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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

SDS22 selectively recognizes and traps metal-deficient inactive PP1

The metalloenzyme protein phosphatase 1 (PP1), which is responsible for ≥50% of all dephosphorylation reactions, is regulated by scores of regulatory proteins, including the highly conserved SDS22 protein. SDS22 has numerous diverse functions, surprisingly acting as both a PP1 inhibitor and as an activator. Here, we integrate cellular, biophysical, and crystallographic studies to address this conundrum. We discovered that SDS22 selectively binds a unique conformation of PP1 that contains a single metal (M2) at its active site, i.e., SDS22 traps metal-deficient inactive PP1. Furthermore, we showed that SDS22 dissociation is accompanied by a second metal (M1) being loaded into PP1, as free metal cannot dissociate the complex and M1-deficient mutants remain constitutively trapped by SDS22. Together, our findings reveal that M1 metal loading and loss are essential for PP1 regulation in cells, which has broad implications for PP1 maturation, activity, and holoenzyme subunit exchange.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Selection and characterization of ssDNA aptamers specifically recognizing pathogenic Vibrio alginolyticus

Abstract Vibrio alginolyticus ( V. alginolyticus ) is a major opportunistic pathogen to both marine animals and humans, which has also caused heavy economic losses to mariculture. The aim of this study was to develop highly specific aptamers for V. alginolyticus . Single‐stranded DNA (ssDNA) aptamers with high binding affinity to viable V. alginolyticus were generated by Systematic Evolution of Ligands by Exponential Enrichment (SELEX) and identified by flow cytometric analysis in this study. The selected aptamers showed high specificity for V. alginolyticus and low apparent binding for other bacteria. The aptamers formed distinct stem‐loop structures, which could form the basis of aptamers’ specific binding to the target V. alginolyticus . Aptamer VA2 and VA8 showed particularly high binding affinity constant (K d ) of 14.31 ± 4.26 and 90.00 ± 13.51 nM, respectively. The aptamers produced no cytotoxic effects in vitro and in vivo. ssDNA aptamers were successfully selected against the viable bacteria pathogen V. alginolyticus by SELEX. The aptamers selected in this study could be not only applied as specific chemical molecular probes for studying V. alginolyticus pathogenesis to Trachinotus ovatus , but also developing rapid convenient diagnosis assay for V. alginolyticus infection, even when applied to the complex sample matrix, such as food and environment samples.

Yu, Qing↗
DOE OSTI2020

Description of Freudenthalidium gen. nov. and Halluxium gen. nov. to Formally Recognize Clades Fr3 and H as Genera in the Family Symbiodiniaceae (Dinophyceae)

The Symbiodiniaceae are a family of marine dinoflagellates known mostly for their endosymbiotic interactions with invertebrates and protists, but facultatively and exclusively free‐living life histories in this family are also evident. A recent systematic revision of the Symbiodiniaceae replaced the clade‐based nomenclature of seven divergent lineages of “ Symbiodinium ” sensu lato with one based on formally described genera. The revised taxonomy was not extended to the whole group because type species to describe a new genus for each of the remaining clades and subclades were lacking. In an effort to characterize benthic habitats of symbiodiniaceans in sediments at Heron Island (Great Barrier Reef, Australia), we isolated >100 monoclonal Symbiodiniaceae cultures. Four of these belonged to Symbiodiniaceae ‘subclade’ Fr3, and three to Clade H, based on nucleotide sequence similarity (ITS2, LSU, cp23S, and mtCOB), representing the first cultures of these taxa. Based on these isolates, we propose two new genera: Freudenthalidium gen. nov. and Halluxium gen. nov., circumscribing Clades Fr3 and H, respectively. Three new species are described: Freudenthalidium heronense , F. endolithicum , and Halluxium pauxillum . Kofoidian tabulations of motile cells confirm previous observations that amphiesmal vesicle arrangements are generally conserved across the family. These descriptions are an important step toward completing the systematic revision of the Symbiodiniaceae. That this contribution was enabled by isolates from an endopsammic habitat highlights the potential of discovering new symbiodiniacean species in the environment, the study of which will lead to a deeper understanding of free‐living versus symbiotic life histories in this ecologically important family of dinoflagellates.

Nitschke, Matthew R.↗
DOE OSTI2025

Data driven methods to recognize patterns in EIC weak-strong simulation

Beam-Beam simulations are currently being studied in preparation for future EIC experiments to study beam-beam effects and, in turn, maximize luminosity. Weak-strong methods are studied for single-particle dynamics during collision. 1 million macro-particles for 1 million turns are typically tracked, corresponding to only 10 seconds in the EIC. The goal of this study is to predict beam properties over the scale of hours. A potential solution focuses on using data-driven methods such as machine learning methods to analyze and extend the insights of the beam properties such as long-term nonlinear effects. This would aid in long-term predictions where results would be more efficiently acquired than a typical tracking simulation. Some limitations such as inaccurate predictions and spatial complexity are also discussed. These methods can then be applied to strong-strong simulations in the future studies.

Accelerator Physics↗
DOE OSTI2022

Continual Learning for Pattern Recognizers using Neurogenesis Deep Learning

Deep neural networks have emerged as a leading set of algorithms to infer information from a variety of data sources such as images and time series data. In their most basic form, neural networks lack the ability to adapt to new classes of information. Continual learning is a field of study attempting to give previously trained deep learning models the ability to adapt to a changing environment. Previous work developed a CL method called Neurogenesis for Deep Learning (NDL). Here, we combine NDL with a specific neural network architecture (the Ladder Network) to produce a system capable of automatically adapting a classification neural network to new classes of data. The NDL Ladder Network was evaluated against other leading CL methods. While the NDL and Ladder Network system did not match the cutting edge performance achieved by other CL methods, in most cases it performed comparably and is the only system evaluated that can learn new classes of information with no human intervention.

97 MATHEMATICS AND COMPUTING↗