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Spin wave Hamiltonian and anomalous scattering in NiPS 3
Here, we report a comprehensive spin wave analysis of the semiconducting honeycomb van der Waal antiferromagnet NiPS 3 . Using single-crystal inelastic neutron scattering, we map out the full Brillouin zone and fit the observed modes to a spin wave model with rigorously defined uncertainty. We find that the third-nearest-neighbor exchange J 3 dominates the Hamiltonian, a feature which we fully account for by ab initio density functional theory calculations. We also quantify the degree to which the threefold rotation symmetry is broken and account for the Q = 0 excitations observed in other measurements, yielding a spin exchange model which is consistent across multiple experimental probes. We also identify a strongly reduced static ordered moment and reduced low-energy intensity relative to the linear spin wave calculations, signaling unexplained features in the magnetism which requires going beyond the linear spin wave approximation.
Mutual spin-phonon driving effects and phonon eigenvector renormalization in nickel (II) oxide
The physics of mutual interaction of phonon quasiparticles with electronic spin degrees of freedom, leading to unusual transport phenomena of spin and heat, has been a subject of continuing interests for decades. Despite its pivotal role in transport processes, the effect of spin-phonon coupling on the phonon system, especially acoustic phonon properties, has so far been elusive. By means of inelastic neutron scattering and first-principles calculations, anomalous scattering spectral intensity from acoustic phonons was identified in the exemplary collinear antiferromagnetic nickel (II) oxide, unveiling strong spin-lattice correlations that renormalize the polarization of acoustic phonon. In particular, a clear magnetic scattering signature of the measured neutron scattering intensity from acoustic phonons is demonstrated by its momentum transfer and temperature dependences. The anomalous scattering intensity is successfully modeled with a modified magneto-vibrational scattering cross-section, suggesting the presence of spin precession driven by phonon. The renormalization of phonon eigenvector is indicated by the observed “geometry-forbidden” neutron scattering intensity from transverse acoustic phonon. Importantly, the eigenvector renormalization cannot be explained by magnetostriction but instead, it could result from the coupling between phonon and local magnetization of ions.
Study of same-sign W boson scattering and anomalous couplings in events with one tau lepton from pp collisions at $\sqrt{s}=13$ TeV
A first study is presented of the cross section for the scattering of same-sign W boson pairs via the detection of a τ lepton. The data from proton-proton collisions at the center-of-mass energy of 13 TeV were collected by the CMS detector at the LHC, and correspond to an integrated luminosity of 138 fb −1 . Events were selected that contain two jets with large pseudorapidity and large invariant mass, one τ lepton, one light lepton (e or μ), and significant missing transverse momentum. The measured cross section for electroweak same-sign WW scattering is $1.44^{+0.63}_{-0.56}$ times the standard model prediction. In addition, a search is presented for the indirect effects of processes beyond the standard model via the effective field theory framework, in terms of dimension-6 and dimension-8 operators.
Vector boson scattering and anomalous quartic couplings in final states with ℓνqq or ℓℓqq plus jets using proton-proton collisions at $\sqrt{s}=13$ TeV
A measurement is presented of the electroweak vector boson scattering production of ZV (V = W, Z) boson pairs associated with two jets in proton-proton collisions at a center-of-mass energy of 13 TeV. The data, corresponding to an integrated luminosity of 138 fb −1 , were collected at the CERN LHC with the CMS detector during the 2016–2018 data-taking period. The analysis targets final states with a pair of isolated electrons or muons from Z boson decays and three or four jets, depending on the momentum of the vector boson that decays into quarks. Signal strength is measured for events characterized by a large invariant mass of two forward jets with a wide pseudorapidity gap between them. The electroweak production of ZV in association with two jets is measured with an observed (expected) significance of 1.3 (1.8) standard deviations. A combination of the analyses of ZV channel and the previously published WV channel in the lepton plus jets final state places constraints on effective field theory parameters that describe anomalous electroweak production of WW, WZ, and ZZ boson pairs in association with two jets. Several world best limits are set on anomalous quartic gauge couplings in terms of dimension-8 standard model effective field theory operators.
Emergence of asymmetric skew-scattering dominated anomalous Nernst effect in the spin gapless semiconductors Co 1+x Fe 1-x CrGa
Heusler alloy-based spin gapless semiconductors (SGSs) with very high Curie temperatures ( T C ) have recently gained enormous attention because of their unconventional electronic structures. They exhibit a nonzero band gap in one of the spin channels and a zero band gap in the other spin channel, making them an important class of materials for tunable spin transport. Here, we report the experimental observation of anomalous Nernst effect (ANE) in Co 1 + x Fe 1 - x CrGa ( x = 0 , 0.2, 0.4, and 0.5), which are the emerging quaternary Heusler alloy-based SGSs. While the electron-electron elastic scattering and the disorder-mediated weak localization effect play the major roles in electrical transport for all the samples at low temperatures, the magnon-drag effect was found to dominate the longitudinal thermoelectric transport. The ANE coefficient at room temperature increases from ≈ 0.018 μ V K - 1 for x = 0 to ≈ 0.063 μ V K - 1 for x = 0.5 , which is higher than that for Ni 81 Fe 19 and compressively strained SrRu O 3 films. Our analysis indicates that the observed ANE in these samples originates from asymmetric skew scattering of charge carriers.
