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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Liquid Jet Endstation for Hard X-ray Scattering and Spectroscopy at the Linac Coherent Light Source

The ability to study chemical dynamics on ultrafast timescales has greatly advanced with the introduction of X-ray free electron lasers (XFELs) providing short pulses of intense X-rays tailored to probe atomic structure and electronic configuration. Fully exploiting the full potential of XFELs requires specialized experimental endstations along with the development of techniques and methods to successfully carry out experiments. The liquid jet endstation (LJE) at the Linac Coherent Light Source (LCLS) has been developed to study photochemistry and biochemistry in solution systems using a combination of X-ray solution scattering (XSS), X-ray absorption spectroscopy (XAS), and X-ray emission spectroscopy (XES). The pump–probe setup utilizes an optical laser to excite the sample, which is subsequently probed by a hard X-ray pulse to resolve structural and electronic dynamics at their intrinsic femtosecond timescales. The LJE ensures reliable sample delivery to the X-ray interaction point via various liquid jets, enabling rapid replenishment of thin samples with millimolar concentrations and low sample volumes at the 120 Hz repetition rate of the LCLS beam. This paper provides a detailed description of the LJE design and of the techniques it enables, with an emphasis on the diagnostics required for real-time monitoring of the liquid jet and on the spatiotemporal overlap methods used to optimize the signal. Additionally, various scientific examples are discussed, highlighting the versatility of the LJE.

EXAFS↗
NASA NTRS1987

Results of the Life Sciences DSOs Conducted Aboard the Space Shuttle 1981-1986

Results are presented for a number of life sciences investigations sponsored by the Space Biomedical Research Institute at the NASA Lyndon B. Johnson Space Center and conducted as Detailed Supplementary Objectives (DSOs) on Space Shuttle flights between 1981 and 1986. An introduction and a description of the DSO program are followed by summary reports on the investigations. Reports are grouped into the following disciplines: Biochemistry and Pharmacology, Cardiovascular Effects and Fluid Shifts, Equipment Testing and Experiment Verification, Microbiology, Space Motion Sickness, and Vision. In the appendix, the status of every medical/life science DSO is presented in graphical form, which enables the flight history, the number of subjects tested, and the experiment results to be reviewed at a glance.

Vestibular Research↗
NASA NTRS1997

Entropy and charge in molecular evolution--the case of phosphate

Biopoesis, the creation of life, implies molecular evolution from simple components, randomly distributed and in a dilute state, to form highly organized, concentrated systems capable of metabolism, replication and mutation. This chain of events must involve environmental processes that can locally lower entropy in several steps; by specific selection from an indiscriminate mixture, by concentration from dilute solution, and in the case of the mineral-induced processes, by particular effectiveness in ordering and selective reaction, directed toward formation of functional biomolecules. Numerous circumstances provide support for the notion that negatively charged molecules were functionally required and geochemically available for biopoesis. Sulfite ion may have been important in bisulfite complex formation with simple aldehydes, facilitating the initial concentration by sorption of aldehydes in positively charged surface active minerals. Borate ion may have played a similar, albeit less investigated role in forming charged sugar complexes. Among anionic species, oligophosphate ions and charged phosphate esters are likely to have been of even more wide ranging importance, reflected in the continued need for phosphate in a proposed RNA world, and extending its central role to evolved biochemistry. Phosphorylation is shown to result in selective concentration by surface sorption of compounds, otherwise too dilute to support condensation reactions. It provides protection against rapid hydrolysis of sugars and, by selective concentration, induces the oligomerization of aldehydes. As a manifestation of life arisen, phosphate already appears in an organic context in the oldest preserved sedimentary record.

NASA Discipline Exobiology↗
NASA NTRS2013

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗
DOE OSTI2020

Special Issue on Nitrogenases and Homologous Systems

The nitrogenase superfamily comprises homologous enzyme systems that carry out fundamentally important processes, including the reduction of N 2 and CO, and the biosynthesis of bacteriochlorophyll and coenzyme F430. This special issue provides a cross-disciplinary overview of the ongoing research in this highly diverse and unique research area of metalloprotein biochemistry.

