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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Quantitative iTRAQ-based secretome analysis reveals species-specific and temporal shifts in carbon utilization strategies among manganese(II)-oxidizing Ascomycete fungi

Fungi generate a wide range of extracellular hydrolytic and oxidative enzymes and reactive metabolites, collectively known as the secretome, that synergistically drive plant litter decomposition in the environment. While secretome studies of model organisms have greatly expanded our knowledge of these enzymes, few have extended secretome characterization to environmental isolates or directly compared temporal patterns of enzyme utilization among diverse species. Thus, the mechanisms of carbon (C) degradation by many ubiquitous soil fungi remain poorly understood. Here we use a combination of iTRAQ proteomics and custom bioinformatic analyses to compare the protein composition of the secretomes of four manganese(II)-oxidizing Ascomycete fungi over a three-week time course. We demonstrate that although the fungi produce a similar suite of extracellular enzymes, they exhibit striking differences in the regulation of these enzymes among species and over time, revealing species-specific and temporal shifts in C utilization strategies as they degrade the same substrate. Specifically, our findings suggest that Paraconiothyrium sporulosum AP3s5-JAC2a and Alternaria alternata SRC1lrK2f employ sequential enzyme secretion patterns concomitant with decreasing resource availability, Stagonospora sp. SRC1lsM3a preferentially degrades proteinaceous substrate before switching to carbohydrates, and Pyrenochaeta sp. DS3sAY3a utilizes primarily peptidases to aggressively attack carbon sources in a concentrated burst. This work highlights the diversity of operative metabolic strategies among cellulose-degrading Ascomycetes and enhances our understanding of their role in C turnover in the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Ab initio-informed maximum entropy modeling of rovibrational relaxation and state-specific dissociation with application to the O{sub 2} + O system

Quasi-classical trajectory (QCT) calculations are used to study state-specific ro-vibrational energy exchange and dissociation in the O{sub 2} + O system. Atom-diatom collisions with energy between 0.1 and 20 eV are calculated with a double many body expansion potential energy surface by Varandas and Pais [Mol. Phys. 65, 843 (1988)]. Inelastic collisions favor mono-quantum vibrational transitions at translational energies above 1.3 eV although multi-quantum transitions are also important. Post-collision vibrational favoring decreases first exponentially and then linearly as Δv increases. Vibrationally elastic collisions (Δv = 0) favor small ΔJ transitions while vibrationally inelastic collisions have equilibrium post-collision rotational distributions. Dissociation exhibits both vibrational and rotational favoring. New vibrational-translational (VT), vibrational-rotational-translational (VRT) energy exchange, and dissociation models are developed based on QCT observations and maximum entropy considerations. Full set of parameters for state-to-state modeling of oxygen is presented. The VT energy exchange model describes 22 000 state-to-state vibrational cross sections using 11 parameters and reproduces vibrational relaxation rates within 30% in the 2500–20 000 K temperature range. The VRT model captures 80 × 10{sup 6} state-to-state ro-vibrational cross sections using 19 parameters and reproduces vibrational relaxation rates within 60% in the 5000–15 000 K temperature range. The developed dissociation model reproduces state-specific and equilibrium dissociation rates within 25% using just 48 parameters. The maximum entropy framework makes it feasible to upscale ab initio simulation to full nonequilibrium flow calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

METACLUSTER—an R package for context-specific expression analysis of metabolic gene clusters

Abstract Summary Plants and microbes produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have yet to be elucidated. Some biosynthetic pathways are encoded by enzymes collocated in the chromosome. To facilitate a more comprehensive condition and tissue-specific expression analysis of metabolic gene clusters, we developed METACLUSTER, a probabilistic framework for characterizing metabolic gene clusters using context-specific gene expression information. Availability and implementation METACLUSTER is freely available at https://github.com/mbanf/METACLUSTER. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗
DOE OSTI2016

A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription factor

A whole-cell biosensor utilizing a transcription factor (TF) is an effective tool for sensitive and selective detection of specialty chemicals or anthropogenic molecules, but requires access to an expanded repertoire of TFs. Using homology modeling and ligand docking for binding pocket identification, assisted by conservative mutations in the pocket, we engineered a novel specificity in an Acinetobacter TF, PobR, to ‘sense’ a chemical p-nitrophenol (pNP) and measured the response via a fluorescent protein reporter expressed from a PobR promoter. Out of 107 variants of PobR, four were active when dosed with pNP, with two mutants showing a specificity switch from the native effector 4-hydroxybenzoate (4HB). One of the mutants, pNPmut1 was then used to create a smart microbial cell responding to pNP production from hydrolysis of an insecticide, paraoxon, in a coupled assay involving phosphotriesterase (PTE) enzyme expressed from a separate promoter. We show the fluorescence of the cells correlated with the catalytic efficiency of the PTE variant expressed in each cell. High selectivity between similar molecules (4HB versus pNP), high sensitivity for pNP detection (~2 μM) and agreement of apo- and holo-structures of PobR scaffold with predetermined computational models are other significant results presented in this work.

