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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

neuropsychological↗
DOE OSTI2023

Discovery of the Azaserine Biosynthetic Pathway Uncovers a Biological Route for α‐Diazoester Production

Abstract Azaserine is a bacterial metabolite containing a biologically unusual and synthetically enabling α‐diazoester functional group. Herein, we report the discovery of the azaserine ( aza ) biosynthetic gene cluster from Glycomyces harbinensis . Discovery of related gene clusters reveals previously unappreciated azaserine producers, and heterologous expression of the aza gene cluster confirms its role in azaserine assembly. Notably, this gene cluster encodes homologues of hydrazonoacetic acid (HYAA)‐producing enzymes, implicating HYAA in α‐diazoester biosynthesis. Isotope feeding and biochemical experiments support this hypothesis. These discoveries indicate that a 2‐electron oxidation of a hydrazonoacetyl intermediate is required for α‐diazoester formation, constituting a distinct logic for diazo biosynthesis. Uncovering this biological route for α‐diazoester synthesis now enables the production of a highly versatile carbene precursor in cells, facilitating approaches for engineering complete carbene‐mediated biosynthetic transformations in vivo.

Van Cura, Devon↗
DOE OSTI2023

Discovery of the Azaserine Biosynthetic Pathway Uncovers a Biological Route for α‐Diazoester Production

Abstract Azaserine is a bacterial metabolite containing a biologically unusual and synthetically enabling α‐diazoester functional group. Herein, we report the discovery of the azaserine ( aza ) biosynthetic gene cluster from Glycomyces harbinensis . Discovery of related gene clusters reveals previously unappreciated azaserine producers, and heterologous expression of the aza gene cluster confirms its role in azaserine assembly. Notably, this gene cluster encodes homologues of hydrazonoacetic acid (HYAA)‐producing enzymes, implicating HYAA in α‐diazoester biosynthesis. Isotope feeding and biochemical experiments support this hypothesis. These discoveries indicate that a 2‐electron oxidation of a hydrazonoacetyl intermediate is required for α‐diazoester formation, constituting a distinct logic for diazo biosynthesis. Uncovering this biological route for α‐diazoester synthesis now enables the production of a highly versatile carbene precursor in cells, facilitating approaches for engineering complete carbene‐mediated biosynthetic transformations in vivo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Encapsulation Enhances the Quantum Coherence of a Solid‐State Molecular Spin Qubit

Spins within molecules benefit from the atomistic control of synthetic chemistry for the realization of qubits. One advantage is that the quantum superpositions of the spin states encoding the qubit can be coherently manipulated using electromagnetic radiation. The main challenge is the fragility of these superpositions when qubits are to partake of solid-state devices. We address this issue with a supramolecular approach for protecting molecular spin qubits against decoherence. The molecular qubit [Cr(ox)3]3- has been encapsulated inside the diamagnetic triple-stranded helicate [Zn2L3]4+ (L is a bis-pyrazolylpyridine ligand). The quantum coherence of the protected qubit is then analyzed with pulsed EPR spectroscopy and compared with the unprotected qubit, both in solution and in the solid state. Crucially, the spin-spin relaxation in the solid state has been examined within diamagnetic crystal lattices of the isostructural ([Al(ox)3]@[Zn2L3])+ or [Al(ox)3]3- assemblies, respectively, doped with the Cr3+ qubit in two different (<10%) concentrations. The study unveils a surprising increase of the phase memory time of the qubit upon encapsulation only in the solid. Spin-lattice relaxation times also exhibit a significant enhancement, as established from inversion recovery pulse sequences and from slow relaxation of the magnetization of the protected qubit, not featured by the free qubit.

Swain, Abinash↗
DOE OSTI2023

Proxy quality control of biomass particles using thermogravimetric analysis and Gaussian process regression models

Abstract The temperature experienced by reactants during preparation in a reactor is a key component in determining the yield and homogeneity of usable chemical products such as biomass particles. Thermocouples with sensors can be used to monitor spatial temperature gradients within reactors but these sensors are often too expensive and/or invasive. The present work proposes a strategy to identify optimal machine learning models to infer the maximum effective temperature experienced by particles during oxidative biomass torrefaction using key thermochemical combustion parameters. The maximum rate of weight loss, the corresponding temperature, and fixed carbon content on a dry‐ash‐free basis are used as literature‐based predictor variables obtained from thermogravimetric analysis. The evaluation of 24 machine‐learning models using the standard tenfold cross‐validation method suggests that the exponential Gaussian process regression (GPR) model is the most effective, followed by other GPR models. These high‐performing GPR models were also utilized to predict the effective preparation temperature distribution of reactor‐produced biomass particles under eight conditions of varying residence time and air‐to‐biomass ratio. The effective preparation temperature and residence time of individual biomass particles were then encoded into the torrefaction severity factor and used to estimate the energy yield of the reactor output as a novel quality control method. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2021

