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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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Inhibition of Low Molecular Weight Protein Tyrosine Phosphatase by an Induced-Fit Mechanism
Abstract not provided
No One Size Fits All: Semiconductor Nanocrystal Sizing Curves
Although colloidal quantum dots or nanocrystals (NCs) are now long past their infancy, there remain basic issues that must be addressed to fully establish their fundamental, size-dependent properties. This is especially true for model systems such as CdSe where confinement effects are responsible for changes in their optical response and where significant effort has been invested in developing theories of their underlying electronic structure. Surprisingly, there still appears to be a lack of consensus on one of the most fundamental metrics for NCs, their sizing curves. As shown here, these are empirical functions that link the size of isotropically shaped semiconductor NCs (such as the diameter, d, for spherical NCs and edge length, l, for cube-shaped ones) to corresponding changes in optical response.
Comparing Morphological Evolution during Tensile Deformation of Two Precise Polyethylenes via 2D Fitting of in Situ X-ray Scattering
Some types of precise polyethylenes, or linear polyethylenes containing precisely periodic functional groups, exhibit significant strain hardening under tensile deformation. In this work we perform in situ X-ray scattering during tensile deformation of two precise polyethylenes: one with pendant carboxylic acid groups every 21st carbon (p21AA) and another with pendant imidazolium bromide groups every 15th carbon (p15ImBr). p21AA exhibits significant strain hardening and its layered structure orients with the layer normal along the tensile axis, while p15ImBr does not exhibit strain hardening and its layer normal orients perpendicular to the tensile axis. Quantitative evaluation of the 2D fiber patterns shows that p21AA undergoes a morphological transition, from a semicrystalline structure to a nanofibrillar structure, while the morphology of p15ImBr reorients and the chain folding structure is preserved. This suggests that fibrillization plays an important role in the strain hardening mechanism.
Small Molecule Inhibitors of the BfrB–Bfd Interaction Decrease Pseudomonas aeruginosa Fitness and Potentiate Fluoroquinolone Activity
The iron storage protein bacterioferritin (BfrB) is central to bacterial iron homeostasis. The mobilization of iron from BfrB, which requires binding by a cognate ferredoxin (Bfd), is essential to the regulation of cytosolic iron levels in P. aeruginosa . This paper describes the structure-guided development of small molecule inhibitors of the BfrB–Bfd protein–protein interaction. The process was initiated by screening a fragment library and followed by obtaining the structure of a fragment hit bound to BfrB. The structural insights were used to develop a series of 4-(benzylamino)- and 4-((3-phenylpropyl)amino)-isoindoline-1,3-dione analogs that selectively bind BfrB at the Bfd binding site. Challenging P. aeruginosa cells with the 4-substituted isoindoline analogs revealed a dose-dependent growth phenotype. Further investigation determined that the analogs elicit a pyoverdin hyperproduction phenotype that is consistent with blockade of the BfrB–Bfd interaction and ensuing irreversible accumulation of iron in BfrB, with concomitant depletion of iron in the cytosol. The irreversible accumulation of iron in BfrB prompted by the 4-substituted isoindoline analogs was confirmed by visualization of BfrB-iron in P. aeruginosa cell lysates separated on native PAGE gels and stained for iron with Ferene S. Challenging P. aeruginosa cultures with a combination of commercial fluoroquinolone and our isoindoline analogs results in significantly lower cell survival relative to treatment with either antibiotic or analog alone. Collectively, these findings furnish proof of concept for the usefulness of small molecule probes designed to dysregulate bacterial iron homeostasis by targeting a protein–protein interaction pivotal for iron storage in the bacterial cell.
Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?
The Global Carbon Project estimates that the terrestrial biosphere has absorbed about one-third of anthropogenic CO 2 emissions during the 1959–2019 period. This sink-estimate is produced by an ensemble of terrestrial biosphere models and is consistent with the land uptake inferred from the residual of emissions and ocean uptake. The purpose of our study is to understand how well terrestrial biosphere models reproduce the processes that drive the terrestrial carbon sink. One challenge is to decide what level of agreement between model output and observation-based reference data is adequate considering that reference data are prone to uncertainties. To define such a level of agreement, we compute benchmark scores that quantify the similarity between independently derived reference data sets using multiple statistical metrics. Models are considered to perform well if their model scores reach benchmark scores. Our results show that reference data can differ considerably, causing benchmark scores to be low. Model scores are often of similar magnitude as benchmark scores, implying that model performance is reasonable given how different reference data are. While model performance is encouraging, ample potential for improvements remains, including a reduction in a positive leaf area index bias, improved representations of processes that govern soil organic carbon in high latitudes, and an assessment of causes that drive the inter-model spread of gross primary productivity in boreal regions and humid tropics. The success of future model development will increasingly depend on our capacity to reduce and account for observational uncertainties.