Jha, Ramesh K.↗
DOE OSTI2020

Experimental validation of color rendition specification criteria based on ANSI/IES TM-30-18

An experiment was conducted to examine color preference specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied color rendition conditions designed to meet or not meet previously proposed color preference specification criteria using ANSI/IES TM-30-18 Rf, Rcs,h1, and Rg. The color rendition conditions did not meet the criterion for none, one, two, or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects’ color appearance on eight-point scales for saturated-dull, normal-shifted, and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that color preference criteria could be adjusted slightly to improve performance, with Tier A having Rf = 78, Rg = 95, and -1% = Rcs,h1 = 15%, Tier B having Rf = 74, Rg = 92, and -7% = Rcs,h1 = 19%, and Tier C having Rf = 70, Rg = 89, -12% = Rcs,h1 = 23%. A companion regression analysis shows models based on Rf, Rg, and Rcs,h1 were superior in predicting color preference compared to those using other measures of color rendition.

Royer, Michael P.↗
DOE OSTI2026

Data for FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Genomics↗
NASA NTRS1999

Intent Specifications: An Approach to Building Human-Centered Specifications

This paper examines and proposes an approach to writing software specifications, based on research in systems theory, cognitive psychology, and human-machine interaction. The goal is to provide specifications that support human problem solving and the tasks that humans must perform in software development and evolution. A type of specification, called intent specifications, is constructed upon this underlying foundation.

Leveson, Nancy G.↗
NASA NTRS1991

Phytochrome-mediated germination and early development in spores of Dryopteris filix-mas L.: phase-specific and non phase-specific inhibition by staurosporine

The alkaloid staurosporine, currently known as the most potent inhibitor of protein kinase C, PKC, was tested for its ability to inhibit phytochrome-mediated spore germination in Dryopteris filix-mas L., evaluated by the induction of chlorophyll synthesis. Approximately half-maximal inhibition was obtained at a concentration of 10(-5) M. This effect of staurosporine was phase-specific and was found during the same period in which the presence of extracellular calcium is necessary for realization of the light signal. Furthermore, the ability of staurosporine to prevent progression of a germinated spore into early gametophyte development, evaluated by the accumulation of chlorophyll, was examined. Again, staurosporine (10(-5) M) significantly diminished chlorophyll accumulation, determined quantitatively in vivo by single-cell measurements, in a non-phase specific way. The fact that the phase-specific inhibitory effect of staurosporine in preventing germination was coincident with the phase-specific requirement of Ca2+ suggests that both Ca2+ and staurosporine affect the same step in the signal-transduction chain. A phosphorylation event catalysed by PKC or any Ca2+ -dependent protein kinase is proposed as the target of staurosporine and Ca2+.

Non-NASA Center↗
DOE OSTI2016

Sci-Thur AM: YIS – 04: Stopping power-to-Cherenkov power ratios and beam quality specification for clinical Cherenkov emission dosimetry of electrons: beam-specific effects and experimental validation

Purpose: To advance towards clinical Cherenkov emission (CE)-based dosimetry by investigating beam-specific effects on Monte Carlo-calculated electron-beam stopping power-to-CE power ratios (SCRs), addressing electron beam quality specification in terms of CE, and validating simulations with measurements. Methods: The EGSnrc user code SPRRZnrc, used to calculate Spencer-Attix stopping-power ratios, was modified to instead calculate SCRs. SCRs were calculated for 6- to 22-MeV clinical electron beams from Varian TrueBeam, Clinac 21EX, and Clinac 2100C/D accelerators. Experiments were performed with a 20-MeV electron beam from a Varian TrueBeam accelerator, using a diffraction grating spectrometer with optical fiber input and a cooled back-illuminated CCD. A fluorophore was dissolved in the water to remove CE signal anisotropy. Results: It was found that angular spread of the incident beam has little effect on the SCR (≤ 0.3% at d{sub max}), while both the electron spectrum and photon contamination increase the SCR at shallow depths and decrease it at large depths. A universal data fit of R{sub 50} in terms of C{sub 50} (50% CE depth) revealed a strong linear dependence (R{sup 2} > 0.9999). The SCR was fit with a Burns-type equation (R{sup 2} = 0.9974, NRMSD = 0.5%). Below-threshold incident radiation was found to have minimal effect on beam quality specification (< 0.1%). Experiments and simulations were in good agreement. Conclusions: Our findings confirm the feasibility of the proposed CE dosimetry method, contingent on computation of SCRs from additional accelerators and on further experimental validation. This work constitutes an important step towards clinical high-resolution out-of-beam CE dosimetry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons: Event-Specific 1-D Modeling

