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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 1,063 records · Page 59

Mesophyll-specific phytochromes impact chlorophyll light-harvesting complexes (LHCs) and non-photochemical quenching

Phytochromes regulate light-dependent plastid development and plant growth and development. Prior analyses demonstrated that phytochromes regulate expression of Sigma factor 2 (SIG2), which is involved in plastid transcription and coordinates expression of plastid- and nuclear-encoded genes involved in plastid development, as well as plant growth and development. Mutation of SIG2 impacts distinct aspects of photosynthesis, resulting in elevated levels of cyclic electron flow and nonphotochemical quenching (NPQ). As we initially identified SIG2 expression as misregulated in a line lacking phytochromes in mesophyll tissues (i.e., CAB3::pBVR lines), here we report on an investigation of whether photosynthetic parameters such as NPQ are also disrupted in CAB3::pBVR lines. We determined that a specific parameter of NPQ, i.e., energy-dependent quenching (qE) which is a rapidly induced photoprotective mechanism that dissipates stressful absorption of excess light energy during photosynthesis, is disrupted when mesophyll phytochromes are significantly depleted. The observed reduction in NPQ levels in strong CAB3::pBVR lines is associated with a reduction in the accumulation of Lhcb1 proteins and assembly or stability of light-harvesting complexes (LHCs), especially trimeric LHC. These results implicate mesophyll-localized phytochromes in a specific aspect of phytochrome-mediated NPQ, likely through regulation of chlorophyll synthesis and accumulation and the associated impacts on chlorophyll-protein complexes. Finally, this role is distinct from the impact of mesophyll phytochrome-dependent control of SIG2 and associated NPQ regulation.

59 BASIC BIOLOGICAL SCIENCES↗

Pregnancy level of estradiol attenuated virus-specific humoral immune response in H5N1-infected female mice despite inducing anti-inflammatory protection

Estradiol, a major female steroid produced during pregnancy, has been reported to protect ovariectomized animals against H1N1 influenza infections via its anti-inflammatory effects. However, it remains unclear why pregnant women with high gestational estradiol levels are highly susceptible to influenza infections. This study was aimed to investigate the effects of pregnancy level of estradiol on female immunity against H5N1 infection in Balb/c mice. A sex-dependent susceptibility to H5N1 infection (higher morbidity and higher mortality) was observed in both pregnant and non-pregnant female mice as compared to male mice. Subcutaneous implantation of estradiol pellets increased serum estradiol concentrations of non-pregnant female mice to the pregnancy level. These mice were protected from H5N1 infection through downregulation of pulmonary pro-inflammatory cytokines. However, the production of virus-specific antibodies after infection was significantly delayed in estradiol-implanted mice when compared to placebos. Virus-specific IgG-secreting and IL-4-secreting cells were also reduced in estradiol-implanted mice. Similarly, lower antibody titers to seasonal vaccine antigens were found in pregnant women as compared to non-pregnant females without hormone usage. Our results indicate that estradiol levels equivalent to those found during pregnancy have divergent effects on female immunity against influenza, highlighting the importance of vaccination during pregnancy to prevent severe influenza infections.

60 APPLIED LIFE SCIENCES↗

Assembly, molecular organization, and membrane-binding properties of development-specific septins

Septin complexes display remarkable plasticity in subunit composition, yet how a new subunit assembled into higher-order structures confers different functions is not fully understood. Here, this question is addressed in budding yeast, where during meiosis Spr3 and Spr28 replace the mitotic septin subunits Cdc12 and Cdc11 (and Shs1), respectively. In vitro, the sole stable complex that contains both meiosis-specific septins is a linear Spr28–Spr3–Cdc3–Cdc10–Cdc10–Cdc3–Spr3–Spr28 hetero-octamer. Only coexpressed Spr3 and Spr28 colocalize with Cdc3 and Cdc10 in mitotic cells, indicating that incorporation requires a Spr28-Spr3 protomer. Unlike their mitotic counterparts, Spr28-Spr3–capped rods are unable to form higher-order structures in solution but assemble to form long paired filaments on lipid monolayers containing phosphatidylinositol-4,5-bisphosphate, mimicking presence of this phosphoinositide in the prospore membrane. Spr28 and Spr3 fail to rescue the lethality of a cdc11Δ cdc12Δ mutant, and Cdc11 and Cdc12 fail to restore sporulation proficiency to spr3Δ/spr3Δ spr28Δ/spr28Δ diploids. Thus, specific meiotic and mitotic subunits endow septin complexes with functionally distinct properties.

