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At least 883 records · Page 49

Insights on carbon dioxide adsorption in a flexible 1-D coordination polymer from in situ X-ray scattering and density functional theory

A combination of in situ small-angle X-ray scattering (SAXS) microstructure characterization over scales ranging from 1 nm to 10 µm and powder X-ray diffraction (XRD) structure characterization under various gas/pressure/temperature conditions with density functional theory (DFT) calculations provides new insights for the CO2 sorption behavior of a one-dimensional porous coordination polymer: catena-bis­(di­benzoyl­methanato)(4,4′-bi­pyridyl)­nickel(II), denoted NiDBM-Bpy. The NiDBM-Bpy chains are held together by van der Waals forces, but the structure of guest-free NiDBM-Bpy is unsolved due to a lack of suitable crystals and high-quality powder XRD patterns. Nevertheless, SAXS and powder XRD can follow microstructural and structural changes as a function of gas pressure, composition and temperature. Both mixed-gas flow and static supercritical CO2 regimes are explored experimentally. DFT calculations are used to model the structural variation associated with XRD changes and hysteresis in the sorption isotherms. XRD and DFT calculations suggest that an orthorhombic Fddd structure with two CO2 per Ni emerges following a transition from the structure with lower molar volume and symmetry that exists without CO2 present.

Allen, Andrew J.↗

Room-temperature X-ray crystallography reveals the oxidation and reactivity of cysteine residues in SARS-CoV-2 3CL Mpro: insights into enzyme mechanism and drug design

The emergence of the novel coronavirus SARS-CoV-2 has resulted in a worldwide pandemic not seen in generations. Creating treatments and vaccines to battle COVID-19, the disease caused by the virus, is of paramount importance in order to stop its spread and save lives. The viral main protease, 3CL M pro , is indispensable for the replication of SARS-CoV-2 and is therefore an important target for the design of specific protease inhibitors. Detailed knowledge of the structure and function of 3CL M pro is crucial to guide structure-aided and computational drug-design efforts. Here, the oxidation and reactivity of the cysteine residues of the protease are reported using room-temperature X-ray crystallography, revealing that the catalytic Cys145 can be trapped in the peroxysulfenic acid oxidation state at physiological pH, while the other surface cysteines remain reduced. Only Cys145 and Cys156 react with the alkylating agent N -ethylmaleimide. It is suggested that the zwitterionic Cys145–His45 catalytic dyad is the reactive species that initiates catalysis, rather than Cys145-to-His41 proton transfer via the general acid–base mechanism upon substrate binding. The structures also provide insight into the design of improved 3CL M pro inhibitors.

3CL Mpro↗

Metalloprotein catalysis: structural and mechanistic insights into oxidoreductases from neutron protein crystallography

Metalloproteins catalyze a range of reactions, with enhanced chemical functionality due to their metal cofactor. The reaction mechanisms of metalloproteins have been experimentally characterized by spectroscopy, macromolecular crystallography and cryo-electron microscopy. An important caveat in structural studies of metalloproteins remains the artefacts that can be introduced by radiation damage. Photoreduction, radiolysis and ionization deriving from the electromagnetic beam used to probe the structure complicate structural and mechanistic interpretation. Neutron protein diffraction remains the only structural probe that leaves protein samples devoid of radiation damage, even when data are collected at room temperature. Additionally, neutron protein crystallography provides information on the positions of light atoms such as hydrogen and deuterium, allowing the characterization of protonation states and hydrogen-bonding networks. Neutron protein crystallography has further been used in conjunction with experimental and computational techniques to gain insight into the structures and reaction mechanisms of several transition-state metal oxidoreductases with iron, copper and manganese cofactors. Here, the contribution of neutron protein crystallography towards elucidating the reaction mechanism of metalloproteins is reviewed.

59 BASIC BIOLOGICAL SCIENCES↗

Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model

Power is a fundamental constraint as supercomputing advances to exascale. Efficient operation within strict power budgets requires application-aware power management based on a detailed understanding of application-level power behavior. This work analyzes the Energy Exascale Earth System Model (E3SM) atmosphere component, SCREAM, on Perlmutter (NERSC) and Frontier (OLCF). We characterize power variation across inputs, concurrency levels, and power caps, evaluate the energy impact of code optimizations, and attribute energy within the code using a newly developed GPU energy model. Results show that SCREAM’s peak power remains stable during its core execution phase and decreases gradually as concurrency increases. Power capping experiments reveal a performance–energy "sweet spot". On Perlmutter, limiting GPU power to 50% of thermal design power (TDP) achieves up to 15% energy savings with a 7% performance penalty. On Frontier, a 40% TDP cap yields up to 10% energy savings with less than 10% performance loss. Code optimizations reduce SCREAM energy by shortening run time without increasing power. Modeling reveals a critical insight: data movement accounts for approximately 70% of SCREAM’s GPU energy. This fundamentally shifts the optimization focus from FLOPS to data transfer reduction for this class of applications, offering the most impactful strategy for improving energy efficiency. This work establishes a foundation for practical, application-aware power management at exascale.

