Search NASA⌕ Search

SEARCH · Search NASA

Results for “Knowledge Discovery”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Mesorhizobium japonicum quorum sensing circuit that involves three linked genes and an unusual acyl-homoserine lactone signal

ABSTRACT Members of the genus Mesorhizobium, which are core components of the rhizosphere and specific symbionts of legume plants, possess genes for acyl-homoserine lactone (AHL) quorum sensing (QS). Here we show Mesorhizobium japonicum MAFF 303099 (formerly M. loti ) synthesizes and responds to N -[(2 E , 4 E )-2,4-dodecadienoyl] homoserine lactone (2 E, 4 E- C 12:2 -HSL). We show that the 2 E, 4 E- C 12:2 -HSL QS circuit involves one of four luxR-luxI -type genes found in the sequenced genome of MAFF 303099. We refer to this circuit, which appears to be conserved among Mesorhizobium species, as R1-I1. We show that two other Mesorhizobium strains also produce 2 E, 4 E- C 12:2 -HSL. The 2 E, 4 E- C 12:2 -HSL is unique among known AHLs in its arrangement of two trans double bonds. The R1 response to 2 E, 4 E- C 12:2 -HSL is extremely selective in comparison with other LuxR homologs, and the trans double bonds appear critical for R1 signal recognition. Most well-studied LuxI-like proteins use S -adenosylmethionine and an acyl-acyl carrier protein as substrates for synthesis of AHLs. Others that form a subgroup of LuxI-type proteins use acyl-coenzyme A substrates rather than acyl-acyl carrier proteins. I1 clusters with the acyl-coenzyme A-type AHL synthases. We show that a gene linked to the I1 AHL synthase is involved in the production of the QS signal. The discovery of the unique I1 product enforces the view that further study of acyl-coenzyme A-dependent LuxI homologs will expand our knowledge of AHL diversity. The involvement of an additional enzyme in AHL generation leads us to consider this system a three-component QS circuit. IMPORTANCE We report a Mesorhizobium japonicum quorum sensing (QS) system involving a novel acyl-homoserine lactone (AHL) signal. This system is known to be involved in root nodule symbiosis with host plants. The chemistry of the newly described QS signal indicated that there may be a dedicated cellular enzyme involved in its synthesis in addition to the types known for production of other AHLs. Indeed, we report that an additional gene is required for synthesis of the unique signal, and we propose that this is a three-component QS circuit as opposed to the canonical two-component AHL QS circuits. The signaling system is exquisitely selective. The selectivity may be important when this species resides in the complex microbial communities around host plants and may make this system useful in various synthetic biology applications of QS circuits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7 th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1 st to 4 th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8 th ARDD meeting that is scheduled for the 31 st of August to 3 rd of September, 2021, at Columbia University, USA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

On the provenance of GEMS, a quarter century post discovery

The provenance of GEMS (glass with embedded metal and sulfides) in cometary type interplanetary dust particles is investigated using analytical scanning transmission electron microscopy and secondary ion mass spectrometry. We review the current state of knowledge and closely examine the densities, elemental compositions and distributions, iron oxidation states, and isotopic compositions of a subset of GEMS in chondritic porous interplanetary dust. We find that GEMS are underdense with estimated densities that are 35–65% of compositionally equivalent crystalline aggregates. GEMS low densities result in a lower contribution to the bulk compositions of IDPs than has been assumed based on their volume fraction. We also find that element/Si ratios, assumed to be primary (indigenous), are instead perturbed by contamination and secondary alteration, including pulse heating during atmospheric entry. Fe in pyrrhotite inclusions was oxidized and Mg, S, Ca, and Fe were depleted relative to lithophile Al and Si, resulting in reduction in element/Si ratios. Because they trap outgassing elements, Fe-rich oxide rims that formed on the surface of GEMS are serendipitous “witness plates” to the changes in composition that accompany atmospheric entry. As a result of alteration, GEMS elemental compositions cannot reliably inform about their provenance. Except for highly anomalous oxygen isotope ratios measured in some large GEMS grains that indicate a contribution from circumstellar dust, oxygen isotope compositions are generally poor indicators of provenance. Prior work indicates that most GEMS fall close to the terrestrial oxygen isotope composition, which, however, does not exclude a presolar interstellar origin. Nitrogen isotopic compositions are more diagnostic. Elevated 15 N/ 14 N ratios indicate that GEMS accreted in conjunction with formation of organic matter by ion–molecule reactions in a cold (<50 K) presolar environment like the extreme outer nebula or interstellar medium. Considering all observations, we conclude that GEMS are most likely processed interstellar silicates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ab Initio Prediction of Ultra‐Wide Band Gap B x Al 1− x N Materials

