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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Opening doors to physical sample tracking and attribution in Earth and environmental sciences

Physical samples and their associated data and metadata underpin scientific discoveries across disciplines and can enable new science when appropriately archived. However, there are significant gaps in current practices and infrastructure that prevent accurate provenance tracking, reproducibility, and attribution. For most samples, descriptive metadata are often sparse, inaccessible, or absent. Samples and associated data and metadata may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkage or provenance tracking as new information is generated over time. The Earth Science Information Partners (ESIP) Physical Samples Curation Cluster has therefore developed guidance for scientific authors on ‘Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, gathering community feedback, and assessing real-world examples. We identified improvements needed to enable authors to efficiently cite and link Earth science samples and related data, and track their use. Our goal is to help improve discoverability, interoperability, and reuse of physical samples, and associated data and metadata. Though primarily focused on the needs of Earth and environmental sciences, these guidelines are broadly applicable.

58 GEOSCIENCES↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2015

Gateways to the FANTOM5 promoter level mammalian expression atlas

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). In conclusion, this resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Small ncRNA Expression-Profiling of Blood from Hemophilia A Patients Identifies miR-1246 as a Potential Regulator of Factor 8 Gene

Hemophilia A (HA) is a bleeding disorder caused by deficiency of functional plasma clotting factor VIII (FVIII). Genetic mutations in the gene encoding FVIII (F8) have been extensively studied. Over a thousand different mutations have been reported in the F8 gene. These span a diverse range of mutation types, namely, missense, splice-site, deletions of single and multiple exons, inversions, etc. There is nonetheless evidence that other molecular mechanisms, in addition to mutations in the gene encoding the FVIII protein, may be involved in the pathobiology of HA. In this study, global small ncRNA expression profiling analysis of whole blood from HA patients, and controls, was performed using high-throughput ncRNA microarrays. Patients were further sub-divided into those that developed neutralizing-anti-FVIII antibodies (inhibitors) and those that did not. Selected differentially expressed ncRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. We identified several ncRNAs, and among them hsa-miR1246 was significantly up-regulated in HA patients. In addition, miR-1246 showed a six-fold higher expression in HA patients without inhibitors. We have identified an miR-1246 target site in the noncoding region of F8 mRNA and were able to confirm the suppressory role of hsa-miR-1246 on F8 expression in a stable lymphoblastoid cell line expressing FVIII. These findings suggest several testable hypotheses vis-à-vis the role of nc-RNAs in the regulation of F8 expression. These hypotheses have not been exhaustively tested in this study as they require carefully curated clinical samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Apollo Next Generation Sample Analysis (ANGSA): an Apollo Participating Scientist Program to Prepare the Lunar Sample Community for Artemis

As a first step in preparing for the return of samples from the Moon by the Artemis Program, NASA initiated the Apollo Next Generation Sample Analysis Program (ANGSA). ANGSA was designed to function as a low-cost sample return mission and involved the curation and analysis of samples previously returned by the Apollo 17 mission that remained unopened or stored under unique conditions for 50 years. These samples include the lower portion of a double drive tube previously sealed on the lunar surface, the upper portion of that drive tube that had remained unopened, and a variety of Apollo 17 samples that had remained stored at -27 °C for approximately 50 years. ANGSA constitutes the first preliminary examination phase of a lunar “sample return mission” in over 50 years. It also mimics that same phase of an Artemis surface exploration mission, its design included placing samples within the context of local and regional geology through new orbital observations collected since Apollo and additional new “boots-on-the-ground” observations, data synthesis, and interpretations provided by Apollo 17 astronaut Harrison Schmitt. ANGSA used new curation techniques to prepare, document, and allocate these new lunar samples, developed new tools to open and extract gases from their containers, and applied new analytical instrumentation previously unavailable during the Apollo Program to reveal new information about these samples. Most of the 90 scientists, engineers, and curators involved in this mission were not alive during the Apollo Program, and it had been 30 years since the last Apollo core sample was processed in the Apollo curation facility at NASA JSC. There are many firsts associated with ANGSA that have direct relevance to Artemis. ANGSA is the first to open a core sample previously sealed on the surface of the Moon, the first to extract and analyze lunar gases collected in situ, the first to examine a core that penetrated a lunar landslide deposit, and the first to process pristine Apollo samples in a glovebox at -20 °C. All the ANGSA activities have helped to prepare the Artemis generation for what is to come. The timing of this program, the composition of the team, and the preservation of unopened Apollo samples facilitated this generational handoff from Apollo to Artemis that sets up Artemis and the lunar sample science community for additional successes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology

We present a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS 2 ) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-curation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS 1 -based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS 2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-curation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

