Identification and optimisation of a pyrimidopyridone series of IRAK4 inhibitors
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Cumming, Iain A.↗
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Results for “NaI”
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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Improved integration of single-cell transcriptome and surface protein expression by LinQ-View
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Li, Lei↗
Profiling B cell immunodominance after SARS-CoV-2infection reveals antibody evolution to non-neutralizing viral targets
Dissecting the evolution of memory B cells (MBCs) against SARS-CoV-2 is critical for understanding antibody recall upon secondary exposure. Here, we used single-cell sequencing to profile SARS-CoV-2-reactive B cells in 38 COVID-19 patients. Using oligo-tagged antigen baits, we isolated B cells specific to the SARS-CoV-2 spike, nucleoprotein (NP), open reading frame 8 (ORF8), and endemic human coronavirus (HCoV) spike proteins. SARS-CoV-2 spike-specific cells were enriched in the memory compartment of acutely infected and convalescent patients several months post symptom onset. With severe acute infection, substantial populations of endemic HCoV-reactive antibody-secreting cells were identified and possessed highly mutated variable genes, signifying preexisting immunity. Finally, MBCs exhibited pronounced maturation to NP and ORF8 over time, especially in older patients. Monoclonal antibodies against these targets were non-neutralizing and non-protective in vivo. These findings reveal antibody adaptation to non-neutralizing intracellular antigens during infection, emphasizing the importance of vaccination for inducing neutralizing spike-specific MBCs.
antibody↗
Epitopes recognition of SARS-CoV-2 nucleocapsid RNA binding domain by human monoclonal antibodies
Coronavirus nucleocapsid protein (NP) of SARS-CoV-2 plays a central role in many functions important for virus proliferation including packaging and protecting genomic RNA. The protein shares sequence, structure, and architecture with nucleocapsid proteins from betacoronaviruses. The N-terminal domain (NP RBD ) binds RNA and the C-terminal domain is responsible for dimerization. After infection, NP is highly expressed and triggers robust host immune response. The anti-NP antibodies are not protective and not neutralizing but can effectively detect viral proliferation soon after infection. Two structures of SARS-CoV-2 NP RBD were determined providing a continuous model from residue 48 to 173, including RNA binding region and key epitopes. Five structures of NP RBD complexes with human mAbs were isolated using an antigen-bait sorting. Complexes revealed a distinct complement-determining regions and unique sets of epitope recognition. This may assist in the early detection of pathogens and designing peptide-based vaccines. Mutations that significantly increase viral load were mapped on developed, full length NP model, likely impacting interactions with host proteins and viral RNA.
59 BASIC BIOLOGICAL SCIENCES↗
Processing Strategies for an Organic Photovoltaic Module with over 10% Efficiency
Abstract not provided
Liao, Chuang-Yi↗
Role of NLR family pyrin domain-containing 3 inflammasome in the activation of pancreatic stellate cells
Highlights: • NLRP3 inflammasome was activated with the extension of activation time of PSCs. • LPS triggered PSCs activation through activating NLRP3 Inflammasome. • Inhibition of NLRP3 inflammasome mitigates the activation of PSCs. • NLRP3 inflammasome activates the TGF-β1/Smad3 signaling pathway in PSCs. NLRP3 inflammasome activation plays an important role in the development of pancreatic fibrosis. However, it is unclear whether the activation of the NLRP3 inflammasome is directly involved in the activation of Pancreatic stellate cells (PSCs). The aim of this study was to investigate the role and mechanism of the NLRP3 inflammasome in the activation of PSCs. In vivo, a rat model of chronic pancreatitis (CP) was induced by intravenous injection of dibutyltin dichloride (DBTC). In vitro, rat primary PSCs were isolated from pancreatic tissues and incubated with the NLRP3 inflammasome activator LPS, the NLRP3 inhibitor MCC950, or NLRP3 siRNA. The results showed that the expression of NLRP3, pro-Caspase-1, Caspase-1 and IL-18 was increased in the rat model of CP and during PSCs activation. LPS increased the protein levels of NLRP3, ASC, Caspase-1, IL-1β and IL-18 accompanied by the upregulation of α-SMA, Col I and FN expression. Moreover, MCC950 or NLPR3 siRNA decreased the expression of α-SMA, Col I, FN, TGF-β1 and p-Smad3. Furthermore, MCC950 reversed the LPS-induced upregulation of α-SMA, FN and Col Ⅰ expression in PSCs. This study revealed that the NLRP3 inflammasome is directly involved in the activation of PSCs in vivo and in vitro. Inhibiting NLRP3 suppresses the activation of PSCs through the TGF-β1/Smad3 pathway.