Anomalous continuum scattering and higher-order van Hove singularity in the strongly anisotropic S = 1/2 triangular lattice antiferromagnet
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Ion permeation in potassium ion channels
The study of ion channels dates back to the 1950s and the groundbreaking electrophysiology work of Hodgin and Huxley, who used giant squid axons to probe how action potentials in neurons were initiated and propagated. More recently, several experiments using different structural biology techniques and approaches have been conducted to try to understand how potassium ions permeate through the selectivity filter of potassium ion channels. Two mechanisms of permeation have been proposed, and each of the two mechanisms is supported by different experiments. The key structural biology experiments conducted so far to try to understand how ion permeation takes place in potassium ion channels are reviewed and discussed. Protein crystallography has made, and continues to make, key contributions in this field, often through the use of anomalous scattering. Other structural biology techniques used to study the contents of the selectivity filter include solid-state nuclear magnetic resonance and two-dimensional infrared spectroscopy, both of which make clever use of isotopic labeling techniques, while molecular-dynamics simulations of ion flow through the selectivity filter have been enabled by the growing number of potassium ion channel structures deposited in the Protein Data Bank.
Application of sulfur SAD to small crystals with a large asymmetric unit and anomalous substructure
The application of sulfur single-wavelength anomalous dispersion (S-SAD) to determine the crystal structures of macromolecules can be challenging if the asymmetric unit is large, the crystals are small, the size of the anomalously scattering sulfur structure is large and the resolution at which the anomalous signals can be accurately measured is modest. Here, as a study of such a case, approaches to the SAD phasing of orthorhombic Ric-8A crystals are described. The structure of Ric-8A was published with only a brief description of the phasing process [Zeng et al. (2019), Structure , 27 , 1137–1141]. Here, alternative approaches to determining the 40-atom sulfur substructure of the 103 kDa Ric-8A dimer that composes the asymmetric unit are explored. At the data-collection wavelength of 1.77 Å measured at the Frontier micro-focusing Macromolecular Crystallography (FMX) beamline at National Synchrotron Light Source II, the sulfur anomalous signal strength, |Δ ano |/σΔ ano ( d ′′/sig), approaches 1.4 at 3.4 Å resolution. The highly redundant, 11 000 000-reflection data set measured from 18 crystals was segmented into isomorphous clusters using BLEND in the CCP 4 program suite. Data sets within clusters or sets of clusters were scaled and merged using AIMLESS from CCP 4 or, alternatively, the phenix.scale_and_merge tool from the Phenix suite. The latter proved to be the more effective in extracting anomalous signals. The HySS tool in Phenix , SHELXC / D and PRASA as implemented in the CRANK 2 program suite were each employed to determine the sulfur substructure. All of these approaches were effective, although HySS , as a component of the phenix.autosol tool, required data from all crystals to find the positions of the sulfur atoms. Critical contributors in this case study to successful phase determination by SAD included (i) the high-flux FMX beamline, featuring helical-mode data collection and a helium-filled beam path, (ii) as recognized by many authors, a very highly redundant, multiple-crystal data set and (iii) the inclusion within that data set of data from crystals that were scanned over large ω ranges, yielding highly isomorphous and highly redundant intensity measurements.
Physics-driven learning of Wasserstein GAN for density reconstruction in dynamic tomography
Object density reconstruction from projections containing scattered radiation and noise is of critical importance in many applications. Existing scatter correction and density reconstruction methods may not provide the high accuracy needed in many applications and can break down in the presence of unmodeled or anomalous scatter and other experimental artifacts. Incorporating machine-learning models could prove beneficial for accurate density reconstruction, particularly in dynamic imaging, where the time evolution of the density fields could be captured by partial differential equations or by learning from hydrodynamics simulations. In this work, we demonstrate the ability of learned deep neural networks to perform artifact removal in noisy density reconstructions, where the noise is imperfectly characterized. Here, we use a Wasserstein generative adversarial network (WGAN), where the generator serves as a denoiser that removes artifacts in densities obtained from traditional reconstruction algorithms. We train the networks from large density time-series datasets, with noise simulated according to parametric random distributions that may mimic noise in experiments. The WGAN is trained with noisy density frames as generator inputs, to match the generator outputs to the distribution of clean densities (time series) from simulations. A supervised loss is also included in the training, which leads to an improved density restoration performance. In addition, we employ physics-based constraints such as mass conservation during the network training and application to further enable highly accurate density reconstructions. Our preliminary numerical results show that the models trained in our frameworks can remove significant portions of unknown noise in density time-series data.
