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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Plant Summit 2019

The Plant Science Research Network organized the Plant Summit 2019, which took place February 10-13, 2019 at Biosphere 2 (Oracle, AZ). The Summit brought together plant scientists from many quarters, including stakeholders from academic institutions, government, nonprofits, and private industry with a broad range of experience in plant science research and education. Participants were guided through a facilitated workshop to review and assess the outcomes from previous PSRN workshops on cyberinfrastructure, postgraduate training, broadening participation, and future scenarios. An outcome of the Summit is the development of a report, “The Plant Science Decadal Vision (2020-2030): Reimagining the Potential of Plants for a Healthy Future.” The Decadal Vision frames societally vital, exciting and far-reaching research challenges as being necessary and deeply interwoven with human and technical resources. An Executive Summary of that report is provided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of Resources and Tools to Improve Oil Content and Quality in Pennycress (Final Report)

This is the final report for the project entitled "Development of Resources and Tools to Improve Oil Content and Quality in Pennycress". The project focused on three main aspects: 1) Investigate pennycress natural variation to identify candidate genes and biomarkers associated with oil accumulation and fatty acid composition. 2) Identify targets to improve oil content and composition. 3) Establish metabolic engineering targets and develop community resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Digital Biosurveillance for Zoonotic Disease Detection in Kenya

Infectious disease surveillance is crucial for early detection and situational awareness of disease outbreaks. Digital biosurveillance monitors large volumes of open-source data to flag potential health threats. This study investigates the potential of digital surveillance in the detection of the top five priority zoonotic diseases in Kenya: Rift Valley fever (RVF), anthrax, rabies, brucellosis, and trypanosomiasis. Open-source disease events reported between August 2016 and October 2020 were collected and key event-specific information was extracted using a newly developed disease event taxonomy. A total of 424 disease reports encompassing 55 unique events belonging to anthrax (43.6%), RVF (34.6%), and rabies (21.8%) were identified. Most events were first reported by news media (78.2%) followed by international health organizations (16.4%). News media reported the events 4.1 (±4.7) days faster than the official reports. There was a positive association between official reporting and RVF events (odds ratio (OR) 195.5, 95% confidence interval (CI); 24.01–4756.43, p < 0.001) and a negative association between official reporting and local media coverage of events (OR 0.03, 95% CI; 0.00–0.17, p = 0.030). This study highlights the usefulness of local news in the detection of potentially neglected zoonotic disease events and the importance of digital biosurveillance in resource-limited settings.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Rapid Prototyping of Biological Materials for In-Space Applications

The topics include: 1) Why is this technology needed? 2) In-Situ Fabrication and Repair (ISFR) and In-Situ Resource Utilization (ISRU); 3) Multi-Material Fabricator; 4) Medical Products; 5) Bioplotter; 6) Closing Remarks; and 7) Additional Information.

Frazier, Natalie↗
DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Center for Lignocellulose Structure and Formation (CLSF)

Lignocellulose is the carbon- and energy-rich material synthesized by plants when they make secondary cell walls, e.g. in woody tissues. Plants annually convert gigatons of atmospheric CO 2 into these complex and useful biomaterials that comprise over half of all biological carbon on Earth. This biological conversion helps to reduce atmospheric CO 2 that contributes to climate change while generating renewable plant cell walls that are used commercially on a massive scale in the paper, timber and textile industries. Recent technical developments open new possibilities for use of modified wood and cellulose fibers as large-scale alternatives to steel, plastics, and other nonrenewable materials with high carbon footprints and energy inputs, as well as for generation of biofuels and bio-hydrogen. Despite the utility of plant-based biomaterials, many physical and biological aspects of cell wall structure and formation remain obscure, and this limits the current scope for engineering these renewable resources for greater utility.

09 BIOMASS FUELS↗
NASA NTRS2001

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗
DOE OSTI2021

Vertical movement of soluble carbon and nutrients from biocrusts to subsurface mineral soils

