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At least 1,009 records · Page 56

Molybdenum Burial Mechanism in Sulfidic Sediments: Iron-Sulfide Pathway

Relative to continental crust, sediments underlying sulfidic marine waters are molybdenum-rich, a property preserved in the rock record and useful for characterizing paleoenvironments. The enrichment mechanism is not agreed upon but is attributed at least partly to deposition of Fe–Mo–S compounds, which are as yet uncharacterized. Here, we determine the composition and stability of colloidal Fe–Mo–S precipitates formed at mildly basic pH and H 2 S(aq) > 10 –5 M. The first product consists simply of FeMoS 4 , with K sp = 10 –14.95 . Within hours, FeMoS 4 irreversibly transforms by internal self-reduction to a Mo(IV) product of similar composition. The reduced product is insoluble in 1 M HCl but soluble in concentrated HNO3, implying that it would be recovered with pyrite in a common assay of sediments. X-ray absorption fine structure data show that Mo(IV) in the colloids is coordinated by a split first shell of about five sulfur atoms at average distances of 2.31 and 2.46 Å and in its second shell by an iron atom at about 2.80 Å. These properties resemble those determined for Mo in modern anoxic lake sediments and in Phanerozoic black shales. The atomic environment around Mo suggests that the colloidal products may be inorganic polymers containing cuboid, Fe 2 Mo 2 S 4 4+ cores. Such materials are so far unreported by mineralogists, although a rare mineral, jordisite, may be a related, but more Mo-rich material. The low solubility of FeMoS 4 makes it a feasible precipitate in euxinic waters like those in the modern Black Sea. We propose that colloids similar to those studied here could account for Mo-enrichment in euxinic basin sediments and black shales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability Frontiers in the AM 6 X 6 Kagome Metals: The Ln Nb 6 Sn 6 ( Ln :Ce–Lu,Y) Family and Density-Wave Transition in LuNb 6 Sn 6

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV 3 Sb 5 superconductors and structurally-derived bond density waves (BDW) in FeGe and ScV 6 Sn 6 have stoked the search for new kagome platforms broadly exhibiting density wave (DW) transitions. Here, in this work, we evaluate the known AM 6 X 6 chemistries and construct a stability diagram that summarizes the structural relationships among the >125 member family. Subsequently, we introduce our discovery of the broader LnNb 6 Sn 6 (Ln:Ce–Nd,Sm,Gd–Tm,Lu,Y) family of kagome metals and an analogous DW transition in LuNb 6 Sn 6 . Our X-ray scattering measurements clearly indicate a (1/3, 1/3, 1/3) ordering wave vector (√$\bar{3}$ x √$\bar{3}$ x $3$ superlattice) and diffuse scattering on half-integer L-planes. Our analysis of the structural data supports the “rattling mode” DW model proposed for ScV 6 Sn 6 and paints a detailed picture of the steric interactions between the rare-earth filler element and the host Nb–Sn kagome scaffolding. We also provide a broad survey of the magnetic properties within the HfFe 6 Ge 6 -type LnNb 6 Sn 6 members, revealing a number of complex antiferromagnetic and metamagnetic transitions throughout the family. This work integrates our new LnNb 6 Sn 6 series of compounds into the broader AM 6 X 6 family, providing new material platforms and forging a new route forward at the frontier of kagome metal research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observed Relationships Between Cloud Droplet Effective Radius and Biogenic Gas Concentrations in Summertime Marine Stratocumulus Over the Eastern North Atlantic

Abstract Biogenic gases are a prominent component of the summertime marine boundary layer (MBL) over the Eastern North Atlantic. One of these gases, dimethyl sulfide (DMS), can produce sulfate cloud condensation nuclei (CCN) that, in theory, can brighten clouds through photolysis, and produces a reaction product, methane sulfonic acid (MSA). It is also possible that DMS can interact with sea‐salt or other marine aerosols changing their CCN activation spectrum, which could also modify cloud microphysical structure. Data collected aboard the G1 aircraft during the Aerosol Cloud Experiment Eastern North Atlantic (ACE‐ENA) in well‐mixed and decoupled marine boundary layers (MBLs) were used to examine relationships between the cloud droplet effective radii, , and the concentrations of DMS and MSA in constant cloud liquid water content (LWC) bins. A weak but statistically significant negative correlation was observed between CCN concentration and in most LWC bins, regardless of the source of the CCN, while a weak but statistically significant positive correlation between and DMS was observed. No correlation between the cloud droplet number concentration and DMS was found. The presence of MSA indicated that DMS‐to‐sulfate photolysis was likely occurring, but data sparsity prevented a statistically significant conclusion regarding the relationship between MSA and . Data sparsity in decoupled conditions also prevented statistically significant conclusions. To properly address biogenic gas impacts on cloud microphysics, it is recommended that aircraft data be supplemented by long‐term biogenic gas measurements at the surface in marine locations with appropriate remote and in‐situ cloud sensing capabilities, and the analysis limited to well‐mixed MBL's.