The tree of life describes a tripartite cellular world

The canonical view of a 3-domain (3D) tree of life was recently challenged by the discovery of Asgardarchaeota encoding eukaryote signature proteins (ESPs), which were treated as missing links of a 2-domain (2D) tree. Here we revisit the debate. We discuss methodological limitations of building trees with alignment-dependent approaches, which often fail to satisfactorily address the problem of ‘‘gaps.’’ In addition, most phylogenies are reconstructed unrooted, neglecting the power of direct rooting methods. Alignment-free methodologies lift most difficulties but require employing realistic evolutionary models. We argue that the discoveries of Asgards and ESPs, by themselves, do not rule out the 3D tree, which is strongly supported by comparative and evolutionary genomic analyses and vast genomic and biochemical superkingdom distinctions. Given uncertainties of retrodiction and interpretation difficulties, we conclude that the 3D view has not been falsified but instead has been strengthened by genomic analyses. In turn, the objections to the 2D model have not been lifted. The debate remains open. Also see the video abstract here: https://youtu.be/-6TBN0bubI8

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enzyme selection, optimization, and production toward biodegradation of post–consumer poly(ethylene terephthalate) at scale

Poly(ethylene terephthalate) (PET) is one of the world's most widely used polyester plastics. Due to its chemical stability, PET is extremely difficult to hydrolyze in a natural environment. Recent discoveries in new polyester hydrolases and breakthroughs in enzyme engineering strategies have inspired enormous research on biorecycling of PET. This study summarizes our research efforts toward large-scale, efficient, and economical biodegradation of post-consumer waste PET, including PET hydrolase selection and optimization, high-yield enzyme production, and high-capacity enzymatic degradation of post-consumer waste PET. First, genes encoding PETase and MHETase from Ideonella sakaiensis and the ICCG variant of leaf-branch compost cutinase (LCC ICCG ) were codon-optimized and expressed in Escherichia coli BL21(DE3) for high-yield production. To further lower the enzyme production cost, a pelB leader sequence was fused to LCC ICCG so that the enzyme can be secreted into the medium to facilitate recovery. To help bind the enzyme on the hydrophobic surface of PET, a substrate-binding module in a polyhydroxyalkanoate depolymerase from Alcaligenes faecalis (PBM) was fused to the C-terminus of LCC ICCG . The resulting four different LCC ICCG variants (LCC, PelB-LCC, LCC-PBM, and PelB-LCC-PBM), together with PETase and MHETase, were compared for PET degradation efficiency. A fed-batch fermentation process was developed to produce the target enzymes up to 1.2 g L –1 . Finally, the best enzyme, PelB-LCC, was selected and used for the efficient degradation of 200 g L –1 recycled PET in a well-controlled, stirred-tank reactor. Furthermore, the results will help develop an economical and scalable biorecycling process toward a circular PET economy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Hijacking Translation Initiation for Synthetic Biology

Genetic code expansion (GCE) has revolutionized the field of protein chemistry. Over the past several decades more than 150 different noncanonical amino acids (ncAAs) have been co-translationally installed into proteins within various host organisms. Further, the vast majority of these ncAAs have been incorporated between the start and stop codons within an open reading frame. This requires that the ncAA be able to form a peptide bond at the α-amine, limiting the types of molecules that can be genetically encoded. In contrast, the α-amine of the initiating amino acid is not required for peptide bond formation. Therefore, including the initiator position in GCE allows for co-translational insertion of more diverse molecules that are modified, or completely lacking an α-amine. This review explores various methods which have been used to initiate protein synthesis with diverse molecules both in vitro and in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization of a Mo-Nitrogenase Variant Containing a Citrate-Substituted Cofactor

Nitrogenase converts N 2 to NH 3 , and CO to hydrocarbons, at its cofactor site. In this work, we report a biochemical and spectroscopic characterization of a Mo-nitrogenase variant expressed in an Azotobacter vinelandii strain containing a deletion of nifV, the gene encoding the homocitrate synthase. Designated NifDK Cit , the catalytic component of this Mo-nitrogenase variant contains a citrate-substituted cofactor analogue. Activity analysis of NifDK Cit reveals a shift of CO reduction from H 2 evolution toward hydrocarbon formation and an opposite shift of N 2 reduction from NH 3 formation toward H 2 evolution. Consistent with a shift in the Mo K-edge energy of NifDK Cit relative to that of its wild-type counterpart, EPR analysis demonstrates a broadening of the line-shape and a decrease in the intensity of the cofactor-originated S=3/2 signal, suggesting a change in the spin properties of the cofactor upon citrate substitution. These observations point to a crucial role of homocitrate in substrate reduction by nitrogenase and the possibility to tune product profiles of nitrogenase reactions via organic ligand substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structures and Mechanisms of a Novel Bacterial Transport System for Fatty Acids

