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At least 685 records · Page 38

SEC ‐ SAXS / MC Ensemble Structural Studies of the Microtubule Binding Protein Cdt1 Show Monomeric, Folded‐Over Conformations

ABSTRACT Cdt1 is a mixed folded protein critical for DNA replication licensing and it also has a “moonlighting” role at the kinetochore via direct binding to microtubules and the Ndc80 complex. However, it is unknown how the structure and conformations of Cdt1 could allow it to participate in these multiple, unique sets of protein complexes. While robust methods exist to study entirely folded or unfolded proteins, structure–function studies of combined, mixed folded/disordered proteins remain challenging. In this work, we employ orthogonal biophysical and computational techniques to provide structural characterization of mitosis‐competent human Cdt1. Thermal stability analyses shows that both folded winged helix domains1 are unstable. CD and NMR show that the N‐terminal and linker regions are intrinsically disordered. DLS shows that Cdt1 is monomeric and polydisperse, while SEC‐MALS confirms that it is monomeric at high concentrations, but without any apparent inter‐molecular self‐association. SEC‐SAXS enabled computational modeling of the protein structures. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble of structures. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with SAXS. The best‐fit models have the N‐terminal and linker disordered regions extended into the solution and the two folded domains close to each other in apparent “folded over” conformations. We hypothesize the best‐fit Cdt1 conformations could be consistent with a function as a scaffold protein that may be sterically blocked without binding partners. Our study also provides a template for combining experimental and computational techniques to study mixed‐folded proteins.

Cell Biology↗

Bemnifosbuvir: An HCV NS5B Inhibitor With Multiple Modes of Action

Bemnifosbuvir (BEM) is a potent, pan-genotypic inhibitor targeting the hepatitis C virus (HCV) NS5B polymerase. Its antiviral activity was evaluated in an ascending dose phase I clinical trial involving 30 patients treated once a day for 7 days. After treatment initiation, plasma HCV RNA declined in a biphasic manner with a mean reduction of 2.3 log 10 IU/mL after 24 hours and 4.4 log10 IU/mL by day 7 for the highest dose. Alanine aminotransferase (ALT) also normalized in most patients. We employed a multiscale mathematical model fitted to the HCV RNA and ALT dynamics to quantify the antiviral activity and evaluate the modes of action of BEM. We found that models in which BEM only acted as a typical HCV RNA polymerase inhibitor and reduced the intracellular production of HCV RNA did not fit the data as well as models in which BEM had multiple modes of action, including suppressing viral assembly and secretion and enhancing intracellular HCV RNA degradation. BEM's effectiveness in inhibiting intracellular HCV RNA production increased with dose (150 mg/day: 88.2%, 300 mg/day: 98.8%, 600 mg/day: 99.5%), while inhibition of viral assembly and release was ~95% effective regardless of dose. We observed a dose-dependent enhancement in the degradation of intracellular HCV RNA, with degradation rates 1.5-fold higher in patients receiving 300 mg/day and 2.7-fold higher in those receiving 600 mg/day than in patients receiving 150 mg/day. No significant differences in antiviral activity were detected between HCV genotypes 1b and 3 or between patients with and without compensated cirrhosis.

59 BASIC BIOLOGICAL SCIENCES↗

Inferring pesticide toxicity to honey bees from a field‐based feeding study using a colony model and Bayesian inference

Abstract Honey bees are crucial pollinators for agricultural crops but are threatened by a multitude of stressors including exposure to pesticides. Linking our understanding of how pesticides affect individual bees to colony‐level responses is challenging because colonies show emergent properties based on complex internal processes and interactions among individual bees. Agent‐based models that simulate honey bee colony dynamics may be a tool for scaling between individual and colony effects of a pesticide. The U.S. Environmental Protection Agency (USEPA) and U.S. Department of Agriculture (USDA) are developing the VarroaPop + Pesticide model, which simulates the dynamics of honey bee colonies and how they respond to multiple stressors, including weather, Varroa mites, and pesticides. To evaluate this model, we used Approximate Bayesian Computation to fit field data from an empirical study where honey bee colonies were fed the insecticide clothianidin. This allowed us to reproduce colony feeding study data by simulating colony demography and mortality from ingestion of contaminated food. We found that VarroaPop + Pesticide was able to fit general trends in colony population size and structure and reproduce colony declines from increasing clothianidin exposure. The model underestimated adverse effects at low exposure (36 µg/kg), however, and overestimated recovery at the highest exposure level (140 µg/kg), for the adult and pupa endpoints, suggesting that mechanisms besides oral toxicity‐induced mortality may have played a role in colony declines. The VarroaPop + Pesticide model estimates an adult oral LD 50 of 18.9 ng/bee (95% CI 10.1–32.6) based on the simulated feeding study data, which falls just above the 95% confidence intervals of values observed in laboratory toxicology studies on individual bees. Overall, our results demonstrate a novel method for analyzing colony‐level data on pesticide effects on bees and making inferences on pesticide toxicity to individual bees.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of Anode Porosity and Temperature on the Performance and Lithium Plating During Fast-Charging of Lithium-Ion Cells