54 ENVIRONMENTAL SCIENCES↗

Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization

Abstract Accurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph‐structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.

58 GEOSCIENCES↗

Structural basis of omalizumab therapy and omalizumab-mediated IgE exchange

Omalizumab is a widely used therapeutic anti-IgE antibody. Here we report the crystal structure of the omalizumab–Fab in complex with an IgE-Fc fragment. This structure reveals the mechanism of omalizumab-mediated inhibition of IgE interactions with both high- and low-affinity IgE receptors, and explains why omalizumab selectively binds free IgE. The structure of the complex also provides mechanistic insight into a class of disruptive IgE inhibitors that accelerate the dissociation of the high-affinity IgE receptor from IgE. We use this structural data to generate a mutant IgE-Fc fragment that is resistant to omalizumab binding. Treatment with this omalizumab-resistant IgE-Fc fragment, in combination with omalizumab, promotes the exchange of cell-bound full-length IgE with omalizumab-resistant IgE-Fc fragments on human basophils. Furthermore, this combination treatment also blocks basophil activation more efficiently than either agent alone, providing a novel approach to probe regulatory mechanisms underlying IgE hypersensitivity with implications for therapeutic interventions.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal structure of a multi-domain human smoothened receptor in complex with a super stabilizing ligand

Here, the Smoothened receptor (SMO) belongs to the Class Frizzled of the G protein-coupled receptor (GPCR) superfamily, constituting a key component of the Hedgehog signalling pathway. Here we report the crystal structure of the multi-domain human SMO, bound and stabilized by a designed tool ligand TC114, using an X-ray free-electron laser source at 2.9 Å. The structure reveals a precise arrangement of three distinct domains: a seven-transmembrane helices domain (TMD), a hinge domain (HD) and an intact extracellular cysteine-rich domain (CRD). This architecture enables allosteric interactions between the domains that are important for ligand recognition and receptor activation. By combining the structural data, molecular dynamics simulation, and hydrogen-deuterium-exchange analysis, we demonstrate that transmembrane helix VI, extracellular loop 3 and the HD play a central role in transmitting the signal employing a unique GPCR activation mechanism, distinct from other multi-domain GPCRs.

36 MATERIALS SCIENCE↗

Bivalent antibody pliers inhibit β-tryptase by an allosteric mechanism dependent on the IgG hinge

Human β-tryptase, a tetrameric trypsin-like serine protease, is an important mediator of allergic inflammatory responses in asthma. Antibodies generally inhibit proteases by blocking substrate access by binding to active sites or exosites or by allosteric modulation. The bivalency of IgG antibodies can increase potency via avidity, but has never been described as essential for activity. Here we report an inhibitory anti-tryptase IgG antibody with a bivalency-driven mechanism of action. Using biochemical and structural data, we determine that four Fabs simultaneously occupy four exosites on the β-tryptase tetramer, inducing allosteric changes at the small interface. In the presence of heparin, the monovalent Fab shows essentially no inhibition, whereas the bivalent IgG fully inhibits β-tryptase activity in a hinge-dependent manner. Our results suggest a model where the bivalent IgG acts akin to molecular pliers, pulling the tetramer apart into inactive β-tryptase monomers, and may provide an alternative strategy for antibody engineering.

59 BASIC BIOLOGICAL SCIENCES↗

High-fidelity DNA ligation enforces accurate Okazaki fragment maturation during DNA replication

DNA ligase 1 (LIG1, Cdc9 in yeast) finalizes eukaryotic nuclear DNA replication by sealing Okazaki fragments using DNA end-joining reactions that strongly discriminate against incorrectly paired DNA substrates. Whether intrinsic ligation fidelity contributes to the accuracy of replication of the nuclear genome is unknown. Here, we show that an engineered low-fidelity LIG1 Cdc9 variant confers a novel mutator phenotype in yeast typified by the accumulation of single base insertion mutations in homonucleotide runs. The rate at which these additions are generated increases upon concomitant inactivation of DNA mismatch repair, or by inactivation of the Fen1 Rad27 Okazaki fragment maturation (OFM) nuclease. Biochemical and structural data establish that LIG1 Cdc9 normally avoids erroneous ligation of DNA polymerase slippage products, and this protection is compromised by mutation of a LIG1 Cdc9 high-fidelity metal binding site. Collectively, our data indicate that high-fidelity DNA ligation is required to prevent insertion mutations, and that this may be particularly critical following strand displacement synthesis during the completion of OFM.

