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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Alternative Binding Modes Identified for Growth and Differentiation Factor-associated Serum Protein (GASP) Family Antagonism of Myostatin

Myostatin, a member of the TGF-β family of ligands, is a strong negative regulator of muscle growth. As such, it is a prime therapeutic target for muscle wasting disorders. Similar to other TGF-β family ligands, myostatin is neutralized by binding one of a number of structurally diverse antagonists. Included are the antagonists GASP-1 and GASP-2, which are unique in that they specifically antagonize myostatin. However, little is known from a structural standpoint describing the interactions of GASP antagonists with myostatin. In this paper, we present the First low resolution solution structure of myostatin-free and myostatin-bound states of GASP-1 and GASP-2. Our studies have revealed GASP-1, which is 100 times more potent than GASP-2, preferentially binds myostatin in an asymmetrical 1:1 complex, whereas GASP-2 binds in a symmetrical 2:1 complex. Additionally, C-terminal truncations of GASP-1 result in less potent myostatin inhibitors that form a 2:1 complex, suggesting that the C-terminal domains of GASP-1 are the primary mediators for asymmetric complex formation. Overall, this study provides a new perspective on TGF-β antagonism, where closely related antagonists can utilize different ligand-binding strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Structure of Human B 12 Trafficking Protein CblD Reveals Molecular Mimicry and Identifies a New Subfamily of Nitro-FMN Reductases

In mammals, B12 (or cobalamin) is an essential cofactor required by methionine synthase and methylmalonyl-CoA mutase. A complex intracellular pathway supports the assimilation of cobalamin into its active cofactor forms and delivery to its target enzymes. MMADHC (the methylmalonic aciduria and homocystinuria type D protein), commonly referred to as CblD, is a key chaperone involved in intracellular cobalamin trafficking, and mutations in CblD cause methylmalonic aciduria and/or homocystinuria. Herein, we report the first crystal structure of the globular C-terminal domain of human CblD, which is sufficient for its interaction with MMADHC (the methylmalonic aciduria and homocystinuria type C protein), or CblC, and for supporting the cytoplasmic cobalamin trafficking pathway. CblD contains an α+β fold that is structurally reminiscent of the nitro-FMN reductase superfamily. Two of the closest structural relatives of CblD are CblC, a multifunctional enzyme important for cobalamin trafficking, and the activation domain of methionine synthase. CblD, CblC, and the activation domain of methionine synthase share several distinguishing features and, together with two recently described corrinoid-dependent reductive dehalogenases, constitute a new subclass within the nitro-FMN reductase superfamily. We demonstrate that CblD enhances oxidation of cob(II)alamin bound to CblC and that disease-causing mutations in CblD impair the kinetics of this reaction. Here, the striking structural similarity of CblD to CblC, believed to be contiguous in the cobalamin trafficking pathway, suggests the co-option of molecular mimicry as a strategy for achieving its function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Functional metagenomics identifies an exosialidase with an inverting catalytic mechanism that defines a new glycoside hydrolase family (GH156)

Exosialidases are glycoside hydrolases that remove a single terminal sialic acid residue from oligosaccharides. They are widely distributed in biology, having been found in prokaryotes, eukaryotes, and certain viruses. Most characterized prokaryotic sialidases are from organisms that are pathogenic or commensal with mammals. However, in this study, we used functional metagenomic screening to seek microbial sialidases encoded by environmental DNA isolated from an extreme ecological niche, a thermal spring. Using recombinant expression of potential exosialidase candidates and a fluorogenic sialidase substrate, we discovered an exosialidase having no homology to known sialidases. Phylogenetic analysis indicated that this protein is a member of a small family of bacterial proteins of previously unknown function. Proton NMR revealed that this enzyme functions via an inverting catalytic mechanism, a biochemical property that is distinct from those of known exosialidases. This unique inverting exosialidase defines a new CAZy glycoside hydrolase family we have designated GH156

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Video-Based Electroshocking Platform to Identify Lamprey Ammocoete Habitats: Field Validation and New Discoveries in the Columbia River Basin