Zhao, Zhengji [Lawrence Berkeley National Laborato↗

Outcomes and Insights From Simplified Analytic Trajectory Optimization for a Tethered Underwater Kite

This letter formulates and solves a periodic trajectory optimization problem for a tethered underwater kite. The goal is to maximize the average mechanical power harvested by the kite. The type of kite considered in this letter extracts electricity from ocean currents by moving cross-current as its reel away from its base station, and consumes electricity to reel back. The problem of optimizing this kite’s trajectory is challenging due to the high dimensionality and nonlinearity of its dynamics. To tackle this challenge, the literature often separates the problem into two subproblems focusing on optimizing the cross-current and the reel-in/reel-out components of the trajectory, respectively, which may be sub-optimal. In contrast, this letter solves for the combined cross-current and reel-in/reel-out trajectory by linearizing the dynamics of the kite around a zero-power reference equilibrium trajectory in spherical coordinates. This allows the trajectory optimization problem to be solved analytically for simple sinusoidal input perturbations from equilibrium. Here we use linear quadratic regulation to enable the nonlinear kite model to track the optimized trajectory. The result is a computationally efficient approach that achieves an attractive Loyd factor of 19.9%, while providing important insights into the nature of the optimal trajectory.

42 ENGINEERING↗

Insights From the Software Design of a Multiphysics Multicomponent Scientific Code

Using simulations for scientific discovery requires that the software used in the simulations undergoes a rigorous design and development process similar to that of the lab instruments in the experimental sciences. To devise a good design methodology, it is critical to understand the requirements, constraints, and challenges. Furthermore, this article describes insights from the long-term stewardship of a multiphysics multicomponent software, FLASH, that was designed more than 20 years ago for astrophysics, now serves multiple communities, and has been successful in adapting to the changing world of high-performance computing.

97 MATHEMATICS AND COMPUTING↗

ECP SOLLVE: Validation and Verification Testsuite Status Update and Compiler Insight for OpenMP

The OpenMP language continues to evolve with every new specification release, as does the need to validate and verify the new features that have been implemented by the different vendors. With the release of OpenMP 5.0 and OpenMP 5.1, new target offload and host-based features have been introduced to the programming model. While OpenMP continues to grow in maturity, there is an observable growth in the number of compiler and hardware vendors that support OpenMP. In this manuscript, the main focus is on evaluating the conformity and OpenMP implementation progress of various compiler vendors such as Cray, IBM, GNU, Clang/LLVM, NVIDIA, and Intel. More specifically, the 4.5, 5.0, and 5.1 versions of the OpenMP specification are analyzed. For our experimental setup, the Crusher and Summit computing systems hosted by Oak Ridge National Lab’s Computing Facilities are utilized. The effort of vendor agnostic analysis of these implementations is especially valuable for application developers who are using new OpenMP features to accelerate their scientific codes. Insights are presented into the current implementation status of various vendors, the progression of specific compiler’s support for OpenMP overtime, the subset of OpenMP 4.5, 5.0, and 5.1 that is supported by all compilers, and examples of how our test suite has influenced discussion regarding the correct interpretation of the OpenMP specification. By evaluating OpenMP conformity of pre-Exascale computing systems, the aim is to detail progress and status of AMD + Cray ecosystem before the system and their OpenMP implementation is used for mission critical applications when the first Exascale Computer Frontier is made available to applications.