59 BASIC BIOLOGICAL SCIENCES↗

Multiscale influenza forecasting

Abstract Influenza forecasting in the United States (US) is complex and challenging due to spatial and temporal variability, nested geographic scales of interest, and heterogeneous surveillance participation. Here we present Dante, a multiscale influenza forecasting model that learns rather than prescribes spatial, temporal, and surveillance data structure and generates coherent forecasts across state, regional, and national scales. We retrospectively compare Dante’s short-term and seasonal forecasts for previous flu seasons to the Dynamic Bayesian Model (DBM), a leading competitor. Dante outperformed DBM for nearly all spatial units, flu seasons, geographic scales, and forecasting targets. Dante’s sharper and more accurate forecasts also suggest greater public health utility. Dante placed 1st in the Centers for Disease Control and Prevention’s prospective 2018/19 FluSight challenge in both the national and regional competition and the state competition. The methodology underpinning Dante can be used in other seasonal disease forecasting contexts having nested geographic scales of interest.

59 BASIC BIOLOGICAL SCIENCES↗

The intrinsically disordered protein TgIST from Toxoplasma gondii inhibits STAT1 signaling by blocking cofactor recruitment

Signal transducer and activator of transcription (STAT) proteins communicate from cell-surface receptors to drive transcription of immune response genes. The parasite Toxoplasma gondii blocks STAT1-mediated gene expression by secreting the intrinsically disordered protein TgIST that traffics to the host nucleus, binds phosphorylated STAT1 dimers, and occupies nascent transcription sites that unexpectedly remain silenced. Here we define a core region within internal repeats of TgIST that is necessary and sufficient to block STAT1-mediated gene expression. Cellular, biochemical, mutational, and structural data demonstrate that the repeat region of TgIST adopts a helical conformation upon binding to STAT1 dimers. The binding interface is defined by a groove formed from two loops in the STAT1 SH2 domains that reorient during dimerization. TgIST binding to this newly exposed site at the STAT1 dimer interface alters its conformation and prevents the recruitment of co-transcriptional activators, thus defining the mechanism of blocked transcription.

59 BASIC BIOLOGICAL SCIENCES↗

Facile hermetic TEM grid preparation for molecular imaging of hydrated biological samples at room temperature

Abstract Although structures of vitrified supramolecular complexes have been determined at near-atomic resolution, elucidating in situ molecular structure in living cells remains a challenge. Here, we report a straightforward liquid cell technique, originally developed for real-time visualization of dynamics at a liquid-gas interface using transmission electron microscopy, to image wet biological samples. Due to the scattering effects from the liquid phase, the micrographs display an amplitude contrast comparable to that observed in negatively stained samples. We succeed in resolving subunits within the protein complex GroEL imaged in a buffer solution at room temperature. Additionally, we capture various stages of virus cell entry, a process for which only sparse structural data exists due to their transient nature. To scrutinize the morphological details further, we used individual particle electron tomography for 3D reconstruction of each virus. These findings showcase this approach potential as an efficient, cost-effective complement to other microscopy technique in addressing biological questions at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for C-degron selectivity across KLHDCX family E3 ubiquitin ligases

Abstract Specificity of the ubiquitin-proteasome system depends on E3 ligase-substrate interactions. Many such pairings depend on E3 ligases binding to peptide-like sequences - termed N- or C-degrons - at the termini of substrates. However, our knowledge of structural features distinguishing closely related C-degron substrate-E3 pairings is limited. Here, by systematically comparing ubiquitylation activities towards a suite of common model substrates, and defining interactions by biochemistry, crystallography, and cryo-EM, we reveal principles of C-degron recognition across the KLHDCX family of Cullin-RING ligases (CRLs). First, a motif common across these E3 ligases anchors a substrate’s C-terminus. However, distinct locations of this C-terminus anchor motif in different blades of the KLHDC2, KLHDC3, and KLHDC10 β-propellers establishes distinct relative positioning and molecular environments for substrate C-termini. Second, our structural data show KLHDC3 has a pre-formed pocket establishing preference for an Arg or Gln preceding a C-terminal Gly, whereas conformational malleability contributes to KLHDC10’s recognition of varying features adjacent to substrate C-termini. Finally, additional non-consensus interactions, mediated by C-degron binding grooves and/or by distal propeller surfaces and substrate globular domains, can substantially impact substrate binding and ubiquitylatability. Overall, the data reveal combinatorial mechanisms determining specificity and plasticity of substrate recognition by KLDCX-family C-degron E3 ligases.