59 BASIC BIOLOGICAL SCIENCES↗

THE SPECIFIC ACCELERATION RATE IN LOOP-STRUCTURED SOLAR FLARES-IMPLICATIONS FOR ELECTRON ACCELERATION MODELS

We analyze electron flux maps based on RHESSI hard X-ray imaging spectroscopy data for a number of extended coronal-loop flare events. For each event, we determine the variation of the characteristic loop length L with electron energy E, and we fit this observed behavior with models that incorporate an extended acceleration region and an exterior 'propagation' region, and which may include collisional modification of the accelerated electron spectrum inside the acceleration region. The models are characterized by two parameters: the plasma density n in, and the longitudinal extent L{sub 0} of, the acceleration region. Determination of the best-fit values of these parameters permits inference of the volume that encompasses the acceleration region and of the total number of particles within it. It is then straightforward to compute values for the emission filling factor and for the specific acceleration rate (electrons s{sup -1} per ambient electron above a chosen reference energy). For the 24 events studied, the range of inferred filling factors is consistent with a value of unity. The inferred mean value of the specific acceleration rate above E{sub 0} = 20 keV is {approx}10{sup -2} s{sup -1}, with a 1{sigma} spread of about a half-order-of-magnitude above and below this value. We compare these values with the predictions of several models, including acceleration by large-scale, weak (sub-Dreicer) fields, by strong (super-Dreicer) electric fields in a reconnecting current sheet, and by stochastic acceleration processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Age and gender specific biokinetic model for strontium in humans

A biokinetic model for strontium in humans is necessary for quantification of internal doses due to strontium radioisotopes. The ICRP-recommended biokinetic model for strontium has limitation for use in a population study, because it is not gender specific and does not cover all age ranges. The extensive Techa River data set on 90Sr in humans (tens of thousands of measurements) is a unique source of data on long-term strontium retention for men and women of all ages at intake. These, as well as published data, were used for evaluation of age- and gender-specific parameters for a new compartment biokinetic model for strontium (Sr-AGe model). The Sr-AGe model has similar structure as the ICRP model for the alkaline earth elements. The following parameters were mainly reevaluated: gastro-intestinal absorption and parameters related to the processes of bone formation and resorption defining calcium and strontium transfers in skeletal compartments. The Sr-AGe model satisfactorily describes available data sets on strontium retention for different kinds of intake (dietary and intravenous) at different ages (0–80 years old) and demonstrates good agreement with data sets for different ethnic groups. The Sr-AGe model can be used for dose assessment in epidemiological studies of general population exposed to ingested strontium radioisotopes.

age dependence↗

Improvement of stability of Nb 3 Sn superconductors by introducing high specific heat substances

High-J c Nb 3 Sn conductors have low stability against perturbations, which accounts for the slow training rates of high-field Nb 3 Sn magnets. While it is known that adding substances with high specific heat (C) into Nb 3 Sn wires can increase their overall specific heat and thus improve their stability, there has not been a practical method that is compatible with the fabrication of long-length conductors. In this work, we put forward a scheme to introduce such substances to distributed-barrier Nb 3 Sn wires, which adds minimum difficulty to the wire manufacturing process. Multifilamentary wires using a mixture of Cu and high-C Gd 2 O 3 powders have been successfully fabricated along this line. Measurements showed that addition of Gd 2 O 3 had no negative effects on residual resitivity ratio or non-Cu J c , and that flux jumps were remarkably reduced, and minimum quench energy values at 4.2 K, 14 T were increased by a factor of three, indicating that stability was significantly improved. We also discussed the influences of the positioning of high-C substances and their thermal diffusivity on their effectiveness in reducing the superconductor temperature rise against perturbations. Based on these results, we proposed an optimized conductor architecture to maximize the effectiveness of this approach.

43 PARTICLE ACCELERATORS↗

Flavor-specific interaction favors strong neutrino self-coupling in the early universe

Flavor-universal neutrino self-interaction has been shown to ease the tension between the values of the Hubble constant measured from early and late Universe data. Here, we introduce a self-interaction structure that is flavor-specific in the three active neutrino framework. This is motivated by the stringent constraints on new secret interactions among electron and muon neutrinos from several laboratory experiments. Our study indicates the presence of a strongly interaction mode which implies a late-decoupling of the neutrinos just prior to matter radiation equality. Using the degeneracy of the coupling strength with other cosmological parameters, we explain the origin of this new mode as a result of better fit to certain features in the CMB data. We find that if only one or two of the three active neutrino flavors are interacting, then the statistical significance of the strongly-interacting neutrino mode increases substantially relative to the flavor-universal scenario. However, the central value of the coupling strength for this interaction mode does not change by any appreciable amount in the flavor-specific cases. We also briefly analyze a scenario with more than three neutrino species of which only one is self-interacting. In none of the cases, we find a large enough Hubble constant that could resolve the so-called Hubble tension.