Huber, Thomas↗

Insights into Na + Diffusion in Silicon Modules under Operating Conditions: Measuring Low Concentrations by D-SIMS

Sodium induced shunting under an electric field is a challenging reliability issue in crystalline Si solar modules. The source of this Potential-Induced Degradation of the Shunting type (PID-s) is well understood and its influence on power loss has been intensively studied based on phenomenological models on cell or module level relating the experimental power-loss to stressing parameters (time, temperature, voltage). However, little is known about the Na ion migration kinetics, responsible for PID on a microscopic level, and its quantitative relation to the efficiency degradation. In this paper we present our investigations of sodium ion migration in Ethylene-Vinyl Acetate (EVA) and silicon through Dynamic Secondary Ion Mass Spectroscopy (D-SIMS). Each sample was annealed at field relevant temperatures from 60-90 °C to address typical migration mechanisms of common PV installations. Analysis of the SIMS migration profiles revealed a diffusivity constant D 0,EVA = 0.09 ± 0.14 cm 2 /s and an activation energy E A,EVA = 0.85 ± .04 eV for Na in EVA and diffusivities higher than extrapolated literature values in silicon (D 0,Si = (3.03 ± 2.42)x10 -5 cm 2 /s, and E A,Si = 0.98 ± 0.02 eV). The new insight will be included in a drift-diffusion based degradation model accounting for the partition coefficient across all relevant interfaces. This model can assist in predicting PID-failure in the field based on the given model stack and the diffusion of Na + through each material. Furthermore, this tool can be used for process optimization as well as material selection significantly reducing the cost and time to validate a technology.

14 SOLAR ENERGY↗

Navigating Exascale Operational Data Analytics: From Inundation to Insight

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments.

Shin, Woong↗

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.

97 MATHEMATICS AND COMPUTING↗

Genomic resolution of a cold subsurface aquifer community provides metabolic insights for novel microbes adapted to high CO 2 concentrations

As in many deep underground environments, the microbial communities in subsurface high-CO 2 ecosystems remain relatively unexplored. Current research based on single-gene assays revealed a remarkable variety of organisms from little studied phyla in Crystal Geyser (Utah, USA), a site where deeply sourced CO 2 -saturated fluids are erupted at the surface. To provide genomic resolution of the metabolisms of these organisms, we used a novel metagenomic approach to recover 227 high-quality genomes from 150 microbial species affiliated with 46 different phylum-level lineages. Bacteria from two novel phylum-level lineages have the capacity for CO 2 fixation. Analyses of carbon fixation pathways in all studied organisms revealed that the Wood-Ljungdahl pathway and the Calvin-Benson-Bassham Cycle occurred with the highest frequency, whereas the reverse TCA cycle was little used. We infer that this, and selection for form II RuBisCOs, are adaptions to high CO 2 -concentrations. Yet, many autotrophs can also grow mixotrophically, a strategy that confers metabolic versatility. The assignment of 156 hydrogenases to 90 different organisms suggests that H 2 is an important inter-species energy currency even under gaseous CO 2 -saturation. As a whole, metabolic analyses at the organism level provided insight into the biochemical cycles that support subsurface life under the extreme condition of CO 2 saturation.

59 BASIC BIOLOGICAL SCIENCES↗

Genomics insights into ecotype formation of ammonia‐oxidizing archaea in the deep ocean

Summary Various lineages of ammonia‐oxidizing archaea (AOA) are present in deep waters, but the mechanisms that determine ecotype formation are obscure. We studied 18 high‐quality genomes of the marine group I AOA lineages (alpha, gamma and delta) from the Mariana and Ogasawara trenches. The genomes of alpha AOA resembled each other, while those of gamma and delta lineages were more divergent and had even undergone insertion of some phage genes. The instability of the gamma and delta AOA genomes could be partially due to the loss of DNA polymerase B ( polB) and methyladenine DNA glycosylase ( tag ) genes responsible for the repair of point mutations. The alpha AOA genomes harbour genes encoding a thrombospondin‐like outer membrane structure that probably serves as a barrier to gene flow. Moreover, the gamma and alpha AOA lineages rely on vitamin B 12 ‐independent MetE and B 12 ‐dependent MetH, respectively, for methionine synthesis. The delta AOA genome contains genes involved in uptake of sugar and peptide perhaps for heterotrophic lifestyle. Our study provides insights into co‐occurrence of cladogenesis and anagenesis in the formation of AOA ecotypes that perform differently in nitrogen and carbon cycling in dark oceans.