A deep water electroshocking platform (DEP), developed to characterize larval lampreys (ammocoetes) and associated habitat in depths up to 15 m, was recently tested in the field. The DEP samples 0.55 m2∙min-1 without requiring ammocoete transport to the surface. Searches were conducted at a known rearing location (mouth of the Wind River, WA) and at locations on the Cowlitz River, WA, where ammocoetes had not previously been found. At the mouth of the Wind River, video imaged ammocoetes ranged from 50 to 150 mm in water depths between 1.5 m and 4.5 m and were more common in sediments containing organic silt. Ammocoetes (n=137) were detected at 61% of locations sampled (summer) and 50% of the locations sampled (winter). Following the field verification, the DEP was used on the lower 11.7 km of the Cowlitz River, WA. Ammocoetes (n=41) were found with a detection rate of 26% at specific search locations. Cowlitz River sediment containing ammocoetes was also dominated by silt with organic material, often downstream of alluvial bars in water depths from 0.8 to 1.7 m. Test results indicated a high sampling efficiency, favorable detection rates, and little or no impact to ammocoetes and their surrounding benthic environments.

Cowlitz River↗
DOE OSTI2025

Identifying rolling resistance and air resistance simultaneously for an electric truck

Accurately estimating rolling and air resistance is essential for predicting the energy consumption of vehicles. This study presents a field-based approach using a rolldown test to simultaneously determine rolling and air resistance coefficients. Unlike prior methods that frequently used simulations or models, we employ a goal programming methodology to improve precision and evaluate the actual vehicle and environmental conditions. Our methodology was tested using a Class 8 Freightliner eCascadia on a surveyed road section, ensuring controlled conditions for data collection. By analyzing the time–velocity relationship across multiple test runs, we derived resistance coefficients for both loaded and unloaded conditions. The study confirms that rolling resistance is largely independent of velocity at low speeds but exhibits a nonlinear dependency at higher speeds. Additionally, road surface conditions, tire condition, axle configuration, aerodynamic properties, and weather conditions significantly impact resistance values, emphasizing the need for real-world testing rather than relying solely on standardized projections. Our results align with existing literature while demonstrating the efficacy of the goal programming approach in refining resistance estimates. This work contributes to improved vehicle energy modeling, offering practical insights for fleet operators and policymakers seeking accurate energy consumption predictions for electric trucks operating under varying environmental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Using excitation-energy dependent fission yields to identify key fissioning nuclei in r -process nucleosynthesis

The possibility that nucleosynthesis in neutron star mergers may reach fissioning nuclei introduces significant uncertainties in predicting the relative abundances of $r$-process material from such events. We evaluate the impact of using sets of fission yields given by the 2016 GEF code for spontaneous (sf), neutron-induced $((n, f))$, and $β$-delayed (βdf) fission processes which take into account the approximate initial excitation energy of the fissioning compound nucleus. We further explore energy-dependent fission dynamics in the $r$ process by considering the sensitivity of our results to the treatment of the energy sharing and de-excitation of the fission fragments using the FREYA code. We show that the asymmetric-to-symmetric yield trends predicted by GEF 2016 can reproduce the high-mass edge of the second $r$-process peak seen in solar data and examine the sensitivity of this result to the mass model and astrophysical conditions applied. We consider the effect of fission yields and barrier heights on the nuclear heating rates used to predict kilonova light curves. We find that fission barriers influence the contribution of 254 Cf spontaneous fission to the heating at ~100 d, such that a light curve observation consistent with such late-time heating would both confirm that actinides were produced in the event and imply the fission barriers are relatively high along the 254 Cf β-feeding path. We lastly determine the key nuclei responsible for setting the r-process abundance pattern by averaging over thirty trajectories from a 1.2–1.4 M ⊙ neutron star merger simulation. Finally, we show it is largely the odd-N nuclei undergoing $(Z, N)(n, f)$ and $(Z, N)β$df that control the relative abundances near the second peak. We find the 'hot spots' for β-delayed and neutron-induced fission given all mass models considered and show most of these nuclei lie between the predicted $N$ = 184 shell closure and the location of currently available experimental decay data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A new algorithm for identifying the flavour of B 0 s mesons at LHCb

A new algorithm for the determination of the initial flavour of B 0 s mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B 0 s meson. The second network combines the kaon charges to assign the B 0 s flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb –1 collected by the LHCb experiment in proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B 0 s – B ¯ 0 s flavour oscillations in B 0 s → D – s π + decays, and by analysing flavour-specific B * s 2 (5840) 0 → B + K – decays. The tagging power measured in B 0 s → D – s π + decays is found to be (1.80 ± 0.19 (stat) ± 0.18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