79 ASTRONOMY AND ASTROPHYSICS↗

Tradeoffs between uniform land protection and biodiversity-specific land protection with <2 °C global warming

Nearly 200 countries have pledged to conserve 30% of terrestrial ecosystems to stop the global biodiversity crisis. However, biodiversity is not uniformly distributed across countries. Adequately addressing this crisis requires a scientific basis for selecting protected land that considers both ecological benefits and impacts to humans. We use the global change analysis model to evaluate land use tradeoffs of four land protection cases under two climate cases. We find that biodiversity-specific land protection up to 39% globally can reduce land use constraints and food prices compared to protecting 30% of land uniformly in each country (’30 × 30’ initiative). Valuing terrestrial carbon for climate change mitigation reduces land conversion pressure and can complement protection strategies. Global impacts to agriculture of additional land protection are small, but regional impacts vary and may be considerable. Overall, biodiversity-specific land protection has greater potential than a uniform target to meet both ecological and human needs.

biodiversity↗

Domain-specific compilers for dynamic simulations of quantum materials on quantum computers

Abstract Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only produce high-fidelity results for those quantum circuits smaller than some given circuit size. Dynamic simulations, therefore, pose a challenge as current algorithms produce circuits that grow in size with each subsequent time-step of the simulation. This underscores the crucial role of quantum circuit compilers to produce executable quantum circuits of minimal size, thereby maximizing the range of physical phenomena that can be studied within the NISQ fidelity budget. Here, we present two domain-specific (DS) quantum circuit compilers for the Rigetti and IBM quantum computers, specifically designed to compile circuits simulating dynamics under a special class of time-dependent Hamiltonians. The compilers outperform state-of-the-art general-purpose compilers in terms of circuit size reduction by around 25%–30% as well as wall-clock compilation time by around 40% (dependent on system size and simulation time-step). Drawing on heuristic techniques commonly used in artificial intelligence, both compilers scale well with simulation time-step and system size. Code for both compilers is open-source and packaged into a full-stack quantum simulation software with tutorials included for ease of use for future researchers wishing to perform dynamic simulations of quantum materials on quantum computers. As our DS compilers provide significant improvements in both compilation time and simulation fidelity, they provide a building block for accelerating progress toward physical quantum supremacy.

Physics↗

Species-specific flowering phenology responses to experimental warming and drought alter herbaceous plant species overlap in a temperate–boreal forest community

Abstract Background and Aims Warmer temperatures and altered precipitation patterns are expected to continue to occur as the climate changes. How these changes will impact the flowering phenology of herbaceous perennials in northern forests is poorly understood but could have consequences for forest functioning and species interactions. Here, we examine the flowering phenology responses of five herbaceous perennials to experimental warming and reduced summer rainfall over 3 years. Methods This study is part of the B4WarmED experiment located at two sites in northern Minnesota, USA. Three levels of warming (ambient, +1.6 °C and +3.1 °C) were crossed with two rainfall manipulations (ambient and 27 % reduced growing season rainfall). Key Results We observed species-specific responses to the experimental treatments. Warming alone advanced flowering for four species. Most notably, the two autumn blooming species showed the strongest advance of flowering to warming. Reduced rainfall alone advanced flowering for one autumn blooming species and delayed flowering for the other, with no significant impact on the three early blooming species. Only one species, Solidago spp., showed an interactive response to warming and rainfall manipulation by advancing in +1.6 °C warming (regardless of rainfall manipulation) but not advancing in the warmest, driest treatment. Species-specific responses led to changes in temporal overlap between species. Most notably, the two autumn blooming species diverged significantly in their flowering timing. In ambient conditions, these two species flowered within the same week. In the warmest, driest treatment, flowering occurred over a month apart. Conclusions Herbaceous species may differ in how they respond to future climate conditions. Changes to phenology may lead to fewer resources for insects or a mismatch between plants and pollinators.

Plant Sciences↗

AdenPredictor: accurate prediction of the adenylation domain specificity of nonribosomal peptide biosynthetic gene clusters in microbial genomes

Microbial natural products represent a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class that include antibiotics, immunosuppressants, anticancer agents, toxins, siderophores, pigments, and cytostatics. The discovery of novel NRPs remains a laborious process because many NRPs consist of nonstandard amino acids that are assembled by nonribosomal peptide synthetases (NRPSs). Adenylation domains (A-domains) in NRPSs are responsible for selection and activation of monomers appearing in NRPs. During the past decade, several support vector machine-based algorithms have been developed for predicting the specificity of the monomers present in NRPs. These algorithms utilize physiochemical features of the amino acids present in the A-domains of NRPSs. In this article, we benchmarked the performance of various machine learning algorithms and features for predicting specificities of NRPSs and we showed that the extra trees model paired with one-hot encoding features outperforms the existing approaches. Moreover, we show that unsupervised clustering of 453560 A-domains reveals many clusters that correspond to potentially novel amino acids. While it is challenging to predict the chemical structure of these amino acids, we developed novel techniques to predict their various properties, including polarity, hydrophobicity, charge, and presence of aromatic rings, carboxyl, and hydroxyl groups.