The most significant unknown regarding relativistic electrons in Earth’s outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in-situ measurements during the 13-14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and THEMIS observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss timescale show deviation from the event specific model of nearly two orders of magnitude within 72 hours of the enhancement event. However, models using alternative loss timescales closely resemble the event specific model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The role of filamentation in activation and DNA sequence specificity of the sequence-specific endonuclease SgrAI

Filament formation by metabolic, biosynthetic, and other enzymes has recently come into focus as a mechanism to fine-tune enzyme activity in the cell. Filamentation is key to the function of SgrAI, a sequence-specific DNA endonuclease that has served as a model system to provide some of the deepest insights into the biophysical characteristics of filamentation and its functional consequences. Structure-function analyses reveal that, in the filamentous state, SgrAI stabilizes an activated enzyme conformation that leads to accelerated DNA cleavage activity and expanded DNA sequence specificity. The latter is thought to be mediated by sequence-specific DNA structure, protein–DNA interactions, and a disorder-to-order transition in the protein, which collectively affect the relative stabilities of the inactive, non-filamentous conformation and the active, filamentous conformation of SgrAI bound to DNA. Full global kinetic modeling of the DNA cleavage pathway reveals a slow, rate-limiting, second-order association rate constant for filament assembly, and simulations of in vivo activity predict that filamentation is superior to non-filamenting mechanisms in ensuring rapid activation and sequestration of SgrAI's DNA cleavage activity on phage DNA and away from the host chromosome. In vivo studies demonstrate the critical requirement for accelerated DNA cleavage by SgrAI in its biological role to safeguard the bacterial host. Collectively, these data have advanced our understanding of how filamentation can regulate enzyme structure and function, while the experimental strategies used for SgrAI can be applied to other enzymatic systems to identify novel functional roles for filamentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A funnel approach to enable analyses of epitope-specific human CD4 T cells specific for influenza and SARS-CoV-2

Protection against pathogens relies heavily on the adaptive immune response, whose key regulators are CD4 T cells. CD4 T cells, notable for their complex repertoire and functional potential, can most easily be dissected by identifying, quantifying, characterizing, and isolating epitope-specific cells. In the study reported here, we present a systematic and unbiased strategy that has enabled the identification of highly immunogenic peptide epitopes derived from influenza virus and SARS-CoV-2, presented by human HLA-DR proteins. Coupling the use of HLA-DR transgenic mice with infection and vaccination and highly sensitive epitope-specific cytokine ELISpot assays, we have narrowed the potential epitopes from 450 to 600 peptides to 5–15 peptides for each allele by an iterative process of elimination and selection, which we have termed a funnel approach. These epitopes have been validated in HLA-DR-typed human CD4 T cells directly ex vivo and enabled the derivation and implementation of HLA-DR peptide tetramers. Tetramer staining of human PBMCs enriched for CD4 T memory populations from healthy adult subjects, highlighted this approach as a sensitive and specific method for identifying novel epitopes, and subsequent CD4 T-cell responses to human viral infections.

CD4 T cell↗
NASA NTRSDate not supplied

BERT-E: An Earth Science Specific Language Model for Domain-Specific Downstream Tasks

Language models are fast approaching human-like understanding of natural language. They have been shown to perform equally, if not better than humans in a myriad of language tasks such as next sentence prediction, question answering, entity extraction etc. Part of the success of the models are owed to the fact that they have been trained on varied natural language text over the internet. By virtue of this, the models do not contain the semantic information present in Earth science literature. Hence, there is a lot of room for improvement when using these models for earth science specific tasks. In this work, we showcase our approach on developing Earth science specific language models. Furthermore, we justify the need for such a model by using the embeddings generated by the model to perform a domain specific downstream task that performs better than a generic model.

Prasanna Koirala↗
DOE OSTI2020

Voltage Restoration in Microgrids using Temporal Logic Specifications

This paper proposes an energy storage controller synthesis method for voltage restoration in microgrids with respect to temporal logic specifications (TLSs). TLSs is introduced in this paper as a formalism to control the voltage variation of a critical bus against an operational bounds over time. The power system with synchronous generator (SG) connected to a critical load bus is modeled as a set of differential-algebraic equations and a simplified analytical model is derived to describe the voltage variation of this critical bus. The control objective is to schedule an optimal control input signal from a supportive energy storage system (ESS) connected to the critical bus, such that the voltage variation of the latter satisfies the TLSs, such as a finite-time restoration. The proposed control is verified on a lumped distribution system model. With this control diagram, supportive controllers can be designed to make voltage behaviors comply with grid codes and avoid unnecessary relay actions.

Taousser, Fatima Zohra↗