Science & Technology - Other Topics↗

Molecular model of TFIIH recruitment to the transcription-coupled repair machinery

Transcription-coupled repair (TCR) is a vital nucleotide excision repair sub-pathway that removes DNA lesions from actively transcribed DNA strands. Binding of CSB to lesion-stalled RNA Polymerase II (Pol II) initiates TCR by triggering the recruitment of downstream repair factors. Yet it remains unknown how transcription factor IIH (TFIIH) is recruited to the intact TCR complex. Combining existing structural data with AlphaFold predictions, we build an integrative model of the initial TFIIH-bound TCR complex. We show how TFIIH can be first recruited in an open repair-inhibited conformation, which requires subsequent CAK module removal and conformational closure to process damaged DNA. In our model, CSB, CSA, UVSSA, elongation factor 1 (ELOF1), and specific Pol II and UVSSA-bound ubiquitin moieties come together to provide interaction interfaces needed for TFIIH recruitment. STK19 acts as a linchpin of the assembly, orienting the incoming TFIIH and bridging Pol II to core TCR factors and DNA. Molecular simulations of the TCR-associated CRL4CSA ubiquitin ligase complex unveil the interplay of segmental DDB1 flexibility, continuous Cullin4A flexibility, and the key role of ELOF1 for Pol II ubiquitination that enables TCR. Collectively, these findings elucidate the coordinated assembly of repair proteins in early TCR.

Paul, Tanmoy↗

The Rational Design of Therapeutic Peptides for Aminopeptidase N using a Substrate-Based Approach

The M1 family of metalloproteases represents a large number of exopeptidases that cleave single amino acid residues from the N-terminus of peptide substrates. One member of this family that has been well studied is aminopeptidase N (APN), a multifunctional protease known to cleave biologically active peptides and aide in coronavirus entry. The proteolytic activity of APN promotes cancer angiogenesis and metastasis making it an important target for cancer therapy. To understand the substrate specificity of APN for the development of targeted inhibitors, we used a global substrate profiling method to determine the P1–P4' amino acid preferences. Here, the key structural features of the APN pharmacophore required for substrate recognition were elucidated by x-ray crystallography. By combining these substrate profiling and structural data, we were able to design a selective peptide inhibitor of APN that was an effective therapeutic both in vitro and in vivo against APN-expressing prostate cancer models.

59 BASIC BIOLOGICAL SCIENCES↗

Question-answering system extracts information on injection drug use from clinical notes

Background. Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods. Here, to address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information from temporally out-of-distribution data. Results. Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions. Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

60 APPLIED LIFE SCIENCES↗

Efficient generation of grids and traversal graphs in compositional spaces towards exploration and path planning

Abstract Diverse disciplines across science and engineering deal with problems related to compositions, which exist in non-Euclidean simplex spaces, rendering many standard tools inaccurate or inefficient. This work explores such spaces conceptually in the context of materials discovery, quantifies their computational feasibility, and implements several essential methods specific to simplex spaces through a new high-performance open-source library . Most significantly, we derive and implement an algorithm for constructing a novel n-dimensional simplex graph data structure, containing all discretized compositions and possible neighbor-to-neighbor transitions. Critically, no distance or neighborhood calculations are performed, instead leveraging pure combinatorics and order in procedurally generated simplex grids, keeping the algorithm $${\mathcal{O}}(N)$$ O ( N ) , with minimal memory, enabling rapid construction of graphs with billions of transitions in seconds. Additionally, we demonstrate how such graph representations can be combined to homogeneously express complex path-planning problems, while facilitating efficient deployment of existing high-performance gradient descent, graph traversal, and other optimization algorithms.

Krajewski, Adam M. (ORCID:0000000222660099)↗

Modelling the local atomic structure of molybdenum in nuclear waste glasses with ab initio molecular dynamics simulations

The nature of chemical bonding of molybdenum in high level nuclear waste glasses has been elucidated by ab initio molecular dynamics simulations. Two compositions, (SiO2)57.5 – (B2O3)10 – (Na2O)15 – (CaO)15 – (MoO3)2.5 and (SiO2)57.3 – (B2O3)20 – (Na2O)6.8 – (Li2O)13.4 – (MoO3)2.5 , were considered in order to investigate the effect of ionic and covalent components on the glass structure and the formation of the crystallisation precursors (Na2MoO4 and CaMoO4). The coordination environments of Mo cations and the corresponding bond lengths calculated from our model are in excellent agreement with experimental observations. The analysis of the first coordination shell reveals two different types of molybdenum host matrix bonds in the lithium sodium borosilicate glass. Based on the structural data and the bond valence model, we demonstrate that the Mo cation can be found in a redox state and the molybdate tetrahedron can be connected with the borosilicate network in a way that inhibits the formation of crystalline molybdates. These results significantly extend our understanding of bonding in Mo-containing nuclear waste glasses and demonstrate that tailoring the glass composition to specific heavy metal constituents can facilitate incorporation of heavy metals at high concentrations. K.K. was supported through the Impact Studentship scheme at UCL co-funded by the IHI Corporation and UCL. P.V.S. thanks the Royal Society, which supported preliminary work on this project, and the Laboratory Directed Research and Development program at PNNL, a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy. Via our membership of the UK's HEC Materials Chemistry Consortium, which is funded by EPSRC (EP/L000202), this work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