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

A successful start for mLife

mLife made its debut with the publication of the inaugurating issue on March 30, 2022. We are pleased to have published 42 high-quality articles, including reviews, research articles, and application notes, which cover microbial genetics, biochemistry and physiology, ecology and evolution, pathogenic and public health microbiology, and so forth. Nine of the articles concern technical innovations and applications in areas including genome editing, single-cell analysis, and database. To pay tribute to the great microbiologist Carl Woese on the 10th anniversary of his death, the Journal published a special section containing three thought-provoking articles in the last issue of the year. mLife and its collaborating publisher Wiley have made great efforts to increase the Journal's national and continental representation. As a result, the Journal received submissions from over 20 countries in five continents last year. The authors of the published articles are from China, United States, Great Britain, France, Canada, Ger many, Japan, Switzerland, and Austria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

X‐ray scattering reveals disordered linkers and dynamic interfaces in complexes and mechanisms for DNA double‐strand break repair impacting cell and cancer biology

Abstract Evolutionary selection ensures specificity and efficiency in dynamic metastable macromolecular machines that repair DNA damage without releasing toxic and mutagenic intermediates. Here we examine non‐homologous end joining (NHEJ) as the primary conserved DNA double‐strand break (DSB) repair process in human cells. NHEJ has exemplary key roles in networks determining the development, outcome of cancer treatments by DSB‐inducing agents, generation of antibody and T‐cell receptor diversity, and innate immune response for RNA viruses. We determine mechanistic insights into NHEJ structural biochemistry focusing upon advanced small angle X‐ray scattering (SAXS) results combined with X‐ray crystallography (MX) and cryo‐electron microscopy (cryo‐EM). SAXS coupled to atomic structures enables integrated structural biology for objective quantitative assessment of conformational ensembles and assemblies in solution, intra‐molecular distances, structural similarity, functional disorder, conformational switching, and flexibility. Importantly, NHEJ complexes in solution undergo larger allosteric transitions than seen in their cryo‐EM or MX structures. In the long‐range synaptic complex, X‐ray repair cross‐complementing 4 (XRCC4) plus XRCC4‐like‐factor (XLF) form a flexible bridge and linchpin for DNA ends bound to KU heterodimer (Ku70/80) and DNA‐PKcs (DNA‐dependent protein kinase catalytic subunit). Upon binding two DNA ends, auto‐phosphorylation opens DNA‐PKcs dimer licensing NHEJ via concerted conformational transformations of XLF‐XRCC4, XLF–Ku80, and LigIV BRCT –Ku70 interfaces. Integrated structures reveal multifunctional roles for disordered linkers and modular dynamic interfaces promoting DSB end processing and alignment into the short‐range complex for ligation by LigIV. Integrated findings define dynamic assemblies fundamental to designing separation‐of‐function mutants and allosteric inhibitors targeting conformational transitions in multifunctional complexes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Characterization of protein–ligand binding interactions of enoyl-ACP reductase ( FabI ) by native MS reveals allosteric effects of coenzymes and the inhibitor triclosan

The enzyme enoyl-ACP reductase (also called FabI in bacteria) is an essential member of the fatty acid synthase II pathway in plants and bacteria. This enzyme is the target of the antibacterial drug triclosan and has been the subject of extensive studies for the past 20 years. Despite the large number of reports describing the biochemistry of this enzyme, there have been no studies that provided direct observation of the protein and its various ligands. In this paper we describe the use of native MS to characterize the protein–ligand interactions of FabI with its coenzymes NAD + and NADH and with the inhibitor triclosan. Measurements of the gas-phase affinities of the enzyme for these ligands yielded values that are in close agreement with solution-phase affinity measurements. Additionally, FabI is a homotetramer and we were able to measure the affinity of each subunit for each coenzyme, which revealed that both coenzymes exhibit a positive homotropic allosteric effect. An allosteric effect was also observed in association with the inhibitor triclosan. These observations provide new insights into this well-studied enzyme and suggest that there may still be gaps in the existing mechanistic models that explain FabI inhibition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes

Abstract Predicting the structure of multi‐protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage predefined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any precomputed physics‐inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end‐to‐end learning from molecular structures containing tens of thousands of atoms: a point‐based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems.

Eismann, Stephan↗