Dryland ecosystems can be constrained by low soil fertility. Within drylands, the soil nutrient and organic carbon (C) cycling that does occur is often mediated by soil surface communities known as biological soil crusts (biocrusts), which cycle C and nutrients in the top ca. 0–2 cm of soil. However, the degree to which biocrusts are influencing soil fertility and biogeochemical cycling in deeper, subsurface mineral soils is unclear. The movement of dissolved resources from biocrusts to deeper soil layers in leachate may be one of the main mechanisms through which biocrust fertility is transferred downward towards deeper microbial communities and plant roots occurring within mineral soil. Here, in this study, we examined the role of biocrust leachate in contributing to subsurface nutrient and soluble C pools and subsurface microbial cycling. We collected biocrusts from three biocrust successional stages and explored resource pools in situ at multiple soil depths, while collecting leachate and measuring nutrient and organic C concentrations and metabolite composition from each successional stage in the laboratory. After four leachate collections, we conducted an incubation of mineral soil collected from below each biocrust successional stage to measure heterotrophic microbial CO 2 flux and biomass. Overall, our findings observed that the degree of nutrient and C connectivity between biocrusts and the sub-crust mineral soil depended on the biocrust successional stage and the element being considered, and the influence of biocrust successional stage on mineral soil CO 2 flux is likely related to long-term resource build up. Together, our results suggest that the influence of biocrust leachate on subsurface mineral soil is complex and context dependent, but, over longer time periods and at later successional stages, can have measurable effects on dryland soil biogeochemical cycling with feedbacks to resource availability and CO 2 flux.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a ‘living data resource.’ Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Low-level resource partitioning supports coexistence among functionally redundant bacteria during successional dynamics

Members of microbial communities can substantially overlap in substrate use. However, what enables functionally redundant microorganisms to coassemble or even stably coexist remains poorly understood. Here, we show that during unstable successional dynamics on complex, natural organic matter, functionally redundant bacteria can coexist by partitioning low-concentration substrates even though they compete for one simple, dominant substrate. We allowed ocean microbial communities to self-assemble on leachates of the brown seaweed Fucus vesiculosus and then analyzed the competition among 10 taxonomically diverse isolates representing two distinct stages of the succession. All, but two isolates, exhibited an average of 90% ± 6% pairwise overlap in resource use, and functional redundancy of isolates from the same assembly stage was higher than that from between assembly stages, leading us to construct a simpler four-isolate community with two isolates from each of the early and late stages. We found that, although the short-term dynamics of the four-isolate communities in F. vesiculosus leachate was dependent on initial isolate ratios, in the long term, the four isolates stably coexist in F. vesiculosus leachate, albeit with some strains at low abundance. We therefore explored the potential for nonredundant substrate use by genomic content analysis and RNA expression patterns. This analysis revealed that the four isolates mainly differed in peripheral metabolic pathways, such as the ability to degrade pyrimidine, leucine, and tyrosine, as well as aromatic substrates. These results highlight the importance of fine-scale differences in metabolic strategies for supporting the frequently observed coexistence of large numbers of rare organisms in natural microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Synthetic Biological Membrane

The ultimate goal of the Synthetic Biological Membrane project is to develop a new type of membrane (using FOST - Forward Osmosis Secondary Treatment) that will enable the waste water treatment system required on exploration missions to operate for extended periods while requiring no maintenance, and using only available resources. Because current water treatment systems have a lifetime of less than 1 year, extending membrane life will benefit exploration missions by reducing upmass and crew time requirements associated with maintenance and resupply/replacement of membranes. The project will use synthetic biology to engineer organisms that protect and replenish the membrane, and this new technology can be easily adapted for use in terrestrial waste water treatment plants.

Biomimetic membrane↗
NASA NTRSDate not supplied

Enabling Space Biology Knowledge Discovery Through Biospecimen Sharing: The NASA Biological Institutional Scientific Collection

NASA and international partners have conducted experiments in space to understand the biological impacts and address hazards to health. The resulting basic and applied science is imperative to enabling humanity to venture back to the Moon and then to Mars and beyond. Sending organisms into space is a costly endeavor. All biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (NBISC) to maximize the scientific return. The NASA Biological and Physical Sciences (BPS) Division has an ‘Open Science’ endeavor which includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, the Ames Life Sciences Data Archive, and NBISC. Its purpose is to integrate extensive data and biospecimen resources from spaceflight and/or ground-based analog experiments. NBISC biospecimens are collected and preserved according to well-established standard operating procedures to maintain scientific quality and are available on-request by the international scientific community. NBISC currently stores over 32,000 biospecimens from Shuttle, International Space Station, and ground-based space analog investigations. Tissue sharing has resulted in at least 33 publications since 2011 and 48 requests since 2016. Many requests for NBISC biospecimen come from first-time investigators who subsequently submit grants as the port-of-entry into the field of space biology. Some NBISC biospecimens have been awarded to NASA Genelab, who then generate various ‘Open Science’ -omics data sets on their platform for bioinformatics. Other NBISC biospecimen awards have led to multiple studies such as fecal microbiome analysis, DNA damage analysis using single-cell DNA sequencing, enzymatic-pathway identification involved in spaceflight muscle atrophy, and characterization of ocular morphological changes. Of note, NBISC has expanded to include a new Space Microbial Culture Collection (SMCC) for the collection, identification, documentation, long-term preservation, and distribution of space-related microbial isolates.

