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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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System interrogates and maintains user-definable data files from remote terminals, using English-like, free-form query language easily learned by persons not proficient in computer programming. System operates in asynchronous mode, allowing any number of inquiries within limitation of available core to be active concurrently.
Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.
The CRISPR-Cas9 nuclease has been widely repurposed as a molecular and cell biology tool for its ability to programmably target and cleave DNA. Cas9 recognizes its target site by unwinding the DNA double helix and hybridizing a 20-nucleotide section of its associated guide RNA to one DNA strand, forming an R-loop structure. A dynamic and mechanical description of R-loop formation is needed to understand the biophysics of target searching and develop rational approaches for mitigating off-target activity while accounting for the influence of torsional strain in the genome. Here we investigate the dynamics of Cas9 R-loop formation and collapse using rotor bead tracking (RBT), a single-molecule technique that can simultaneously monitor DNA unwinding with base-pair resolution and binding of fluorescently labeled macromolecules in real time. By measuring changes in torque upon unwinding of the double helix, we find that R-loop formation and collapse proceed via a transient discrete intermediate, consistent with DNA:RNA hybridization within an initial seed region. Using systematic measurements of target and off-target sequences under controlled mechanical perturbations, we characterize position-dependent effects of sequence mismatches and show how DNA supercoiling modulates the energy landscape of R-loop formation and dictates access to states competent for stable binding and cleavage. Consistent with this energy landscape model, in bulk experiments we observe promiscuous cleavage under physiological negative supercoiling. The detailed description of DNA interrogation presented here suggests strategies for improving the specificity and kinetics of Cas9 as a genome engineering tool and may inspire expanded applications that exploit sensitivity to DNA supercoiling.
Abstract Background Mass spectrometry-based proteomics can identify and quantify thousands of proteins from individual microbial species, but a significant percentage of these proteins are unannotated and hence classified as proteins of unknown function (PUFs). Due to the difficulty in extracting meaningful metabolic information, PUFs are often overlooked or discarded during data analysis, even though they might be critically important in functional activities, in particular for metabolic engineering research. Results We optimized and employed a pipeline integrating various “guilt-by-association” (GBA) metrics, including differential expression and co-expression analyses of high-throughput mass spectrometry proteome data and phylogenetic coevolution analysis, and sequence homology-based approaches to determine putative functions for PUFs in Clostridium thermocellum . Our various analyses provided putative functional information for over 95% of the PUFs detected by mass spectrometry in a wild-type and/or an engineered strain of C. thermocellum . In particular, we validated a predicted acyltransferase PUF (WP_003519433.1) with functional activity towards 2-phenylethyl alcohol, consistent with our GBA and sequence homology-based predictions. Conclusions This work demonstrates the value of leveraging sequence homology-based annotations with empirical evidence based on the concept of GBA to broadly predict putative functions for PUFs, opening avenues to further interrogation via targeted experiments.
Abstract Microorganisms play vital roles in modulating organic matter decomposition and nutrient cycling in soil ecosystems. The enzyme latch paradigm posits microbial degradation of polyphenols is hindered in anoxic peat leading to polyphenol accumulation, and consequently diminished microbial activity. This model assumes that polyphenols are microbially unavailable under anoxia, a supposition that has not been thoroughly investigated in any soil type. Here, we use anoxic soil reactors amended with and without a chemically defined polyphenol to test this hypothesis, employing metabolomics and genome-resolved metaproteomics to interrogate soil microbial polyphenol metabolism. Challenging the idea that polyphenols are not bioavailable under anoxia, we provide metabolite evidence that polyphenols are depolymerized, resulting in monomer accumulation, followed by the generation of small phenolic degradation products. Further, we show that soil microbiome function is maintained, and possibly enhanced, with polyphenol addition. In summary, this study provides chemical and enzymatic evidence that some soil microbiota can degrade polyphenols under anoxia and subvert the assumed polyphenol lock on soil microbial metabolism.