60 APPLIED LIFE SCIENCES↗
Probabilistic Diffusion Models Advance Extreme Flood Forecasting
Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce diffusion-based runoff model (DRUM), a probabilistic deep learning (DL) approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 1‰ of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3–0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern US benefiting most, gaining 3–7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.
54 ENVIRONMENTAL SCIENCES↗
Structures of honeybee-infecting Lake Sinai virus reveal domain functions and capsid assembly with dynamic motions
Understanding the structural diversity of honeybee-infecting viruses is critical to maintain pollinator health and manage the spread of diseases in ecology and agriculture. We determine cryo-EM structures of $T$ = 4 and $T$ = 3 capsids of virus-like particles (VLPs) of Lake Sinai virus (LSV) 2 and delta-N48 LSV1, belonging to tetraviruses, at resolutions of 2.3–2.6 Å in various pH environments. Structural analysis shows that the LSV2 capsid protein (CP) structural features, particularly the protruding domain and C-arm, differ from those of other tetraviruses. The anchor loop on the central β-barrel domain interacts with the neighboring subunit to stabilize homo-trimeric capsomeres during assembly. Delta-N48 LSV1 CP interacts with ssRNA via the rigid helix α1’, α1’–α1 loop, β-barrel domain, and C-arm. Cryo-EM reconstructions, combined with X-ray crystallographic and small-angle scattering analyses, indicate that pH affects capsid conformations by regulating reversible dynamic particle motions and sizes of LSV2 VLPs. C-arms exist in all LSV2 and delta-N48 LSV1 VLPs across varied pH conditions, indicating that autoproteolysis cleavage is not required for LSV maturation. The observed linear domino-scaffold structures of various lengths, made up of trapezoid-shape capsomeres, provide a basis for icosahedral $T$ = 4 and $T$ = 3 architecture assemblies. These findings advance understanding of honeybee-infecting viruses that can cause Colony Collapse Disorder.
59 BASIC BIOLOGICAL SCIENCES↗
Rejuvenating dead lithium supply in lithium metal anodes by iodine redox
Inactive lithium (more frequently called dead lithium) in the forms of solid-electrolyte interphase and electrically isolated metallic lithium is principally responsible for the performance decay commonly observed in lithium metal batteries. A fundamental solution of recovering dead lithium is urgently needed to stabilize lithium metal batteries. In this paper, we quantify the solid-electrolyte interphase components, and determine their relation with the formation of electrically isolated dead lithium metal. We present a lithium restoration method based on a series of iodine redox reactions mainly involving I 3 - /I - . Using a biochar capsule host for iodine, we show that the I 3 - /I - redox takes place spontaneously, effectively rejuvenating dead lithium to compensate the lithium loss. Through this design, a full-cell using a very limited lithium metal anode exhibits an excellent lifespan of 1,000 cycles with a high Coulombic efficiency of 99.9%. We also demonstrate the design with a commercial cathode in pouch cells. Cycling lithium batteries often results in inactive lithium that no longer participates in redox reactions, leading to performance deterioration. Here the authors use an iodic species to react with inactive lithium, bringing it back to life and thus making batteries last longer.
25 ENERGY STORAGE↗
The homogenous alternative to biomineralization: Zn- and Mn-rich materials enable sharp organismal “tools” that reduce force requirements
We measured hardness, modulus of elasticity, and, for the first time, loss tangent, energy of fracture, abrasion resistance, and impact resistance of zinc- and manganese-enriched materials from fangs, stings and other “tools” of an ant, spider, scorpion and nereid worm. The mechanical properties of the Zn- and Mn-materials tended to cluster together between plain and biomineralized “tool” materials, with the hardness reaching, and most abrasion resistance values exceeding, those of calcified salmon teeth and crab claws. Atom probe tomography indicated that Zn was distributed homogeneously on a nanometer scale and likely bound as individual atoms to more than ¼ of the protein residues in ant mandibular teeth. This homogeneity appears to enable sharper, more precisely sculpted “tools” than materials with biomineral inclusions do, and also eliminates interfaces with the inclusions that could be susceptible to fracture. Based on contact mechanics and simplified models, we hypothesize that, relative to plain materials, the higher elastic modulus, hardness and abrasion resistance minimize temporary or permanent tool blunting, resulting in a roughly 2/3 reduction in the force, energy, and muscle mass required to initiate puncture of stiff materials, and even greater force reductions when the cumulative effects of abrasion are considered. We suggest that the sharpness-related force reductions lead to significant energy savings, and can also enable organisms, especially smaller ones, to puncture, cut, and grasp objects that would not be accessible with plain or biomineralized “tools”.