Ryan T. Scott↗
NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗
DOE OSTI2024

Long- and short-read sequencing methods discover distinct circular RNA pools in Lotus japonicus

Circular RNAs (circRNAs) are covalently closed single-stranded RNAs, generated through a back-splicing process that links a downstream 5′ site to an upstream 3′ end. The only distinction in the sequence between circRNA and their linear cognate RNA is the back splice junction. Their low abundance and sequence similarity with their linear origin RNA have made the discovery and identification of circRNA challenging. We have identified almost 6000 novel circRNAs from Lotus japonicus leaf tissue using different enrichment, amplification, and sequencing methods as well as alternative bioinformatics pipelines. The different methodologies identified different pools of circRNA with little overlap. We validated circRNA identified by the different methods using reverse transcription polymerase chain reaction and characterized sequence variations using nanopore sequencing. We compared validated circRNA identified in L. japonicus to other plant species and showed conservation of high-confidence circRNA-expressing genes. This is the first identification of L. japonicus circRNA and provides a resource for further characterization of their function in gene regulation. CircRNAs identified in this study originated from genes involved in all biological functions of eukaryotic cells. The comparison of methodologies and technologies to sequence, identify, analyze, and validate circRNA from plant tissues will enable further research to characterize the function and biogenesis of circRNA in L. japonicus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stoichiometric Ecotoxicology for a Multisubstance World

Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Purple is the new green: biopigments and spectra of Earth-like purple worlds

ABSTRACT With more than 5500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also colour their habitats and could dominate a much wider range of environments on Earth-like exoplanets. Here, we characterize the reflectance spectra of a collection of purple sulfur and purple non-sulfur bacteria from a variety of anoxic and oxic environments. We present models for Earth-like planets where purple bacteria dominate the surface and show the impact of their signatures on the reflectance spectra of terrestrial exoplanets. Our research provides a new resource to guide the detection of purple bacteria and improves our chances of detecting life on exoplanets with upcoming telescopes. Our biological pigment data base for purple bacteria and the high-resolution spectra of Earth-like planets, including ocean worlds, snowball planets, frozen worlds, and Earth analogues, are available online, providing a tool for modellers and observers to train retrieval algorithms, optimize search strategies, and inform models of Earth-like planets, where purple is the new green.

Coelho, Lígia Fonseca (ORCID:0000000150081249)↗
DOE OSTI2023

Coupled wave-current modeling for hydrodynamic load analysis of macroalgae cultivation farms

Large-scale cultivation of macroalgae is one of the most promising biofuel sources that could reduce our consumption of fossil fuels and would be particularly economically competitive when grown for the co-production of additional goods such as food and textiles. Current production of biofuel from algal biomass is limited by labor costs and lack of data on potential impacts of cultivation and harvesting on marine and coastal environments as well as a comprehensive characterization of the impact of environmental conditions on macroalgal feedstock and their bioproduct and biofuel yield and quality. Awarded by the United States (U.S.) Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program, which seeks to enable the U.S. as a global leader in the production of marine biomass, the Marine Biological Laboratory (MBL) has been developing a test system for tropical seaweed cultivation in the Gulf of Mexico and the Caribbean. An integral step in designing macroalgae cultivation farms is to adequately characterize the hydrodynamic climate at potential growth sites. In regions like the Gulf of Mexico and the Caribbean, which are highly exposed to tropical cyclones, it is critical to not only consider the day-to-day hydrodynamic conditions but to also assess the risk of extreme sea states to ensure the survivability of future macroalgae farms. Under these considerations, the Pacific Northwest National Laboratory (PNNL) is providing modeling support for MBL to inform the design and siting of the farm systems that have been proposed for their ARPA-E MARINER project. This report describes the development of a high-resolution coupled storm surge and wave model to simulate the hydrodynamics and wave climate at proposed macroalgae cultivation sites selected by MBL in Florida and Puerto Rico. Model results, including model validation, water level, current distributions, and sea states, are discussed for both selected sites in Florida and Puerto Rico coast. These simulations provide an accurate insight into the hydrodynamic conditions that a macroalgae farm is likely to experience during its operational lifetime, including current information to support fine-scale hydrodynamic load modeling, risk analysis and system design.

09 BIOMASS FUELS↗