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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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The data included in this Dryad submission was collected in order to understand how the model organism* Escherichia coli* overcomes stabilized G-quadruplexes. This work involved a multi-omics approach to studying how the G-quadruplex stabilizers NMM and Braco-19 impact growth, gene importance, and mRNA/proteomic abundance in G-quadruplex stabilizing conditions.
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Genomic DNA from each sample was prepared using the Wizard Genomic DNA Purification Kit (Promega) and after, DNA was quantified using the QuantiFluor ONE dsDNA System (Promega). Genomic DNA underwent shearing to ~200 bp fragments via sonication and the gDNA fragments were prepared for sequencing using the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB). Bead-based size selection was used to select ~200 bp fragments and the fragments then underwent a splinkerette PCR using a Tn5-enriching forward primer and custom reverse primers for multiplexing. A final bead-based size selection was used to select for the correct length DNA. DNA was sequenced at the University of Michigan Advanced Genomics Core using Illumina sequencing with a custom read primer reading the last 10 nt of the transposon. PhiX174 DNA spike was added to the run to ensure sufficient sequence diversity on the flow cell. Then, a custom index read primer and standard Illumina primer were used to sequence the index reads and PhiX174, respectively.
A novel budding yeast species was isolated from a soil sample collected in the United States of America. Phylogenetic analyses of multiple loci and phylogenomic analyses conclusively placed the species within the genus Pichia. Strain yHMH446 falls within a clade that includes Pichia norvegensis, Pichia pseudocactophila, Candida inconspicua, and Pichia cactophila. Whole genome sequence data were analyzed for the presence of genes known to be important for carbon and nitrogen metabolism, and the phenotypic data from the novel species were compared to all Pichia species with publicly available genomes. Across the genus, including the novel species candidate, we found that the inability to use many carbon and nitrogen sources correlated with the absence of metabolic genes. Based on these results, Pichia galeolata sp. nov. is proposed to accommodate yHMH446(T) (=NRRL Y-64187 = CBS 16864). This study shows how integrated taxogenomic analysis can add mechanistic insight to species descriptions.
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Pyrolysis of biomass generates hundreds of molecules with different functional groups; water, char and inorganics are also produced. In general, new catalysts are evaluated with single model compounds.
Presentation of the OmniTap technology in a brief commercialization pitch.
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Abstract not provided.
The present invention provides for a system comprising (a) first polynucleotide encoding a first promoter operatively linked to an open reading frame (ORF) encoding an endoribonuclease, or an enzymatic active fragment thereof, which cleaves a cognition sequence (cog), and (b) a second polynucleotide encoding a second promoter operatively linked to a nucleotide sequence encoding (i) a cog linked to a coding sequence of interest (COI), (ii) a cog linked to the 3′ end of a first COI and the 5′ end of a second COI, or (iii) a cog locating within a LS (or targeting sequence) linked to a COI.
The National Renewable Energy Laboratory (NREL), in collaboration with the U.S. Department of Energy's (DOE's) Water Power Technologies Office (WPTO), has developed a unique R&D approach to advance marine energy desalination. Desalination is a foundational investment within WPTO's Powering the Blue EconomyTM portfolio [1], and was the first investment within this portfolio. NREL's marine energy desalination spans techno-economic feasibility studies, numerical modeling, and laboratory testing at the component and subsystem level, as well as development of the Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC). This multilayered approach enables an innovative feedback loop where the data and lessons learned from laboratory and field experiments are used to refine modeling tools and analysis techniques, prioritize out-year activities, and refine strategic directions within NREL and across the WPTO portfolio. The primary objective of the NREL-led research is to identify key barriers associated with the commercialization of wave-powered desalination and develop solutions that can be adopted by the marine energy industry. In parallel, these R&D activities can help inform technical assistance and support of industry and academic technologies. These two tracks help build a common solver community approach, while also identifying key stakeholders, government agencies, and other organizations outside of the marine sector that will be necessary for developing a robust industry. For the English version of this report, see NREL/CP-5700-86724 (https://www.nrel.gov/docs/fy24osti/86724.pdf).
To de-risk the U.S. Department of Energy's Waves to Water Prize, the National Renewable Energy Laboratory (NREL) developed a modular, wave powered desalination system. The prize was open to wave energy converter (WEC) designs that generate electricity or WECs that desalinate water mechanically. This added installation risks due to the variance in competitor devices, and the aggressive installation timeline. To reduce these risks NREL developed a wave energy converter (WEC) that the installation team could use to practice installation techniques prior to the competitors arriving to ensure all steps had been considered prior to the event. This was achieved by developing a WEC with a modular power-take-off (PTO). The modular PTO can be configured in one configuration to drive an electric generator that sends electricity to a pier. The electricity that is generated is converted, and stored, so that it can be used to power an electric pump that feeds water to a Reverse Osmosis (RO) desalination unit. In the other configuration the generator is replaced with a pump and seawater is pumped to the RO system on the pier without any electrons being generated. This WEC is formally known as the Hydraulic and Electric Reverse Osmosis (HERO) WEC. For the English version of this report, see NREL/CP-5700-86623 (https://www.nrel.gov/docs/fy24osti/86623.pdf).
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A memory access system may include a first memory address translator, a second memory address translator and a mapping entry invalidator. The first memory address translator translates a first virtual address in a first protocol of a memory access request to a second virtual address in a second protocol and tracks memory access request completions. The second memory address translator is to translate the second virtual address to a physical address of a memory. The mapping entry invalidator requests invalidation of a first mapping entry of the first mapping address translator requests invalidation of a second mapping entry of the second memory address translator corresponding to the first mapping entry following invalidation of the first mapping entry and based upon the tracked memory access request completions.
Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and -related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.