OpenMSI Arrayed Analysis Tools (OMAAT) v2.0

Mass spectrometry (MS) is an analytical technique that enables all chemical species within a complex mixture to be resolved and identified based on their mass:charge ratio. MS is an increasingly important tool in life science research and development because it can resolve or separate small molecules, peptides, lipids, proteins, biopolymers and fragments of all of these structures. Unfortunately, the use of MS has been limited for lack of software tools to visualize, manipulate, store and transfer MS data. Ben Bowen, Oliver Ruebel and colleagues made a huge advance on the resolution of these limitations with the invention of "OpenMSI" (#2013-004), a computational method that makes the handling of these very large files (up to 50 Tb) much easier, especially for scientists with limited background in bioinformatics or sophisticated software applications of the type needed to handle such data files. With the OpenMSI Arrayed Analysis Tool (OMAAT, #2016-188) invention, the authors take MS data analysis one step further by providing tolls for automatic sample position optimization and ion selection. Even though sample deposition technologies have improved greatly, there is always the chance of encountering outliers in a predefined roster, especially in very large sample sets. Manual curation of the data would be extremely time consuming, so the inventors have included an algorithm that automatically finds the outliers. OMAAT is written in Python with accompanying Jupyter (formerly iPython) notebook and is fully integrated with OpenMSI.

Bowen, Benjamin↗
DOE OSTI2025

An evaporite sequence from ancient brine recorded in Bennu samples

Evaporation or freezing of water-rich fluids with dilute concentrations of dissolved salts can produce brines, as observed in closed basins on Earth and detected by remote sensing on icy bodies in the outer Solar System. The mineralogical evolution of these brines is well understood in regard to terrestrial environments, but poorly constrained for extraterrestrial systems owing to a lack of direct sampling. Here we report the occurrence of salt minerals in samples of the asteroid (101955) Bennu returned by the OSIRIS-REx mission. These include sodium-bearing phosphates and sodium-rich carbonates, sulfates, chlorides and fluorides formed during evaporation of a late-stage brine that existed early in the history of Bennu’s parent body. Discovery of diverse salts would not be possible without mission sample return and careful curation and storage, because these decompose with prolonged exposure to Earth’s atmosphere. Similar brines probably still occur in the interior of icy bodies Ceres and Enceladus, as indicated by spectra or measurement of sodium carbonate on the surface or in plumes.

58 GEOSCIENCES↗
DOE OSTI2013

Assessing Performance and Tradeoffs of Bioforensic Signature Systems

Chemical and biological forensic programs rely heavily on laboratory measurements to determine how a threat agent may have been produced. In addition to laboratory analyses, it may also be useful to identify institutions where the same threat agent has been produced by the same or a very similar process, since the producer of the agent may have learned methods at a university or similar institution. We developed a Bayesian network framework that combines the results of laboratory measurements with evidence from scientific literature to probabilistically rank institutions that have published papers on the agent of interest. As an example, we consider a network of three laboratory assays that are used to estimate the probabilities that a forensic sample of Yersinia pestis was produced using one of three culture media. We then apply techniques from multi-attribute decision science to assess and compare the performance of the various implementations of the Bayesian network in terms of three attributes: fidelity, document curation intensity, and consumption of the forensic sample. The mathematical approach we use to compare the various implementations is generalizable to the evaluation of other signature systems.

Watkins, Daniel M.↗
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 OSTI2025

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

FY 2017 Status Report Nuclear Fuels and Materials Library Including Leve 3 Milestone: Report on the Status of Legacy Samples for the NFML

The Nuclear Fuels and Materials Library (NFML), which is owned by DOE-NE and curated by the NSUF, is a collection of specialized information and nuclear fuel and material samples from past and ongoing irradiation test campaigns, as well as real-world components retrieved from decommissioned power reactors, and donations from other sources. The NFML can be accessed through a web portal at the NSUF web page NSUF.INL.gov or directly at https://nsuf-infrastructure.inl.gov/. This document is intended to provide a status on the NFML for FY 2017, however it includes considerable historical information pertinent to FY 2017 activities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Interactive volumetric segmentation for textile micro-tomography data using wavelets and nonlocal means

This work addresses segmentation of volumetric images of woven carbon fiber textiles from micro-tomography data. We propose a semi-supervised algorithm to classify carbon fibers that requires sparse input as opposed to completely labeled images. The main contributions are: (a) design of effective discriminative classifiers, for three-dimensional textile samples, trained on wavelet features for segmentation; (b) coupling of previous step with nonlocal means as simple, efficient alternative to the Potts model; and (c) demonstration of reuse of classifier to diverse samples containing similar content. We evaluate our work by curating test sets of voxels in the absence of a complete ground truth mask. The algorithm obtains an average 0.95 F1 score on test sets and average F1 score of 0.93 on new samples. Finally, we conclude with discussion of failure cases and propose future directions toward analysis of spatiotemporal high-resolution micro-tomography images.