Adaptive Critical Balance and Firehose Instability in an Expanding, Turbulent, Collisionless Plasma
Abstract Using a hybrid-kinetic particle-in-cell simulation, we study the evolution of an expanding, collisionless, magnetized plasma in which strong Alfvénic turbulence is persistently driven. Temperature anisotropy generated adiabatically by the plasma expansion (and consequent decrease in the mean magnetic-field strength) gradually reduces the effective elasticity of the field lines, causing reductions in the linear frequency and residual energy of the Alfvénic fluctuations. In response, these fluctuations modify their interactions and spatial anisotropy to maintain a scale-by-scale “critical balance” between their characteristic linear and nonlinear frequencies. Eventually the plasma becomes unstable to kinetic firehose instabilities, which excite rapidly growing magnetic fluctuations at ion-Larmor scales. The consequent pitch-angle scattering of particles maintains the temperature anisotropy near marginal stability, even as the turbulent plasma continues to expand. The resulting evolution of parallel and perpendicular temperatures does not satisfy double-adiabatic conservation laws, but is described accurately by a simple model that includes anomalous scattering. Our results have implications for understanding the complex interplay between macro- and microscale physics in various hot, dilute, astrophysical plasmas, and offer predictions concerning power spectra, residual energy, ion-Larmor-scale spectral breaks, and non-Maxwellian features in ion distribution functions that may be tested by measurements taken in high-beta regions of the solar wind.
Crystallographic Characterization of Sodium Ions in a Bacterial Leucine/Sodium Symporter
Na + is the most abundant ion in living organisms and plays essential roles in regulating nutrient uptake, muscle contraction, and neurotransmission. The identification of Na + in protein structures is crucial for gaining a deeper understanding of protein function in a physiological context. LeuT, a bacterial homolog of the neurotransmitter:sodium symporter family, uses the Na + gradient to power the uptake of amino acids into cells and has been used as a paradigm for the study of Na + -dependent transport systems. We have devised a low-energy multi-crystal approach for characterizing low-Z (Z ≤ 20) anomalous scattering ions such as Na + , Mg 2+ , K + , and Ca 2+ by combining Bijvoet-difference Fourier syntheses for ion detection and f” refinements for ion speciation. Using the approach, we experimentally identify two Na + bound near the central leucine binding site in LeuT. Using LeuT microcrystals, we also demonstrate that Na + may be depleted to study conformational changes in the LeuT transport cycle.
Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction
Oxidation states of individual metal atoms within a metalloprotein can be assigned by examining X-ray absorption edges, which shift to higher energy for progressively more positive valence numbers. Indeed, X-ray crystallography is well suited for such a measurement, owing to its ability to spatially resolve the scattering contributions of individual metal atoms that have distinct electronic environments contributing to protein function. However, as the magnitude of the shift is quite small, about +2 eV per valence state for iron, it has only been possible to measure the effect when performed with monochromated X-ray sources at synchrotron facilities with energy resolutions in the range 2–3 × 10 −4 (Δ E / E ). This paper tests whether X-ray free-electron laser (XFEL) pulses, which have a broader bandpass (Δ E / E = 3 × 10 −3 ) when used without a monochromator, might also be useful for such studies. The program nanoBragg is used to simulate serial femtosecond crystallography (SFX) diffraction images with sufficient granularity to model the XFEL spectrum, the crystal mosaicity and the wavelength-dependent anomalous scattering factors contributed by two differently charged iron centers in the 110-amino-acid protein, ferredoxin. Bayesian methods are then used to deduce, from the simulated data, the most likely X-ray absorption curves for each metal atom in the protein, which agree well with the curves chosen for the simulation. The data analysis relies critically on the ability to measure the incident spectrum for each pulse, and also on the nanoBragg simulator to predict the size, shape and intensity profile of Bragg spots based on an underlying physical model that includes the absorption curves, which are then modified to produce the best agreement with the simulated data. This inference methodology potentially enables the use of SFX diffraction for the study of metalloenzyme mechanisms and, in general, offers a more detailed approach to Bragg spot data reduction.