Abstract Bacterial acquisition of metabolites is largely facilitated by transporters with unique substrate scopes. The tripartite ATP‐independent periplasmic (TRAP) transporters comprise a large family of bacterial proteins that facilitate the uptake of a variety of small molecules. It has been reported that some TRAP systems encode a fourth protein, the T component. The T‐component, or TatT, is predicted to be a periplasmic‐facing lipoprotein that enables the uptake of metabolites from the outer membrane. However, no substrates were revealed for any TatT and their functional role(s) remained enigmatic. We recently identified a homolog in Methylococcus capsulatus that binds to sterols, and herein, we report two additional homologs that demonstrate a preference for long‐chain fatty acids. Our bioinformatics, quantitative analyses of protein‐ligand interactions, and high‐resolution crystal structures suggest that TatTs might facilitate the trafficking of hydrophobic or lipophilic substrates and represent a new class of bacterial lipid and fatty acid transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification of quantitative trait loci for sorghum leaf blight resistance

Sorghum leaf blight and northern corn leaf blight, both caused by Exserohilum turcicum {(Pass.) K. J. Leonard and Suggs [syn. Setosphaeria turcica (Luttr.) K. J. Leonard and Suggs.]}, are major diseases of sorghum [Sorghum bicolor (L.) Moench] and maize (Zea mays L.), respectively. Examining the genetic architecture of resistance in sorghum will lead to a better understanding of the relationship between resistance in sorghum and maize, which can ultimately enhance management options in both crops. In 2018 and 2019, we evaluated two sorghum recombinant inbred line (RIL) populations for resistance to E. turcicum. The BTx623 × IS3620C and BTx623 × SC155 populations consisted of 235 and 81 RILs, respectively. Resistance in both populations was moderately to highly heritable. We identified a total of six quantitative trait loci (QTL) across the two populations. Three QTL with small- to moderate-effect sizes were identified in the BTx623 × IS3620C population. Three QTL, including a large-effect QTL on chromosome three that explained 24% of the variation, were identified in the BTx623 × SC155 population. We compared the identified QTL with the position of northern corn leaf blight candidate genes and found eight candidate resistance gene orthologs that colocalize with the sorghum leaf blight QTL. There were also several nucleotide-binding leucine-rich repeat encoding genes within the candidate intervals. Understanding host resistance in multiple species furthers our understanding of the Exserohilum turcicum patho-system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

In–context promoter bashing of the Sorghum bicolor gene models functionally annotated as bundle sheath cell preferred expressing phosphoenolpyruvate carboxykinase and alanine aminotransferase

In-context promoter bashing via genome editing is a route to identify and characterize critical regulatory regions that govern expression of genes of interest. The outcomes of in-context promoter bashing can be used to inform editing strategies to modulate the expression of selected gene models in a desired fashion. Here, we employed in-context promoter bashing to characterize the proximal upstream regulatory regions of sorghum genes encoding phosphoenolpyruvate carboxykinase bundle sheath (SbPEPCK.BS, SbiTx430.01G455400) and alanine aminotransferase bundle sheath (SbAlaAT.BS, SbiTx430.02G006600), two proteins involved in the PCK C 4 pathway. Characterized germinal edits within the targeted regions upstream of these two genes ranged in size from 138 up to 1790 bp. A 138 bp within the SbPEPCK.BS upstream region and a 1643 bp element within the SbAlaAT.BS upstream region were determined to be important for maintenance of transcription levels. No change in development or various physiological parameters was observed in characterized lineages carrying promoter edits. However, significant changes in seed reserves and a reduction in 100-seed weight were consistently observed, under both greenhouse and field environments, in plants carrying an edit in the promoter of SbPEPCK.BS gene, which were significantly reduced in transcript accumulation for this gene.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Compactly‐Supported Nonstationary Kernels for Computing Exact Gaussian Processes on Big Data

The Gaussian process (GP) is a widely used method for analyzing large-scale data sets, including spatio-temporal measurements of nonlinear processes that are now commonplace in the environmental sciences. Traditional implementations of GPs involve stationary kernels (also termed covariance functions) that limit their flexibility, and exact methods for inference that prevent application to data sets with more than about 10,000 points. Modern approaches to address stationarity assumptions generally fail to accommodate large data sets, while all attempts to address scalability focus on approximating the Gaussian likelihood, which can involve subjectivity and lead to inaccuracies. In this work, we explicitly derive an alternative kernel that can discover and encode both sparsity and nonstationarity. We embed the kernel within a fully Bayesian GP model and leverage high-performance computing resources to enable the analysis of massive data sets. We demonstrate the favorable performance of our novel kernel relative to existing exact and approximate GP methods across a variety of synthetic data examples. Furthermore, we conduct space–time prediction based on more than 1 million measurements of daily maximum temperature and verify that our results outperform state-of-the-art methods in the Earth sciences. More broadly, having access to exact GPs that use ultra-scalable, sparsity-discovering, nonstationary kernels allows GP methods to truly compete with a wide variety of machine learning methods.