Abstract Ultra‐wide bandgap (UWBG) materials are poised to play an important role in the future of power electronics. Devices made from UWBG materials are expected to operate at higher voltages, frequencies, and temperatures than current silicon and silicon‐carbide‐based devices and can even lead to significant miniaturization of such devices. In the UWBG field, aluminum nitride and boron nitride have attracted great interest; however, the B x Al 1− x N alloys are much less studied. In this work, using first‐principles simulations combining density‐functional theory and the cluster expansion method, the crystal structure of B x Al 1− x N alloys is predicted. Seventeen ground state structures of B x Al 1− x N with formation energies between 0.11 and 0.25 eV atom ‐1 are found. All of these structures are found to be dynamically stable. The B x Al 1− x N structures are found to have predominantly a tetrahedral bonding environment; however, some structures exhibit sp 2 bonds similar to hexagonal BN. This work expands knowledge of the structures, energies, and bonding in B x Al 1− x N which aids their synthesis, the innovation of lateral or vertical devices, and discovery of compatible dielectric and Ohmic contact materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Breaking the Ice: A Review of Phages in Polar Ecosystems

Bacteriophages, or phages, are viruses that infect and replicate within bacterial hosts, playing a significant role in regulating microbial populations and ecosystem dynamics. However, phages from extreme environments such as polar regions remain relatively understudied due to challenges such as restricted ecosystem access and low biomass. In this study, understanding the diversity, structure, and functions of polar phages is crucial for advancing our knowledge of the microbial ecology and biogeochemistry of these environments. In this review, we will explore the current state of knowledge on phages from the Arctic and Antarctic, focusing on insights gained from -omic studies, phage isolation, and virus-like particle abundance data. Metagenomic studies of polar environments have revealed a high diversity of phages with unique genetic characteristics, providing insights into their evolutionary and ecological roles. Phage isolation studies have identified novel phage–host interactions and contributed to the discovery of new phage species. Virus-like particle abundance and lysis rate data, on the other hand, have highlighted the importance of phages in regulating bacterial populations and nutrient cycling in polar environments. Overall, this review aims to provide a comprehensive overview of the current state of knowledge about polar phages, and by synthesizing these different sources of information, we can better understand the diversity, dynamics, and functions of polar phages in the context of ongoing climate change, which will help to predict how polar ecosystems and residing phages may respond to future environmental perturbations.

09 BIOMASS FUELS↗
DOE OSTI2026

RCSB protein data Bank: Next‐generation advanced search for exploration of experimental structures and computed structure models

Abstract The Protein Data Bank (PDB), established in 1971, is the primary global, open‐access archive for experimentally determined 3D macromolecular structures (proteins, RNA, DNA). The research‐focused RCSB.org web‐portal provides access to these data alongside more than one million machine‐learning‐predicted structure models, greatly expanding the available structural landscape. Rapid growth of both experimental and computational structures has increased the need for powerful yet accessible search tools that serve a broad and diverse scientific community. Herein, we describe a redesigned RCSB Protein Data Bank RCSB.org Advanced Search capability that supports intuitive discovery of 3D structures through a unified interface. This interface integrates annotation‐, sequence‐, and 3D structure‐based searches, embeds an interactive 3D viewer, and incorporates curated biological knowledge, such as catalytic site definitions from Mechanism and Catalytic Site Atlas and ligand‐guided structural motifs, for constructing geometry‐driven queries. A new Chemical Search tool allows definition of chemical queries via an integrated drawing tool or standard identifiers, seamlessly combining them with annotation filters. By allowing query definition directly within spatial and chemical contexts, these search interfaces reduce the need for detailed knowledge of residue numbering, chain identifiers, or external cheminformatics software. This capability enables efficient exploration of structures, chemical diversity, and structure–function relationships across all life domains. The redesigned interfaces can be accessed directly at rcsb.org/search/advanced for Advanced Search and rcsb.org/search/chemical for Chemical Search.

