled data. Although we include four sources from our earlier work, the present study provides a more representative sample unbiased with respect to emission line strength. Contrary to earlier suggestions, our data indicate a more diverse range of kinematic and metal gradient behavior inconsistent with a simple picture of well-ordered rotation developing concurrently with established steep metal gradients in all but merging systems. Comparing our observations with the predictions of hydrodynamical simulations suggests that gas and metals have been mixed by outflows or other strong feedback processes, flattening the metal gradients in early star-forming galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Synthesizing Stellar Populations in South Pole Telescope Galaxy Clusters. I. Ages of Quiescent Member Galaxies at 0.3 < $\textit{z}$ < 1.4

Using stellar population synthesis models to infer star formation histories (SFHs), we analyze photometry and spectroscopy of a large sample of quiescent galaxies that are members of Sunyaev–Zel'dovich (SZ)-selected galaxy clusters across a wide range of redshifts. We calculate stellar masses and mass-weighted ages for 837 quiescent cluster members at 0.3 < $\textit{z}$ < 1.4 using rest-frame optical spectra and the Python-based Prospector framework, from 61 clusters in the SPT-GMOS Spectroscopic Survey (0.3 < $\textit{z}$ < 0.9) and three clusters in the SPT Hi-z cluster sample (1.25 < $\textit{z}$ < 1.4). We analyze spectra of subpopulations divided into bins of redshift, stellar mass, cluster mass, and velocity-radius phase-space location, as well as by creating composite spectra of quiescent member galaxies. We find that quiescent galaxies in our data set sample a diversity of SFHs, with a median formation redshift (corresponding to the lookback time from the redshift of observation to when a galaxy forms 50% of its mass, $t_{50}$) of $\textit{z}$ = 2.8 ± 0.5, which is similar to or marginally higher than that of massive quiescent field and cluster galaxy studies. We also report median age–stellar mass relations for the full sample (age of the universe at $t_{50}$ (Gyr) = 2.52 (±0.04)–1.66 (±0.12) log$_{10}(M/10^{11}M_⊙$)) and recover downsizing trends across stellar mass; we find that massive galaxies in our cluster sample form on aggregate ~0.75 Gyr earlier than lower-mass galaxies. We also find marginally steeper age–mass relations at high redshifts, and report a bigger difference in formation redshifts across stellar mass for fixed environment, relative to formation redshifts across environment for fixed stellar mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Quantifying Annual Industrial Locomotive Energy Consumption in the United States

While US Class 1 railroad locomotive rosters and annual fuel consumption are well-documented, considerably less is known regarding the overall energy consumption of operations involving industrial locomotives. To determine the energy savings potential of this rail operating sector, the objective of this research is to develop an inventory of US industrial locomotives and a baseline estimate of their annual energy consumption. Creating an industrial locomotives roster from public data is challenging given their diverse ownership by shippers or leasing companies, and operating locales largely out of public view. By cross-referencing public data on locomotive reporting marks, serial numbers, online images and aerial images, the project team confirmed the age, model and horsepower of over one thousand industrial locomotives. Estimating energy consumption is complicated by the variability in industrial locomotive types and power ratings, and extreme differences in duty cycles and utilization. Given these limitations, using quantified case study examples and adjustments to standard EPA line-haul and switching duty cycles, bounds on the magnitude of annual US industrial locomotive energy consumption were estimated.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1973

To evaluate ERTS-1 data for the usefulness as a geological sensor in the diverse geological terranes of New York State

The author has identified the following significant results. The straight NNE-trending escarpment that marks the easternmost extent of the Catskill Mountains appears, from ERTS-1 imagery (1079-15124) to be related to a set of parallel topographic lineaments which occur over a distance of 40 km to the west. The October 11 imagery of the Adirondacks (1080-15174) displays the pre-Paleozoic erosion surface along the western and northern margin of the Adirondack Mountains dome. The northern portion of this paleoplain is terminated to the southeast by an escarpment following an ENE topographic linear to produce a pseudo-cuesta. The snow covered terrain in the Mohawk Valley between Albany and Rome (1170-15182 and 1169-15123) displays with sculptural clarity a drumlin field having a cloud-free area of about 2600 sq km; glacial flow directions can be plotted readily because the stoss and lee sides of the drumlins can be distinguished. In the imagery of summer and fall, agricultural patterns obscured the detail which is visible in the winter imagery.

Isachsen, Y. W.↗
NASA NTRS1980

Western Regional Remote Sensing Conference Proceedings, 1979

Remote sensing users from the 14 western states explained their diverse applications of LANDSAT data, discussed operational goals, and exchanged problems and solutions. In addition, conference participants stressed the need for increased cooperation among state and local governments, private industry, and universities to aid NASA's objective of transferring to user agencies the ability to operationally use remote sensing technology for resource and environmental quality management.

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