Fusion of the host membrane and viral envelope by class I viral fusion proteins is driven by the assembly of a postfusion six-helix bundle formed through antiparallel interactions between N-terminal (HR1) and C-terminal (HR2) heptad-repeat regions. Although mutations in these regions of the measles virus (MeV) fusion (F) glycoprotein are known to promote neuropathogenic and hyperfusogenic phenotypes, their effects on postfusion core stability have not been systematically examined. Here, we combine peptide biophysics and X-ray crystallography to interrogate how mutations within the HR2 domain, present in native neuropathogenic MeV isolates (e.g., L454W and N462K) and laboratory-generated hyperfusogenic variants (e.g., L454M and T461A), influence postfusion 6HB assembly. Circular dichroism (CD) spectroscopy reveals that, with few exceptions, these mutations decrease postfusion core stability, despite their association with enhanced fusion activity. We also report the first crystal structure of the wild-type MeV postfusion core as well as structures of six hyperfusogenic variants, enabling high-resolution comparison of the molecular basis of destabilization. Structural analysis shows that these effects arise from localized perturbations to steric packing, hydrogen bonding networks, and helix-stabilizing interactions within HR2, while the overall 6HB architecture remains conserved. Together, these results indicate that hyperfusogenic mutations are not associated with stabilization of the postfusion state and are instead consistent with models in which hyperfusogenicity arises from a reduction in the energetic barrier to fusion, potentially through effects on prefusion stability or triggering efficiency. These findings establish key sequence-structure–stability relationships governing coiled-coil assembly and provide a framework for the design of HR1- and HR2-based fusion inhibitors.
Proteostasis of the endoplasmic reticulum (ER) is controlled by sophisticated signaling pathways that are collectively called the unfolded protein response (UPR) and are initiated by specialized ER membrane-associated sensors. The evidence that complete loss-of-function mutations of the most conserved of the UPR sensors, inositol-requiring enzyme 1 (IRE1), dysregulates tissue growth and development in metazoans and plants raises the fundamental question as to how IRE1 is connected to organismal growth. To address this question, we interrogated the Arabidopsis primary root, an established model for organ development, using the tractable Arabidopsis IRE1 mutant ire1a ire1b, which has marked root development defects in the absence of exogenous stress. We demonstrate that IRE1 is required to reach maximum rates of cell elongation and root growth. We also established that in the actively growing ire1a ire1b mutant root tips the Target of Rapamycin (TOR) kinase, a widely conserved pro-growth regulator, is hyperactive, and that, unlike cell proliferation, the rate of cell differentiation is enhanced in ire1a ire1b in a TOR-dependent manner. By functionally connecting two essential growth regulators, these results underpin a novel and critical role of IRE1 in organ development and indicate that, as cells exit an undifferentiated state, IRE1 is required to monitor TOR activity to balance cell expansion and maturation during organ biogenesis.
Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.
The DOD and NASA inertial upper stage communication system design, hardware specifications and interfaces were analyzed to determine their compatibility with the Orbiter payload communications equipment (Payload Interrogator, Payload Signal Processors, Communications Interface Unit, and the Orbiter operational communications equipment (the S-Band and Ku-band systems). Topics covered include (1) IUS/shuttle Orbiter communications interface definition; (2) Orbiter avionics equipment serving the IUS; (3) IUS communication equipment; (4) IUS/shuttle Orbiter RF links; (5) STDN/TDRS S-band related activities; and (6) communication interface unit/Orbiter interface issues. A test requirement plan overview is included.
It has been demonstrated on Earth that a low power, passive muon detector can penetrate deep into geological structures up to several kilometers in size providing high density images of their interiors. Muon tomography is an entirely new class of planetary instrumentation that is ideally suited to address key areas in Mars Science, such as: the search for life and habitable environments, the distribution and state of water and ice and the level of geologic activity on Mars today.
The Rpd3L histone deacetylase (HDAC) complex is an ancient 12-subunit complex conserved in a broad range of eukaryotes that performs localized deacetylation at or near sites of recruitment by DNA-bound factors. Here we describe the cryo-EM structure of this prototypical HDAC complex that is characterized by as many as seven subunits performing scaffolding roles for the tight integration of the only catalytic subunit, Rpd3. The principal scaffolding protein, Sin3, along with Rpd3 and the histone chaperone, Ume1, are present in two copies, with each copy organized into separate lobes of an asymmetric dimeric molecular assembly. The active site of one Rpd3 is completely occluded by a leucine side chain of Rxt2, while the tips of the two lobes and the more peripherally associated subunits exhibit varying levels of flexibility and positional disorder. The structure reveals unexpected structural homology/analogy between unrelated subunits in the fungal and mammalian complexes and provides a foundation for deeper interrogations of structure, biology, and mechanism of these complexes, as well as for the discovery of HDAC complex-specific inhibitors.