3D image processing↗
DOE OSTI2020

Planet Microbe: a platform for marine microbiology to discover and analyze interconnected ‘omics and environmental data

In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and on-going oceanographic sequencing efforts. In Planet Microbe, each ‘omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Pu(IV) quantification via visible–near-infrared absorption spectroscopy: tackling interferences using D-optimal design and partial least squares

Here, this study presents a novel analytical approach for quantifying Pu(IV) in glove box environments using fiber-optic-based visible–near-infrared absorption spectroscopy in combination with partial least squares regression (PLSR) and design of experiments. The method addresses significant challenges posed by overlapping spectral features arising from Nd(III), which is a common fission product impurity, and the speciation variability of Pu(IV) nitrato complexes in HNO 3 concentrations ranging from 2.5 to 11 M. A curated training set consisting of data from 20 samples was developed via D-optimal design to enable robust PLSR model calibration for Pu(IV) using the near-infrared band near 1050 nm. The training set was acquired from samples in cuvettes with a 1-cm path length and was used to build the PLSR model. The robustness of the model was validated with data collected using a dip probe with a 1-cm path length and varying Pu(IV) concentrations. The strong performance of the model indicates good model transfer from cuvette to dip probe and highlights the potential for in situ measurements and online monitoring of reactions in a crystallization reactor vessel. The results demonstrate that this combined spectroscopic and chemometric approach can accurately and simultaneously quantify Pu(IV) and HNO 3 , thereby offering a promising tool for real-time monitoring in process environments.

Actinide↗
DOE OSTI2014

Communities of microbial eukaryotes in the mammalian gut within the context of environmental eukaryotic diversity

Eukaryotic microbes (protists) residing in the vertebrate gut influence host health and disease, but their diversity and distribution in healthy hosts is poorly understood. Protists found in the gut are typically considered parasites, but many are commensal and some are beneficial. Further, the hygiene hypothesis predicts that association with our co-evolved microbial symbionts may be important to overall health. It is therefore imperative that we understand the normal diversity of our eukaryotic gut microbiota to test for such effects and avoid eliminating commensal organisms. We assembled a dataset of healthy individuals from two populations, one with traditional, agrarian lifestyles and a second with modern, westernized lifestyles, and characterized the human eukaryotic microbiota via high-throughput sequencing. To place the human gut microbiota within a broader context our dataset also includes gut samples from diverse mammals and samples from other aquatic and terrestrial environments. We curated the SILVA ribosomal database to reflect current knowledge of eukaryotic taxonomy and employ it as a phylogenetic framework to compare eukaryotic diversity across environment. We show that adults from the non-western population harbor a diverse community of protists, and diversity in the human gut is comparable to that in other mammals. However, the eukaryotic microbiota of the western population appears depauperate. The distribution of symbionts found in mammals reflects both host phylogeny and diet. Eukaryotic microbiota in the gut are less diverse and more patchily distributed than bacteria. More broadly, we show that eukaryotic communities in the gut are less diverse than in aquatic and terrestrial habitats, and few taxa are shared across habitat types, and diversity patterns of eukaryotes are correlated with those observed for bacteria. These results outline the distribution and diversity of microbial eukaryotic communities in the mammalian gut and across environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Exploration of the Biosynthetic Potential of the Populus Microbiome

Natural products (NPs) isolated from bacteria have dramatically advanced human society, especially in medicine and agriculture. The rapidity and ease of genome sequencing have enabled bioinformatics-guided NP discovery and characterization. As a result, NP potential and diversity within a complex community, such as the microbiome of a plant, are rapidly expanding areas of scientific exploration. Here, we assess biosynthetic diversity in the Populus microbiome by analyzing both bacterial isolate genomes and metagenome samples. We utilize the fully sequenced genomes of isolates from the Populus root microbiome to characterize a subset of organisms for NP potential. The more than 3,400 individual gene clusters identified in 339 bacterial isolates, including 173 newly sequenced organisms, were diverse across NP types and distinct from known NP clusters. The ribosomally synthesized and posttranslationally modified peptides were both widespread and divergent from previously characterized molecules. Lactones and siderophores were prevalent in the genomes, suggesting a high level of communication and pressure to compete for resources. We then consider the overall bacterial diversity and NP variety of metagenome samples compared to the sequenced isolate collection and other plant microbiomes. The sequenced collection, curated to reflect the phylogenetic diversity of the Populus microbiome, also reflects the overall NP diversity trends seen in the metagenomic samples. In our paper, only about 1% of all clusters from sequenced isolates were positively matched to a previously characterized gene cluster, suggesting a great opportunity for the discovery of novel NPs involved in communication and control in the Populus root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