Wang, Yong↗

Insights into VdCmr1‐mediated protection against high temperature stress and UV irradiation in Verticillium dahliae

Summary The fungus Verticillium dahliae causes vascular wilt disease on more than 200 plant species worldwide. This fungus can survive for years in soil as melanized microsclerotia. We found that VdCmr1, a transcription factor, is required for the melanin production and increased survival following UV irradiation in V. dahliae but not for microsclerotia production or virulence. Here, we provided evidence how VdCmr1 protects against high temperature (HT) and UV irradiation in V. dahliae . The results indicate that VdCmr1 mediates entry to the diapause period in V. dahliae in response to HT and contributes to the expression of proteins to minimize protein misfolding and denaturation. VdCmr1 deletion results in the misregulation of DNA repair machinery, suggestive of reduced DNA repair capacity following UV irradiation and in correlation with the low survival rate of UV‐treated VdCmr1 mutants. We discovered a putative VdCmr1 ‐dependent gene cluster associated with secondary metabolism and stress responses. We also functionally characterized two VdCmr1‐responsive genes participating in HT and UV response. These results shed further light on the roles of VdCmr1 in protection from HT or UV irradiation, and the additional insights into the mechanisms of this protection may be useful to exploit for more effective disease control.

Fang, Yulin↗

Novel CHI3L1 ‐Associated Angiogenic Phenotypes Define Glioma Microenvironments: Insights From Multi‐Omics Integration

ABSTRACT The CHI3L1 signaling pathway significantly influences glioma angiogenesis, but its role in the tumor microenvironment (TME) remains elusive. We propose a novelCHI3L1‐associated vascular phenotype classification for glioma through integrative analyses of multiple datasets with bulk and single‐cell transcriptome, genomics, digital pathology, and clinical data. We investigated the biological characteristics, genomic alterations, therapeutic vulnerabilities, and immune profiles within these phenotypes through a comprehensive multi‐omics approach. We constructed the vascular‐related risk (VR) score based onCHI3L1‐associated vascular signatures (CAVS) identified by machine learning algorithms. Utilizing unsupervised consensus clustering, gliomas were stratified into three distinct vascular phenotypes: Cluster A, marked by high vascularization and stromal activation with a relatively low levels of tumor‐infiltrating lymphocytes (TILs); Cluster B, characterized by moderate vascularization and stromal activity, coupled with a high density of TILs; and Cluster C, defined by low vascularization and sparse immune cell infiltration. We observed that the CAVS effectively indicated glioma‐associated angiogenesis and immune suppression by single‐cell RNA‐seq analysis. Moreover, the high‐VR‐score group exhibited enhanced angiogenic activity, reduced immune response, resistance to immunotherapy, and poorer clinical outcomes. The VR score independently predicted glioma prognosis and, combined with a nomogram, provided a robust clinical decision‐making tool. Potential drug prediction based on transcription factors for high‐risk patients was also performed. Our study reveals thatCHI3L1‐associated vascular phenotypes shape distinct immune landscapes in gliomas, offering insights for optimizing therapeutic strategies to improve patient outcomes.

Oncology↗

Structural insights into hydrolytic defluorination of difluoroacetate by microbial fluoroacetate dehalogenases

Fluorine forms the strongest single bond to carbon with the highest bond dissociation energy among natural products. However, fluoroacetate dehalogenases (FADs) have been shown to hydrolyze this bond in fluoroacetate under mild reaction conditions. Furthermore, two recent studies demonstrated that the FAD RPA1163 fromRhodopseudomonas palustriscan also accept bulkier substrates. In this study, we explored the substrate promiscuity of microbial FADs and their ability to defluorinate polyfluorinated organic acids. Enzymatic screening of eight purified dehalogenases with reported fluoroacetate defluorination activity revealed significant hydrolytic activity against difluoroacetate in three proteins. Product analysis using liquid chromatography‐mass spectrometry identified glyoxylic acid as the final product of enzymatic DFA defluorination. The crystal structures of DAR3835 fromDechloromonas aromaticaand NOS0089 fromNostocsp. were determined in the apo‐state along with the DAR3835 H274N glycolyl intermediate. Structure‐based site‐directed mutagenesis of DAR3835 demonstrated a key role for the catalytic triad and other active site residues in the defluorination of both fluoroacetate and difluoroacetate. Computational analysis of the dimer structures of DAR3835, NOS0089, and RPA1163 indicated the presence of one substrate access tunnel in each protomer. Moreover, protein‐ligand docking simulations suggested similar catalytic mechanisms for the defluorination of both fluoroacetate and difluoroacetate, with difluoroacetate being defluorinated via two consecutive defluorination reactions producing glyoxylate as the final product. Thus, our findings provide molecular insights into substrate promiscuity and catalytic mechanism of FADs, which are promising biocatalysts for applications in synthetic chemistry and bioremediation of fluorochemicals.