59 BASIC BIOLOGICAL SCIENCES↗

GIM3E: Condition-specific Models of Cellular Metabolism Developed from Metabolomics and Expression Data

Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/

Environmental Molecular Sciences Laboratory↗

In silico λ-dynamics predicts protein binding specificities to modified RNAs

Abstract RNA modifications shape gene expression through a variety of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.

Biochemistry & Molecular Biology↗

Self-energy dynamics and the mode-specific phonon threshold effect in Kekulé-ordered graphene

Abstract Electron-phonon interaction and related self-energy are fundamental to both the equilibrium properties and non-equilibrium relaxation dynamics of solids. Although electron-phonon interaction has been suggested by various time-resolved measurements to be important for the relaxation dynamics of graphene, the lack of energy- and momentum-resolved self-energy dynamics prohibits direct identification of the role of specific phonon modes in the relaxation dynamics. Here, by performing time- and angle-resolved photoemission spectroscopy measurements on Kekulé-ordered graphene with folded Dirac cones at the Γ point, we have succeeded in resolving the self-energy effect induced by the coupling of electrons to two phonons at Ω1 = 177 meV and Ω2 = 54 meV, and revealing its dynamical change in the time domain. Moreover, these strongly coupled phonons define energy thresholds, which separate the hierarchical relaxation dynamics from ultrafast, fast to slow, thereby providing direct experimental evidence for the dominant role of mode-specific phonons in the relaxation dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Specific Blood Absorption Parameters for 239 PUO 2 and 238 PUO 2 Nanoparticles and Impacts on Bioassay Interpretation

We have determined specific absorption parameters for 239 PuO 2 and 238 PuO 2 based on available biokinetic data from studies in rodents, and the impacts of these parameters on bioassay interpretation and dosimetry after inhalation of nanoPuO 2 materials have been evaluated. Calculations of activities after an acute intake of nanoparticles of 239 PuO 2 and 238PuO 2 are compared with the corresponding calculations using standard default absorption parameters using the International Commission on Radiological Protection (ICRP) 66 respiratory tract model. Committed effective doses are also evaluated and compared. In this case, it was found that interpretation of bioassay measurements with the assumption that the biokinetic behaviour of PuO 2 nanoparticles is the same as that of micrometre-sized particles can result in an overprediction of the committed effective dose by two orders of magnitude. Although in this case the use of the default assumptions (5 µm AMAD, Type S) for assessing dose following inhalation exposure to airborne PuO 2 nanoparticles appears to be conservative, the evaluation of situations involving PuO 2 nanoparticles that may have different particle size and solubility properties should prudently follow the ICRP recommendation to obtain and use additional, material-specific information whenever possible.

61 RADIATION PROTECTION AND DOSIMETRY↗

Specific Gamma-Ray Dose Constants with Current Emission Data

The specific gamma-ray dose constant represents the gamma effective dose rate due to a point source of unit activity of a given nuclide at 1 m. New tabulations of specific gamma-ray dose constants have been made using current gamma emission data from the SCALE 6.2.3 software package and International Commission on Radiological Protection Publication 107, combined with the effective dose per fluence conversion coefficients (antero-posterior orientation) of International Commission on Radiological Protection Publication 116. SCALE data cover 1,264 nuclides, and International Commission on Radiological Protection Publication 107 data include 1,192 nuclides, with only 777 nuclides in common between the two sets.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Binding profiles for 961 Drosophila and C. elegans transcription factors reveal tissue-specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms,Drosophila melanogaster(fly) andCaenorhabditis elegans(worm). These data sets comprise 605 TFs identifying 3.6 M sites in the fly and 356 TFs identifying 0.9 M sites in the worm, and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed “metapeaks,” that larger metapeaks have characteristics of high-occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single-cell RNA-seq data in a machine-learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent–daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing green fluorescent protein (GFP)-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell-type-specific TF–target relationships.

Biochemistry & Molecular Biology↗

Domain-specific text embedding model for accelerator physics

Accelerator physics presents unique challenges for natural language processing (NLP) due to its specialized terminology and complex concepts. A key component in overcoming these challenges is the development of robust text embedding models that transform textual data into dense vector representations, facilitating efficient information retrieval and semantic understanding. In this work, we introduce AccPhysBERT, a sentence embedding model fine-tuned specifically for accelerator physics. Our model demonstrates superior performance across a range of downstream NLP tasks, surpassing existing models in capturing the domain-specific nuances of the field. We further showcase its practical applications, including semantic paper-reviewer matching and integration into retrieval-augmented generation systems, highlighting its potential to enhance information retrieval and knowledge discovery in accelerator physics. Published by the American Physical Society 2025

Hellert, Thorsten (ORCID:0000000227970926)↗