A unifying Bayesian framework for merging X-ray diffraction data
Novel X-ray methods are transforming the study of the functional dynamics of biomolecules. Key to this revolution is detection of often subtle conformational changes from diffraction data. Diffraction data contain patterns of bright spots known as reflections. To compute the electron density of a molecule, the intensity of each reflection must be estimated, and redundant observations reduced to consensus intensities. Systematic effects, however, lead to the measurement of equivalent reflections on different scales, corrupting observation of changes in electron density. Here, we present a modern Bayesian solution to this problem, which uses deep learning and variational inference to simultaneously rescale and merge reflection observations. We successfully apply this method to monochromatic and polychromatic single-crystal diffraction data, as well as serial femtosecond crystallography data. We find that this approach is applicable to the analysis of many types of diffraction experiments, while accurately and sensitively detecting subtle dynamics and anomalous scattering.
Rational design of a genetically encoded NMR zinc sensor
Elucidating the biochemical roles of the essential metal ion, Zn 2+ , motivates detection strategies that are sensitive, selective, quantitative, and minimally invasive in living systems. Fluorescent probes have identified Zn 2+ in cells but complementary approaches employing nuclear magnetic resonance (NMR) are lacking. Recent studies of maltose binding protein (MBP) using ultrasensitive 129 Xe NMR spectroscopy identified a switchable salt bridge which causes slow xenon exchange and elicits strong hyperpolarized 129 Xe chemical exchange saturation transfer (hyper-CEST) NMR contrast. To engineer the first genetically encoded, NMR-active sensor for Zn 2+ , we converted the MBP salt bridge into a Zn 2+ binding site, while preserving the specific xenon binding cavity. The zinc sensor (ZS) at only 1 μM achieved ‘turn-on’ detection of Zn 2+ with pronounced hyper-CEST contrast. This made it possible to determine different Zn 2+ levels in a biological fluid via hyper-CEST. ZS was responsive to low-micromolar Zn 2+ , only modestly responsive to Cu 2+ , and nonresponsive to other biologically important metal ions, according to hyper-CEST NMR spectroscopy and isothermal titration calorimetry (ITC). Protein X-ray crystallography confirmed the identity of the bound Zn 2+ ion using anomalous scattering: Zn 2+ was coordinated with two histidine side chains and three water molecules. Penta-coordinate Zn 2+ forms a hydrogen-bond-mediated gate that controls the Xe exchange rate. Metal ion binding affinity, 129 Xe NMR chemical shift, and exchange rate are tunable parameters via protein engineering, which highlights the potential to develop proteins as selective metal ion sensors for NMR spectroscopy and imaging.
AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography
Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.
K 2P channel C-type gating involves asymmetric selectivity filter order-disorder transitions
K 2P potassium channels regulate cellular excitability using their selectivity filter (C-type) gate. C-type gating mechanisms, best characterized in homotetrameric potassium channels, remain controversial and are attributed to selectivity filter pinching, dilation, or subtle structural changes. The extent to which such mechanisms control C-type gating of innately heterodimeric K 2P s is unknown. Here, combining K 2P 2.1 (TREK-1) x-ray crystallography in different potassium concentrations, potassium anomalous scattering, molecular dynamics, and electrophysiology, we uncover unprecedented, asymmetric, potassium-dependent conformational changes that underlie K 2P C-type gating. These asymmetric order-disorder transitions, enabled by the K 2P heterodimeric architecture, encompass pinching and dilation, disrupt the S1 and S2 ion binding sites, require the uniquely long K 2P SF2-M4 loop and conserved “M3 glutamate network,” and are suppressed by the K 2P C-type gate activator ML335. These findings demonstrate that two distinct C-type gating mechanisms can operate in one channel and underscore the SF2-M4 loop as a target for K 2P channel modulator development.
Nickel Binding to the c-Src SH3 Domain Facilitates Crystallization
Introduction: Numerous X-ray crystal structures of the c-Src SH3 domain have provideda large sampling of atomic-level information for this important signaling domain. Multiple crystalforms have been reported, with variable crystal lattice contacts and chemical crystallizationconditions. Materials and Methods: We crystallized the c-Src SH3 domain in a crystallization buffercontaining NiCl2. Results: A unique crystal structure of the Src SH3 domain in the trigonal space group H32 isdetermined to 1.45 Å resolution. Crystal packing and anomalous scattering reveal that this crystalform is mediated by two ordered nickel ions provided by the crystallization buffer. Nickelcoordination occurs in a 2:2 stoichiometry, which dimerizes two SH3 domain monomers across apseudo-twofold rotation axis and involves the native N-terminal c-Src SH3 amino acid sequence, asurface-exposed histidine residue, and ordered water molecules. Discussion: This study provides an example of metal-mediated crystallization and metal binding byN-terminal protein residues, contrasting with the Amino-Terminal Copper and Nickel Binding(ATCUN) motif. Conclusion: Alternative avenues help widen the potential for future crystallography-based studiesof the c-Src SH3 domain.