Rose, Yana [Research Collaboratory for Structural ↗
DOE OSTI2026

Mutation of active site glutamate in serine hydroxymethyltransferase allows trapping a reactive intermediate: a combined neutron and X-ray crystallography study

Serine hydroxymethyltransferase (SHMT) is a pyridoxal-5′-phosphate (PLP) dependent enzyme that catalyzes a chemical transformation essential for the one-carbon (1C) metabolism. SHMT reversibly converts L-Ser into Gly and transfers a 1C unit to tetrahydrofolate (THF) to give 5,10-methylene-THF (5,10-MTHF). 5,10-MTHF, a 1C-unit donor, plays a crucial role in the downstream biomolecular syntheses required for the cell homeostasis and proliferation. SHMT is a prominent target for the drug discovery to battle bacterial and parasitic infections, and to treat various types of cancer. SHMT-catalyzed chemistry is governed by the general acid-base catalysis. Knowledge of the catalytic mechanism can aid drug design but can only be achieved when the atomic details of each reaction step are mapped, including accurate determination of hydrogen atom positions. Here we utilized the inactive E53Q mutant of Thermus thermophilus ( Tth ) SHMT to directly determine protonation states with room-temperature neutron crystallography and to capture a reactive intermediate containing the PLP-L-Ser external aldimine and THF in the enzyme active site. We observed protonation of the Schiff base nitrogen (N SB ) in the PLP internal aldimine but no change in the protonation states of other ionizable PLP groups and active site residues compared to wild-type Tth SHMT. X-ray structural analysis of the ternary intermediate complex E53Q-Ser-THF that eluded previous structural characterization shows the strategic positioning of the E53Q side chain in close proximity to the external aldimine and THF and reinforces the proposed role for E53 as the driver of proton transfer events along the reaction pathway.

Drago, Victoria N. [Oak Ridge National Laboratory ↗
DOE OSTI2020

The Link Between the Ecology of the Prokaryotic Rare Biosphere and Its Biotechnological Potential

Current research on the prokaryotic low abundance taxa, the prokaryotic rare biosphere, is growing, leading to a greater understanding of the mechanisms underlying organismal rarity and its relevance in ecology. From this emerging knowledge it is possible to envision innovative approaches in biotechnology applicable to several sectors. Bioremediation and bioprospecting are two of the most promising areas where such approaches could find feasible implementation, involving possible new solutions to the decontamination of polluted sites and to the discovery of novel gene variants and pathways based on the attributes of rare microbial communities. Bioremediation can be improved through the realization that diverse rare species can grow abundant and degrade different pollutants or possibly transfer useful genes. Further, most of the prokaryotic diversity found in virtually all environments belongs in the rare biosphere and remains uncultivatable, suggesting great bioprospecting potential within this vast and understudied genetic pool. This Mini Review argues that knowledge of the ecophysiology of rare prokaryotes can aid the development of future, efficient biotechnology-based processes, products and services. However, this promise may only be fulfilled through improvements in (and optimal blending of) advanced microbial culturing and physiology, metagenomics, genome annotation and editing, and synthetic biology, to name a few areas of relevance. In the future, it will be important to understand how activity profiles relate with abundance, as some rare taxa can remain rare and increase activity, whereas other taxa can grow abundant. The metabolic mechanisms behind those patterns can be useful in designing biotechnological processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Major impacts of widespread structural variation on sorghum

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype–phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

TPCpp-10M: Simulated proton-proton collisions in a time projection chamber for AI foundation models

Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field is often limited by the lack of openly available large scale datasets, as well as standardized evaluation tasks and metrics. Furthermore, the specialized knowledge and software typically required to process particle physics data pose significant barriers to interdisciplinary collaboration with the broader machine learning community. This work introduces a large, openly accessible dataset of 10 million simulated proton-proton collisions, designed to support self-supervised training of foundation models. To facilitate ease of use, the dataset is provided in a common NumPy format. In addition, it includes 70,000 labeled examples spanning three well defined downstream tasks: track finding, particle identification, and noise tagging, to enable systematic evaluation of the foundation model's adaptability. The simulated data are generated using the Pythia Monte Carlo event generator at a center of mass energy of $\sqrt{s}$ = 200 GeV and processed with Geant4 to include realistic detector conditions and signal emulation in the sPHENIX Time Projection Chamber at the Relativistic Heavy Ion Collider, located at Brookhaven National Laboratory. This dataset resource establishes a common ground for interdisciplinary research, enabling machine learning scientists and physicists alike to explore scaling behaviors, assess transferability, and accelerate progress toward foundation models in nuclear and high energy physics. The complete simulation and reconstruction chain is reproducible with the sPHENIX software stack. All data and code locations are provided under Data Accessibility.