Biochemistry & Molecular Biology↗

Mechanistic Insights Into Fatigue Life Enhancement of High‐Strength Steel via Ultrasonic Impact Treatment

In this work we explore the impact of Ultrasonic Impact Treatment (UIT) on the fatigue performance of high‐strength microalloyed steel commonly used in crankshaft applications. Building on prior observations of fatigue life improvement with UIT, this work focuses on unraveling the process–structure–performance relationships underpinning these enhancements. Microstructural analysis revealed significant grain refinement in the near‐surface layers, with deformation depth increasing at higher impact energies. This led to increased surface hardness and the development of deeper compressive residual stresses, particularly in samples treated with higher impact energy. Rotating bending fatigue testing showed a substantial improvement in fatigue life for UIT‐treated samples, with the endurance limit nearly doubling compared with untreated specimens. Fractographic analysis revealed a transition in crack initiation from surface defects in untreated samples to interior regions in UIT‐treated samples, characterized by the formation of noninclusion‐induced granular bright facets (GBFs). The observed fatigue enhancement is attributed to the synergistic effects of strain hardening and compressive residual stresses, which increase the surface crack threshold and promote interior crack initiation. This study provides new mechanistic insight into UIT‐induced fatigue resistance and interior failure behavior in high‐strength steels.

36 MATERIALS SCIENCE↗

Illuminating otoliths: New insights for life history of Balistes triggerfishes

Our understanding of fish life-history strategies is informed by key biological processes, such as growth, survival/mortality, recruitment and sexual maturation, used to characterize fish stocks (populations). Characterizing the life-history traits of fish populations requires the application of accurate age estimation for managed species. Grey triggerfish Balistes capriscus and queen triggerfish Balistes vetula are important reef-associated species for commercial and recreational fisheries in the Atlantic Ocean. Both species exhibit a unique reproductive strategy for large-bodied fisheries-targeted reef fishes in that they are nesting benthic spawners and invest substantial energy in defence and care of their benthic nests and fertilized eggs. Until recently, our understanding of the life-history strategies of triggerfishes assumed the main method used to obtain age estimates, increments counted from thin sections of the first dorsal spine, provided an accurate characterization of population age-based parameters. However, results from bomb radiocarbon validation studies on the two Balistes species demonstrated that spines do not provide accurate ages, but sagittal otoliths do. The main goal of the current study was to provide an updated understanding for triggerfish life-history strategies by using otolith-based age estimates to characterize population age structure and growth for grey triggerfish and queen triggerfish from waters of the south-eastern U.S. Atlantic. The current study is the first to report on sex-specific age and growth information for grey triggerfish using the Δ 14 C-validated otolith-based age estimation method and the results indicate that the previous characterization of Balistes species as exhibiting moderately rapid growth and as relatively short-lived, based on spine-derived age estimates, are flawed. Otolith-based ages indicated that grey triggerfish and queen triggerfish are moderately slow-growing and long-lived species, attaining maximum ages of 21 and 40 years, respectively. Management efforts for triggerfishes should evaluate these new insights and incorporate the results of otolith-based age estimation into future population monitoring efforts.

59 BASIC BIOLOGICAL SCIENCES↗

High marker density GWAS provides novel insights into the genomic architecture of terpene oil yield in Eucalyptus

Terpenoid-based essential oils are economically important commodities, yet beyond their biosynthetic pathways, little is known about the genetic architecture of terpene oil yield from plants. Transport, storage, evaporative loss, transcriptional regulation and precursor competition may be important contributors to this complex trait. Here, we associate 2.39 million single nucleotide polymorphisms derived from shallow whole-genome sequencing of 468 Eucalyptus polybractea individuals with 12 traits related to the overall terpene yield, eight direct measures of terpene concentration and four biomass-related traits. Our results show that in addition to terpene biosynthesis, development of secretory cavities, where terpenes are both synthesized and stored, and transport of terpenes were important components of terpene yield. For sesquiterpene concentrations, the availability of precursors in the cytosol was important. Candidate terpene synthase genes for the production of 1,8-cineole and α-pinene, and β-pinene (which comprised > 80% of the total terpenes) were functionally characterized as a 1,8-cineole synthase and a β/α-pinene synthase. Our results provide novel insights into the genomic architecture of terpene yield and we provide candidate genes for breeding or engineering of crops for biofuels or the production of industrially valuable terpenes.

1,8‐cineole↗