Transition metal dichalcogenides (TMDs) are attractive materials for a variety of applications in solar energy conversion and electrocatalysis, due to their favorable optical and electrical properties and their unique two-dimensional structures which facilitate the fabrication of wide-area, ultrathin layers. Unfortunately, the basal planes which make up the majority of these materials are relatively inert, and thus a great deal of effort has been directed to engineering favorable, catalytically active defects into these materials. In this paper, we demonstrate how probe-based electrochemical techniques can be employed as multifunctional tools for locally modifying TMD materials and probing the electrochemical behavior of the resulting defects. Scanning Electrochemical Cell Microscopy (SECCM) was employed to locally anodize exfoliated p-type WSe 2 nanosheets, creating hole-like defects within individual basal planes in a highly controllable fashion. Photoelectrochemical SECCM imaging was then employed to characterize the chemical behavior of these engineered defects, revealing significantly enhanced activity toward the Hydrogen Evolution Reaction (HER). Atomic force microscopy studies are presented which suggest these enhancements result from an increased density of monolayer-high step features within the anodized defects. Analysis of the SECCM data in the context of finite element simulations revealed that these enhancements increased with increasing anodization time, with local kinetic rates over 2 orders of magnitude higher than unaltered basal planes.
The space environment includes unique hazards like radiation and microgravity which can adversely affect biological systems. We assessed a multi-omics NASA GeneLab dataset where mice were hindlimb unloaded and/or gamma irradiated for 21 days followed by retinal analysis at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles resulting in a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation difference was seen across different conditions at the same time point. Nucleotide metabolism biological processes were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. A total of 23 genes showed significant changes in methylation and expression compared to unexposed controls, including genes involved in retinal function and inflammatory response. This multi-omics analysis interrogates the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination and highlights important molecular mechanisms at different post-exposure stages.
The buckling response of thin-walled cylindrical structures have long been shown to be sensitive to various imperfections. That is, imperfections related to load introduction, boundary conditions, material property variation, and geometric deviations can all contribute to experimentally obtained buckling loads being lower than the buckling loads predicted for perfect representations of the same thin-walled cylindrical structure. To account for the influence of geometry-based imperfections of a thin-walled cylindrical structure on buckling response, a design factor (also known as a buckling knockdown factor) is used during the design phase. Guidelines for buckling knockdown factors are readily available in NASA SP-8007, Buckling of Thin Walled Circular Cylinders, which was updated in 2020. Prior to this recent update, NASA SP-8007 had not been updated since 1969, and since that time, computational analysis, experimental testing, and manufacturing methods have significantly improved. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF, NESC Assessment 07-010-E) had the goal of developing buckling design recommendations for select classes of metallic and composite launch-vehicle structures [3]. Specifically, the test and analysis results from the fourth SBKF composite test article SBKF-P3-CYL-CTA8.2B, which is referred to as CTA8.2B, are described in this paper. This test was the fourth in a series of four tests on sandwich composite cylinders that will be used to experimentally validate analysis methods, which in turn can be used to develop new analysis-based shell buckling design guidelines for typical sandwich composite launch vehicle cylindrical structures. Publications describing previous test validation with analysis are available in Refs. CTA8.2B was designed to occupy one corner of the design space with approximately equal bending stiffnesses in the axial and transverse directions and have a larger ratio of radius to effective shell thickness. Each test article had a unique design and was designed to occupy a specific region of the design space. CTA8.2B was an 8-foot diameter honeycomb-core sandwich cylinder that was fabricated and tested at the NASA Marshall Space Flight Center (MSFC). The primary objectives of this test were to interrogate the structural capability of a composite test article, and to verify the test article design and analysis approach for cylinders subjected to axial compression and combined axial and bending loads. First, descriptions of the test article design and test are given in Section 2.0, and modeling and analysis methods used in support of the test article design and testing activities are described briefly in Section 3.0. Then, select test results are presented and compared to predicted results in Section 4.0, and concluding remarks are presented in Section 5.0. Finally, drawings of CTA8.2B and references used to support the test and analysis are provided in the Appendix.
