Search NASA⌕ Search

SEARCH · Search NASA

Results for “function”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47

Plant-microbial interplay for organic nitrogen mediated by functional specificity of root compartments

The organic form of nitrogen (N) is a critical intermediate in mutualistic and competitive root-microbial interactions, mediated by extracellular enzymes. Visualization of the hotspots of organic N and proteolytic activity might be valuable for revealing root functional specificity in N acquisition and transformation at the level of individual roots and compartments. For the first time, we used time-lapse amino-mapping and zymography to co-localize and map the spatial distribution of amino-N and leucine aminopeptidase (LAP) activity in the soil and different root parts of maize (Zea mays L.). Amino-N distribution was mainly associated with seminal roots and root tips, where it overlapped with LAP activity hotspots. In the lateral roots and bulk soil, however, LAP activity was decoupled from amino-N. Distinct functional traits revealed themselves as the highest amino-N content and LAP activity in seminal root tips and as the largest relative extent of the rhizosphere in lateral root tips. Co-localized amino-N and LAP activities highlighted different nutrient acquisition strategies mediated by root-microbe interactions, depending on the root compartment. Seminal roots and their tips appeared to adopt mutualistic strategies, potentially attracting root-associated microorganisms through releasing oligo- and polypeptides. In contrast, lateral roots, with amino-N detected only at their tips, demonstrated stronger N competition, relying on the enzyme activity of the rhizosphere microbial community for N acquisition. These insights emphasized the role of root functional specialization in shaping plant-microbe interactions, offering pathways to enhance nutrient use efficiency.

Maize (Zea mays L.)↗

Design and Function of α-Helix-Rich, Heme-Binding Peptide Materials

Peptide materials often employ short peptides that self-assemble into unique nanoscale architectures and have been employed across many fields relevant to medicine and energy. A majority of peptide materials are high in beta-sheet, secondary structure content, including heme-binding peptide materials. To broaden the structural diversity of heme-binding peptide materials, a small series of peptides were synthesized to explore the design criteria required for (1) folding into an alpha-helix structure, (2) assembling into a nanoscale material, (3) binding heme, and (4) demonstrating functions similar to that of heme proteins. One peptide was identified to meet all four criteria, including the heme protein function of CO binding and its microsecond-to-millisecond recombination rates, as measured by transient absorption spectroscopy. In conclusion, implications of new design criteria and peptide material function through heme incorporation are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Random Phase Approximation Correlation Energy Using Real-Space Density Functional Perturbation Theory

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn–Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic-scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method’s accuracy by comparing with plane-wave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 s on 4608 processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗

Real-Space Quantification of Exciton Localization in Acene Crystals Using Wannier Function Decomposition

Here, we introduce the Wannier function decomposition of excitons (WFDX) method to quantify exciton localization in solids within the ab initio Bethe-Salpeter equation framework. By decomposing each Bloch exciton wave function into products of single-particle electron and hole maximally localized Wannier functions, this real-space approach provides well-defined orbital- and spatial-resolved measures of both Frenkel and charge-transfer excitons at low computational cost. We apply WFDX to excitons in acene crystals, quantifying how the number of rings, the exciton spin state, and the center-of-mass momentum affect spatial localization. Additionally, we show how this real-space representation reflects structural nonsymmorphic symmetries that are hidden in standard reciprocal-space descriptions. We demonstrate how the WFDX framework can be used to efficiently interpolate exciton expansion coefficients in reciprocal-space and outline how it may facilitate evaluation of observables involving position operators, highlighting its potential as a general tool for both analyzing and computing excitonic properties in solids.

Tao, Zui [University of California, Berkeley, CA (↗

Untangling Sources of Error in the Density-Functional Many-Body Expansion

The many-body expansion provides a framework for data-driven applications of electronic structure theory, including parametrization of classical force fields and machine learning. In this article, we demonstrate that its use significantly amplifies quadrature grid errors when modern density-functional approximations are employed. Standard grids that work well in conventional density-functional calculations result in runaway error accumulation when used with the many-body expansion. At the same time, delocalization error is also exacerbated, leading to exaggerated estimates of nonadditive n-body interactions. This is illustrated for anion–water clusters using the SCAN, r2SCAN, ωB97X-V and ωB97M-V functionals. By employing dense quadrature grids, the inherent self-interaction error is exposed, which can then be mitigated using a variety of other strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tethered from the Head and from the Tail: The Structure of Hydroxyl-Functionalized Ionic Liquids

Ionic liquids with special functionalities are synthesized with the specific purpose of creating new patterns of interaction in the condensed phase. This Letter discusses the case of alcohol-functionalized ILs, the so-called HFILs, which are part of the larger cohort of task-specific ionic liquids. We find that this small chemical modification can cause massive changes in the liquid landscape when the cationic tails are longer. For prototypical ionic liquids, larger alkyl tails act as separators of charge networks, but in the case of HFILs these become physical charge network linkers. The OH functionality adds a large repertoire of interactions and correlations that were mostly unavailable to traditional ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transition Metal Dichalcogenide MoS 2 : Oxygen and Fluorine Functionalization for Selective Plasma Processing