Major antigenic site B of human influenza H3N2 viruses has an evolving local fitness landscape
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Epistasis shapes the fitness landscape of an allosteric specificity switch
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The interplay of additivity, dominance, and epistasis on fitness in a diploid yeast cross
In diploid species, genetic loci can show additive, dominance, and epistatic effects. To characterize the contributions of these different types of genetic effects to heritable traits, we use a double barcoding system to generate and phenotype a panel of ~200,000 diploid yeast strains that can be partitioned into hundreds of interrelated families. This experiment enables the detection of thousands of epistatic loci, many whose effects vary across families. Here, we show traits are largely specified by a small number of hub loci with major additive and dominance effects, and pervasive epistasis. Genetic background commonly influences both the additive and dominance effects of loci, with multiple modifiers typically involved. The most prominent dominance modifier in our data is the mating locus, which has no effect on its own. Our findings show that the interplay between additivity, dominance, and epistasis underlies a complex genotype-to-phenotype map in diploids.
Self-driving laboratories to autonomously navigate the protein fitness landscape
Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.
The origin of the Debye relaxation in liquid water and fitting the high frequency excess response
Debye relaxation in the microwave/THz region of the dielectric spectra of water is related to propagation of defects.
Small molecule binders recognize DNA microstructural variations via an induced fit mechanism
Site-specific recognition through contacts, water displacement, and dynamics of a linked azabenzimidazole-diamidine within the DNA minor groove.
Filling the gap with a bulky diaryl boron group: fluorinated and non-fluorinated copper pyrazolates fitted with a dimesityl boron moiety on the backbone
Successful synthesis has been reported of 4-Mes 2 B-3,5-(CF 3 ) 2 PzH and 4-Mes 2 B-3,5-(CF 3 ) 2 PzH bearing sterically demanding diarylboron moieties at the pyrazole ring 4-position, and their corresponding copper(I) pyrazolate complexes. They show visible blue photoluminescence in solution. The X-ray crystal structures revealed that the fluorinated {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 crystallizes as discrete trinuclear molecules whereas as the non-fluorinated {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 forms dimers of trimers with two close inter-trimer Cu···Cu separations. The solid {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 featuring a sterically confined Cu 3 N 6 core displays bright blue phosphorescence while {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 , which is a dimer of a trimer, is a red phosphor at room temperature. Here, this work illustrates the modulation of photo-physical properties of metal pyrazolates by adjusting the supporting ligand steric features and introducing secondary diarylboron luminophores. Computational analysis of the structures and photophysical properties of copper complexes are also presented.
Evaluation of the 235 U resonance parameters to fit the standard recommended values
A great deal of effort has been dedicated to the revision of the standard values in connection with the neutron interaction for some actinides. While standard data compilation are available for decades nuclear data evaluations included in existing nuclear data libraries (ENDF, JEFF, JENDL, etc.) do not follow the standard recommended values. Indeed, the majority of evaluations for major actinides do not conform to the standards whatsoever. In particular, for the n + 235 U interaction the only value in agreement with the standard is the thermal fission cross section. We performed a resonance re-evaluation of the n + 235 U interaction in order to address the issues regarding standard values in the energy range from 10-5 eV to 2250 eV. Recently, 235 U fission cross-section measurements have been performed at the CERN Neutron Time-o-Flight facility (TOF), known as n_TOF, in the energy range from 0.7 eV to 10 keV. The data were normalized according to the recommended standard of the fission integral in the energy range 7.8 eV to 11 eV. As a result, the n_TOF averaged fission cross sections above 100 eV are in good agreement with the standard recommended values. The n_TOF data were included in the 235 U resonance analysis that was performed with the code SAMMY. In addition to the average standard values related to the fission cross section, standard thermal values for fission, capture, and elastic cross sections were also included in the evaluation. Our paper presents the procedure used for re-evaluating the 235 U resonance parameters including the recommended standard values as well as new cross section measurements.
ML Track Fitting in Nuclear Physics
Charged particle tracking represents the largest consumer of CPU resources in high data volume Nuclear Physics (NP) experiments. An effort is underway to develop machine learning (ML) networks that will reduce the resources required for charged particle tracking. Tracking in NP experiments represent some unique challenges compared to high energy physics (HEP). In particular, track finding typically represents only a small fraction of the overall tracking problem in NP. This presentation will outline the differences and similarities between NP and HEP charged particle tracking and areas where ML learning may provide a benefit. The status of the specific effort taking place at Jefferson Lab will also be shown.
Interchange, Extension and Validation of R-matrix fits for gamma production
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