Metal-ligand complexes have been extensively explored as well-defined molecular catalysts in small molecule activation reactions such as carbon dioxide (CO 2 ) reduction. Many hybrid photocatalysts have been prepared by coupling such complexes with photoactive surfaces for use in solar CO 2 reduction. In this work, we employ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies, density functional theory (DFT) and computational XANES modeling to interrogate the structure of a hybrid photocatalyst consisting of a macrocyclic cobalt complex deposited on graphitic carbon nitride (C 3 N 4 ). Results show that the cobalt complex binds on C 3 N 4 through surface OH or NH 2 groups. By refining the local geometry and binding sites of this well-defined molecular cobalt complex on C 3 N 4 , here we established an important benchmark for modeling a large class of molecular catalysts that can be adapted to in situ/operando studies and further enhanced by applying chemometrics-based approaches and machine learning methods of XANES data analysis.
Vitrimers exhibit high, processable viscosities, where other polymers do not, and are among the most promising polymers for closed-loop material circularity. We sought to investigate the underlying chemical kinetic factors that result in high viscosities for vitrimers, which are crucial to designing vitrimers with tunable viscosity. To interrogate these factors, we achieved the first simulated predictions of real vitrimer viscosities, using a novel kinetic Monte Carlo molecular dynamics method, overcoming the time and length scale gaps to predict experimental bulk viscosities. The vitrimer architecture investigated is based on poly(dimethylsiloxane) chains and vinylogous urethane bond swaps. We probed the effects of the extent of free swapping groups, %F, the activation energy, E A , and the steric factor, ρ. The steric factor is related to the intrinsic reaction probability for molecules with sufficient energy. All three factors were found to be significant, but the role of ρ was found to be the biggest and also the most underappreciated. The results show that the inclusion of accurate ρ is of critical importance for viscosity predictions, with the evidence suggesting that the typical assumption of ρ = 1 is not valid for vitrimers and that, indeed, very low steric factors are present in bond-swap vitrimers such that values of ρ < 10 –10 may be typical. This greatly influences the bond exchange rates and, ultimately, the viscosities. Recognition of this result is necessary for the prediction of vitrimer viscosities from molecular simulations and to make vitrimers by design from molecular dynamics. We also investigated the effects that E A , ρ, and the number of free swapping groups have upon vitreous range temperatures, TV, with respect to achieving a specific viscosity (η V = 1 × 10 8 Pa·s), as well as for a commonly reported higher viscosity extrapolation (η V = 1 × 10 12 Pa·s). The evidence suggests that vitrimers may follow universal curves for E A vs T V , as a function of ρ. Finally, this study achieves the first of these comparisons of molecular simulations to experiments and reveals critical insights toward creating vitrimers by design, while providing a route for the prediction of T V from kinetic Monte Carlo molecular dynamics simulations.
Fluctuations of residual amplitude modulation in a scheme of laser frequency stabilisation by a Fabry – Perot cavity reduce the frequency stability of the laser systems intended for interrogating clock transitions of atoms and ions. The dependences of the residual amplitude modulation on a temperature of the waveguide-based electro-optical modulator used for modulating the radiation phase and on polarisation of the radiation are measured. The parameters are found, at which the influence of the residual amplitude modulation on the frequency stability is minimal. A system for active compensation is created, which reduces the contribution of fluctuations of residual amplitude modulation to the instability down to 2.1 × 10{sup −16}, which makes it possible to reach the thermal noise limit of a silicon cryogenic cavity. (paper)
The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or M pro , is a promising target for the development of novel antiviral therapeutics. Previous X-ray crystal structures of M pro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded M pro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these data sets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a perturbation-dependent conformational landscape for M pro , including a mobile zinc ion interleaved between the catalytic dyad, mercurial conformational heterogeneity at various sites including a key substrate-binding loop, and a far-reaching intramolecular network bridging the active site and dimer interface. Our results may inspire new strategies for antiviral drug development to aid preparation for future coronavirus pandemics.