Low-temperature plasma processing is a promising technique for tailoring transition metal dichalcogenides (TMDs). For chalcogen substitution processing, a key challenge is to identify the ion energy window that enables selective chalcogen removal while preserving the metal lattice. Using ab initio molecular dynamics (AIMD), we demonstrate that oxygen and fluorine functionalization widen the processing window by significantly lowering the sulfur sputtering energy threshold (E sputt,S ) of MoS 2 from ∼30 to ∼10 eV via formation of sputtering products such as SO 2 and SF n . Additionally, we show that experimentally relevant cryogenic temperatures strongly affect E sputt,S (T). The dependence is confirmed via AIMD and also predicted by a mechanistic parameter-free theory, suggesting that E sputt (T) generalizes to other TMDs, functionalizations, and surface impact conditions. Our results highlight oxygen/fluorine functionalization, ionic impact angle, and material temperature to be key control parameters for selective, damage-controlled chalcogen removal in TMD processing.

Polyachenko, Yury [Princeton Plasma Physics Labora↗

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineered Endosymbionts that Modulate Primary Macrophage Function and Attenuate Tumor Growth by Shifting the Tumor Microenvironment

Modulating gene expression in macrophages can be used to improve tissue regeneration and redirect tumor microenvironments (TMEs) toward positive therapeutic outcomes. We have developed Bacillus subtilis as an engineered endosymbiont (EES) capable of residing inside the eukaryotic host cell cytoplasm and controlling the fate of macrophages. Secretion of mammalian transcription factors (TFs) from B. subtilis that expresses listeriolysin O (LLO; allowing the EES to escape destruction by the macrophage) modulated expression of surface markers, cytokines, and chemokines, indicating functional changes in a macrophage/monocyte cell line. The engineered B. subtilis LLO TF strains were evaluated in murine bone marrow-derived macrophages (BMDMs) by flow cytometry, chemokine/cytokine profiling, metabolic assays, and RNA-Seq delivery of TFs by the EES shifted BMDM gene expression, production of cytokine and chemokines, and metabolic patterns, indicating that the TF strains could guide primary macrophage function. Thereafter, the ability of the TF strains to alter the TME was characterized in vivo in an orthotopic murine model of triple-negative breast cancer to assess therapeutic effects. The TF strains altered the TME by shifting immune cell composition and attenuating tumor growth. Additionally, multiple doses of the TF strains were well-tolerated by the mice. The use of B. subtilis LLO TF strains as EES showed promise as a unique cancer immunotherapy by directing the immune function intracellularly. The uses of EES could be expanded to modulate other mammalian cells over a range of biomedical applications.

60 APPLIED LIFE SCIENCES↗

Nanoconfinement of High Hydrogen-to-Metal Ratio Lanthanum Hydrides in Functionalized Carbon Hosts

Metal hydrides with a high hydrogen content are important for materials-based hydrogen storage and high-temperature superconductivity. Nanoconfinement of metal hydrides in porous hosts is a promising strategy to tune the thermodynamic stability and control the hydrogen-to-metal ratio. However, lanthanum hydride (LaH x ) nanoconfinement in porous materials has been limited due to the challenges associated with isolating and stabilizing nanoparticles of La or La-hydrides. Here we successfully demonstrated the chemical reduction of La­(III) salts to La(0), and subsequent infiltration into pure CMK-3 and nitrogen-doped CMK-3 (NCMK-3) porous carbons. Transmission electron microscopy measurements revealed a uniform distribution of LaH x species within the carbon hosts, while X-ray absorption and photoelectron spectroscopy provided detailed information about the local chemical environment. Sieverts measurements indicate that LaH x @NCMK-3 could desorb up to 0.75 wt % hydrogen, which is higher than non-nitrogen-functionalized CMK-3 (0.43 wt % H). Density Functional Theory and ab initio molecular dynamics calculations indicate that host–guest interaction energies are favorable for porous carbon with nitrogen defects, which is supported by experimental evidence. Moreover, high-pressure synchrotron X-ray diffraction measurements were conducted using a diamond anvil cell up to 60 GPa and reveal that the nitrogen-functionalized nanoporous carbon host favors the formation of higher H:La ratios in the presence of ammonia borane compared to the pure CMK-3 host. This approach could serve as a suitable platform for developing nanoscale superconducting materials at lower pressures and temperatures compared to bulk.