Gaussian processes↗
DOE OSTI2020

The sodium channel Na X : Possible player in excitation–contraction coupling

Abstract The sodium channel Na X (encoded by the SCN7A gene) was originally identified in the heart and skeletal muscle and is structurally similar to the other voltage‐gated sodium channels but does not appear to be voltage gated. Although Na X is expressed at high levels in cardiac and skeletal muscle, little information exists on the function of Na X in these tissues. Transcriptional profiling of ion channels in the heart in a subset of patients with Brugada syndrome revealed an inverse relationship between the expression of Na X and Na V 1.5 suggesting that, in cardiac myocytes, the expression of these channels may be linked. We propose that Na X plays a role in excitation–contraction coupling based on our experimental observations. Here we show that in cardiac myocytes, Na X is expressed in a striated pattern on the sarcolemma in regions corresponding to the sarcomeric M‐line. Knocking down Na X expression decreased Na V 1.5 mRNA and protein and reduced the inward sodium current ( I Na+ ) following cell depolarization. When the expression of Na V 1.5 was knocked down, ~85% of the I Na+ was reduced consistent with the observations that Na V 1.5 is the main voltage‐gated sodium channel in cardiac muscle and that Na X likely does not directly participate in mediating the I Na+ following depolarization. Silencing Na V 1.5 expression led to significant upregulation of Na X mRNA. Similar to Na V 1.5, Na X protein levels were rapidly downregulated when the intracellular [Ca 2+ ] was increased either by CaCl 2 or caffeine. These data suggest that a relationship exists between Na X and Na V 1.5 and that Na X may play a role in excitation–contraction coupling.

Bogdanovic, Elena↗
DOE OSTI2023

Engineering Super–Poissonian Photon Statistics of Spatial Light Modes

The nature of light sources is defined by the statistical fluctuations of the electromagnetic field. As such, the photon statistics of light sources are typically associated with distinct emitters. Here, the possibility of producing light beams with various photon statistics through the spatial modulation of coherent light is demonstrated. This is achieved by the sequential encoding of controllable Kolmogorov phase screens in a digital micromirror device. Interestingly, the flexibility of this scheme allows for the shaping of spatial light modes with engineered photon statistics at different spatial positions. The performance of this scheme is assessed through the photon-number-resolving characterization of different families of spatial light modes with engineered photon statistics. Furthermore, it is believed that the possibility of controlling the photon fluctuations of the light field at arbitrary spatial locations has important implications for quantum spectroscopy, sensing, and imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗
DOE OSTI2024

Methyl α‐D‐galactopyranosyl‐(1→3)‐β‐D‐galactopyranoside and methyl β‐D‐galactopyranosyl‐(1→3)‐β‐D‐galactopyranoside: Glycosidic linkage conformation determined from MA'AT analysis

Abstract MA'ATanalysis has been applied to two biologically‐importantO‐glycosidic linkages in two disaccharides, α‐D‐Galp‐(1→3)‐β‐D‐GalpOMe (3) and β‐D‐Galp‐(1→3)‐β‐D‐GalpOMe (4). Using density functional theory (DFT) to obtain parameterized equations relating a group of trans‐O‐glycosidic NMR spin‐couplings to eitherphi(ϕ') orpsi(ψ'), and experimental 3 J COCH , 2 J COC , and 3 J COCC spin‐couplings measured in aqueous solution in 13 C‐labeled isotopomers, probability distributions ofϕ'andψ'in each linkage were determined and compared to those determined by aqueous 1‐μs molecular dynamics (MD) simulation. Good agreement was found between theMA'ATand single‐state MD conformational models of these linkages for the most part, with modest (approximately <15°) differences in the mean values ofϕ'andψ', although the envelope of allowed angles (encoded in circular standard deviations or CSDs) is consistently larger forϕ'determined fromMA'ATanalysis than from MD for both linkages. TheMA'ATmodel of the α‐Galp‐(1→3)‐β‐Galplinkage agrees well with those determined previously using conventional NMR methods ( 3 J COCH values and/or 1 H‐ 1 H NOEs), but some discrepancy was observed for the β‐Galp‐(1→3)‐β‐Galplinkage, which may arise from errors in the conventions used to describe the linkage torsion angles. Statistical analyses of X‐ray crystal structures show ranges ofϕ'andψ'for both linkages that include the mean angles determined fromMA'ATanalyses, although both angles adopt a wide range of values in the crystalline state, withϕ'in β‐Galp‐(1→3)‐β‐Galplinkages showing greater‐than‐expected conformational variability.

Chemistry↗