59 BASIC BIOLOGICAL SCIENCES↗
The non-centrosymmetric layered compounds IrTe 2 I and RhTe 2 I
The previously unreported layered compounds IrTe 2 I and RhTe 2 I were prepared by a high-pressure synthesis method. Single crystal X-ray and powder X-ray diffraction studies find that the compounds are isostructural, crystallizing in a layered orthorhombic structure in the non-centrosymmetric, non-symmorphic space group Pca2 1 (#29). Characterization reveals diamagnetic, high resistivity, semiconducting behavior for both compounds, consistent with the +3 chemical valence and d 6 electronic configurations for both iridium and rhodium and the Te–Te dimers seen in the structural study. Finally, electronic band structures are calculated for both compounds, showing good agreement with the experimental results.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Unifying thermochemistry concepts in computational heterogeneous catalysis
Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange–correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Micro-kinetic modeling of temporal analysis of products data using kinetics-informed neural networks
Kinetics-informed neural networks improve fit quality for multi-pulse and noisy temporal analysis of products datasets.
Nai, Dingqi↗
Toward digital design at the exascale: An overview of project ICECap
High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Solving independent set problems with photonic quantum circuits
An independent set (IS) is a set of vertices in a graph such that no edge connects any two vertices. In adiabatic quantum computation [E. Farhi, et al ., Science 292, 472–475 (2001); A. Das, B. K. Chakrabarti, Rev. Mod. Phys. 80, 1061–1081 (2008)], a given graph G ( V , E ) can be naturally mapped onto a many-body Hamiltonian H IS G ( V , E ) , with edges E being the two-body interactions between adjacent vertices V . Thus, solving the IS problem is equivalent to finding all the computational basis ground states of H IS G ( V , E ) . Very recently, non-Abelian adiabatic mixing (NAAM) has been proposed to address this task, exploiting an emergent non-Abelian gauge symmetry of H IS G ( V , E ) [B. Wu, H. Yu, F. Wilczek, Phys. Rev. A 101, 012318 (2020)]. Here, we solve a representative IS problem G ( 8 , 7 ) by simulating the NAAM digitally using a linear optical quantum network, consisting of three C-Phase gates, four deterministic two-qubit gate arrays (DGA), and ten single rotation gates. The maximum IS has been successfully identified with sufficient Trotterization steps and a carefully chosen evolution path. Remarkably, we find IS with a total probability of 0.875(16), among which the nontrivial ones have a considerable weight of about 31.4%. Our experiment demonstrates the potential advantage of NAAM for solving IS-equivalent problems.
Science & Technology - Other Topics↗
HyKKT: a hybrid direct-iterative method for solving KKT linear systems
Here, we propose a solution strategy for the large indefinite linear systems arising in interior methods for nonlinear optimization. The method is suitable for implementation on hardware accelerators such as graphical processing units (GPUs). The current gold standard for sparse indefinite systems is the LBLT factorization where L is a lower triangular matrix and B is 1×1 or 2×2 block diagonal. However, this requires pivoting, which substantially increases communication cost and degrades performance on GPUs. Our approach solves a large indefinite system by solving multiple smaller positive definite systems, using an iterative solver on the Schur complement and an inner direct solve (via Cholesky factorization) within each iteration. Cholesky is stable without pivoting, thereby reducing communication and allowing reuse of the symbolic factorization. We demonstrate the practicality of our approach on large optimal power flow problems and show that it can efficiently utilize GPUs and outperform LBL T factorization of the full system.
97 MATHEMATICS AND COMPUTING↗
Competing magnetic states in transition metal dichalcogenide moiré materials
Small-twist-angle transition metal dichalcogenide (TMD) heterobilayers develop isolated flat moiré bands that are approximately described by triangular lattice generalized Hubbard models. In this paper we explore the metallic and insulating states that appear under different control conditions at a density of one electron per moiré period and the transitions between them. By combining fully self-consistent Hartree-Fock theory calculations with strong-coupling expansions around the atomic limit, we identify four different magnetic states and one nonmagnetic state near the model phase diagram’s metal-insulator phase transition line. Here, ferromagnetic insulating states, stabilized by nonlocal direct exchange interactions, are surprisingly prominent.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