Shivanna, Mohana↗

A [FeFe] Hydrogenase–Rubrerythrin Chimeric Enzyme Functions to Couple H 2 Oxidation to Reduction of H 2 O 2 in the Foodborne Pathogen Clostridium perfringens

[FeFe] hydrogenases are a diverse class of H 2 -activating enzymes with a wide range of utilities in nature. As H 2 is a promising renewable energy carrier, exploration of the increasingly realized functional diversity of [FeFe] hydrogenases is instrumental for understanding how these remarkable enzymes can benefit society and inspire new technologies. In this work, we uncover the properties of a highly unusual natural chimera composed of a [FeFe] hydrogenase and rubrerythrin as a single polypeptide. The unique combination of [FeFe] hydrogenase with rubrerythrin, an enzyme that functions in H 2 O 2 detoxification, raises the question of whether catalytic reactions, such as H 2 oxidation and H 2 O 2 reduction, are functionally linked. Herein, we express and purify a representative chimera from Clostridium perfringens (termed Cper HydR) and apply various electrochemical and spectroscopic approaches to determine its activity and confirm the presence of each of the proposed metallocofactors. The cumulative data demonstrate that the enzyme contains a surprising array of metallocofactors: the catalytic site of [FeFe] hydrogenase termed the H-cluster, two [4Fe-4S] clusters, two rubredoxin Fe(Cys) 4 centers, and a hemerythrin-like diiron site. The absence of an H 2 -evolution current in protein film voltammetry highlights an exceptional bias of this enzyme toward H 2 oxidation to the greatest extent that has been observed for a [FeFe] hydrogenase. Here, we demonstrate that Cper HydR uses H 2 , catalytically split by the hydrogenase domain, to reduce H 2 O 2 by the diiron site. Structural modeling suggests a homodimeric nature of the protein. Overall, this study demonstrates that Cper HydR is an H 2 -dependent H 2 O 2 reductase. Equipped with this information, we discuss the possible role of this enzyme as a part of the oxygen-stress response system, proposing that Cper HydR constitutes a new pathway for H 2 O 2 mitigation.

08 HYDROGEN↗

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

54 ENVIRONMENTAL SCIENCES↗

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

60 APPLIED LIFE SCIENCES↗

Structure of human MUTYH and functional profiling of cancer-associated variants reveal an allosteric network between its [4Fe-4S] cluster cofactor and active site required for DNA repair

Abstract MUTYH is a clinically important DNA glycosylase that thwarts mutations by initiating base-excision repair at 8-oxoguanine (OG):A lesions. The roles for its [4Fe-4S] cofactor in DNA repair remain enigmatic. Functional profiling of cancer-associated variants near the [4Fe-4S] cofactor reveals that most variations abrogate both retention of the cofactor and enzyme activity. Surprisingly, R241Q and N238S retained the metal cluster and bound substrate DNA tightly, but were completely inactive. We determine the crystal structure of human MUTYH bound to a transition state mimic and this shows that Arg241 and Asn238 build an H-bond network connecting the [4Fe-4S] cluster to the catalytic Asp236 that mediates base excision. The structure of the bacterial MutY variant R149Q, along with molecular dynamics simulations of the human enzyme, support a model in which the cofactor functions to position and activate the catalytic Asp. These results suggest that allosteric cross-talk between the DNA binding [4Fe-4S] cofactor and the base excision site of MUTYH regulate its DNA repair function.

Science & Technology - Other Topics↗

Climate-driven succession in marine microbiome biodiversity and biogeochemical function

Abstract Seasonal and El Niño-Southern Oscillation (ENSO) warming result in similar ocean changes as predicted with climate change. Climate-driven environmental cycles have strong impacts on microbiome diversity, but impacts on microbiome function are poorly understood. Here we quantify changes in microbial genomic diversity and functioning over 11 years covering seasonal and ENSO cycles at a coastal site in the southern California Current. We observe seasonal oscillations between large-genome lineages during cold, nutrient rich conditions in winter and spring versus small-genome lineages, including Prochlorococcus and Pelagibacter , in summer and fall. Parallel interannual changes separate communities depending on ENSO condition. Biodiversity shifts translate into clear oscillations in microbiome functional potential. Ocean warming induced an ecosystem with less iron but more macronutrient stress genes, depressed organic carbon degradation potential and biomass, and elevated carbon-to-nutrient biomass ratios. The consistent microbial response observed across time-scales points towards large climate-driven changes in marine ecosystems and biogeochemical cycles.

Larkin, Alyse A. (ORCID:0000000344660791)↗

Mobile genetic elements shape microbial diversity and functions in thawing permafrost soils

Ecosystems are shaped by communities of microorganisms whose niches and impacts depend on functional profiles influenced by gene gains and losses. Culture-based experiments demonstrate that mobile genetic elements (MGEs) can mediate gene flux, but quantitative understanding of these dynamics in natural systems remains limited. Here we develop and apply a systematic, meta-omic framework to investigate MGEs in a complex natural system using an 8-year soil time series collected at Stordalen Mire, in Sweden’s thawing permafrost margin. In this climate-critical peatland, we identify ~2.1 million MGE recombinases across 89 microbial phyla and assess ecological distributions, affected functions, past mobility and current activity. This revealed an active mobilome that shapes natural genetic diversity via differential impacts on major phyla and affects a wide range of functions, including metabolic genes involved in carbon flux and nutrient cycling. These findings and this analytic framework suggest avenues towards a better understanding of MGE diversity, activity, mobility and impacts across ecosystems.

Biological and medical sciences↗