Data Analysis, Statistics and Probability (physics↗
DOE OSTI2026

Neural entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws

We propose a neural entropy-stable conservative flux form neural network (NESCFN) for learning hyperbolic conservation laws and their associated entropy functions directly from solution trajectories, without requiring any predefined numerical discretization. While recent neural network architectures have successfully integrated classical numerical principles into learned models, most rely on prior knowledge of the governing equations or assume a fixed discretization. Our approach removes this dependency by embedding entropy-stable design principles into the learning process itself, enabling the discovery of physically consistent dynamics in a fully data-driven setting. By jointly learning both the flux function and a corresponding entropy, NESCFN promotes conservation and entropy dissipation, which is critical for long-term stability and fidelity in the system of hyperbolic conservation laws. Furthermore, numerical results demonstrate that the method achieves stability and conservation over extended time horizons and accurately captures shock propagation speeds, even without oracle access to future-time solution profiles in the training data.

Conservative flux form↗
DOE OSTI2023

Neutrino self-interactions: A white paper

Neutrinos are the Standard Model (SM) particles which we understand the least, often due to how weakly they interact with the other SM particles. Beyond this, very little is known about interactions among the neutrinos, i.e., their self-interactions. The SM predicts neutrino self-interactions at a level beyond any current experimental capabilities, leaving open the possibility for beyond-the-SM interactions across many energy scales. In this white paper, we review the current knowledge of neutrino self-interactions from a vast array of probes, from cosmology, to astrophysics, to the laboratory. Furthermore, we also discuss theoretical motivations for such self-interactions, including neutrino masses and possible connections to dark matter. Looking forward, we discuss the capabilities of searches in the next generation and beyond, highlighting the possibility of future discovery of this beyond-the-SM physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Automated descriptor selection, volcano curve generation, and active site determination using the DescMAP software

The material space for catalyst discovery is expansive. Volcano curves are traditionally employed to provide physical insights into optimal catalyst characteristics for new material selection. Their generation lies on a single descriptor picked using expert knowledge. Here we present DescMAP, a Python-based software, to automate the selection of descriptors, the generation of volcano maps, and the identification of active sites for structure-sensitive reactions. Here, we consider traditional energy-based and geometric descriptors for structure-sensitive reactions. DescMAP is integrated with the Virtual Kinetic Laboratory (VLab) to provide multiple functionalities. It inputs spreadsheets or template files for flexibility and outputs interactive graphs for post-processing. We demonstrate its features using the non-oxidative dehydrogenation of ethane to ethylene over (111) closed-packed surfaces and the methane total oxidation over various Pt facets. It can be easily applied to other complex chemistries and achieves quick screening of potential catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ontologizing health systems data at scale: making translational discovery a reality

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Selective Enrichment Coupled with Proteomics to Identify S-Acylated Plasma Membrane Proteins in Arabidopsis

Protein S-acylation, predominately in the form of palmitoylation, is a reversible lipid post-translational modification (PTM) on cysteines that plays important roles in protein localization, trafficking, activity, and complex assembly. The functions and regulatory mechanisms of Sacylation have been extensively studied in mammals, owing to remarkable development of the high-resolution proteomics and the discovery of the S-acylation-related enzymes. However, the advance of S-acylation studies in plants lags farther behind than that in mammals, mainly due to the lack of knowledge about proteins responsible for this process, such as protein acyltransferases (PATs) and their substrates. In this article, a systematic protocol to study global S-acylation in Arabidopsis seedlings is described. The procedures are presented in detail, including preparation of Arabidopsis seedlings, enrichment of plasma membrane (PM) proteins, followed by enrichment of S-acylated proteins/peptides based on the acyl-biotin exchange (ABE) method, and large-scale identification of S-acylated proteins/peptides via mass spectrometry. This approach enables researchers to study S-acylation of PM proteins in plants in a systematic and straightforward way. Basic protocol 1: Preparation of Arabidopsis seedling materials Basic protocol 2: Isolation and enrichment of plasma membrane proteins Support protocol 1: Determination of protein concentration using BCA assay Basic Protocol 3: Enrichment of S-acylated proteins by ABE method Support protocol 2: Protein precipitation by methanol/chloroform method Basic Protocol 4: Trypsin digestion and proteomic analysis Alternate protocol 1: Pre-resin digestion and peptide level enrichment.

S-acylation, palmitoylation, plasma membrane prote↗