Twenty-four single-layer approximate to 32 mAh pouch cells are tested to determine the effect of electrode porosity on lithium plating. Twelve cells contain a graphite electrode that is 26% porous, and 47% for the other twelve. The cells are cycled using a 6-C charge and a C/2 discharge protocol at temperatures in the range of 20-50 degrees C. A macro-homogeneous electrochemical model and microstructure analysis tool set are used to help interpret experimental observations for the effect of anode porosity and ambient temperature on fast-charging performance. Additionally, comparison between the two also highlights gaps in current theoretical understanding that need to be addressed. In post-test examination, lithium plating is seen in all cells, regardless of porosity. Elevated temperature is shown to reduce the amount of lithium plating and improve initial fast-charge capacity, but also changes the rate of other, less well-understood degradation mechanisms. Apparent kinetic rate laws, At + Bt 1/2 , where A and B are constants, can be fit to most of the capacity loss and resistance increase data. The relative magnitudes of A and B change with temperature and porosity. The capacity loss data at 50 degrees C from the high-porosity cells are fit by a logistics rate law.

25 ENERGY STORAGE↗

Warmer incubation temperatures and later lay–orders lead to shorter telomere lengths in wood duck ( Aix sponsa ) ducklings

The environment that animals experience during development shapes phenotypic expression. In birds, two important aspects of the early-developmental environment are lay-order sequence and incubation. Later-laid eggs tend to produce weaker offspring, sometimes with compensatory mechanisms to accelerate their growth rate to catch-up to their siblings. Further, small decreases in incubation temperature slow down embryonic growth rates and lead to wide-ranging negative effects on many post-hatch traits. Recently, telomeres, non-coding DNA sequences at the end of chromosomes, have been recognized as a potential proxy for fitness because longer telomeres are positively related to lifespan and individual quality in many animals, including birds. Although telomeres appear to be mechanistically linked to growth rate, little is known about how incubation temperature and lay-order may influence telomere length. We incubated wood duck (Aix sponsa) eggs at two ecologically-relevant temperatures (34.9 and 36.2ºC) and measured telomere length at hatch and one week after. We found that ducklings incubated at the lower temperature had longer telomeres than those incubated at the higher temperature both at hatch and one week later. Further, we found that later-laid eggs produced ducklings with shorter telomeres than those laid early in the lay-sequence, although lay-order was not related to embryonic developmental rate. Furthermore, this study contributes to our broader understanding of how parental effects can affect telomere length early in life. More work is needed to determine if these effects on telomere length persist until adulthood, and if they are associated with effects on fitness in this precocial species.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Calabi–Yau Metrics

We apply machine learning to the problem of finding numerical Calabi–Yau metrics. Building on Donaldson's algorithm for calculating balanced metrics on Kähler manifolds, we combine conventional curve fitting and machine-learning techniques to numerically approximate Ricci-flat metrics. We show that machine learning is able to predict the Calabi–Yau metric and quantities associated with it, such as its determinant, having seen only a small sample of training data. Using this in conjunction with a straightforward curve fitting routine, we demonstrate that it is possible to find highly accurate numerical metrics much more quickly than by using Donaldson's algorithm alone, with our new machine-learning algorithm decreasing the time required by between one and two orders of magnitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantitative XPS of plutonium: Evaluation of the Pu4f peak shape, relative sensitivity factors and estimated detection limits

We report that high-resolution X-ray photoelectron spectra have been acquired from sputter cleaned and in situ oxidized samples of α-plutonium and a face-centred cubic δ-plutonium–gallium alloy. The differences in the Pu4f peak shape in these two materials have been investigated, and the poorly screened satellite peaks have been quantified. Curve fitting parameters for the Pu4p 3/2 , Pu4d 5/2 , Pu4f and Pu6p 3/2 photoelectron peaks are reported, and relative sensitivity factors have been determined. The Pu4f curve fit model has been applied to data acquired using different spectrometers and alloys. Examples of quantification of the plutonium spectra are provided and minimum detection limits are calculated for common impurities in plutonium metal.

36 MATERIALS SCIENCE↗

Surface analysis insight note: Differentiation methods applicable to noisy data for determination of sp2‐ versus sp3‐hybridization of carbon allotropes and AES signal strengths

The derivatives of the spectra are commonly used for quantification in Auger Electron Spectroscopy (AES) spectra, while the derivative of the KLL C Auger line has proven to be valuable in obtaining a measure of the relative proportions of sp 2 ‐ and sp 3 ‐hybridization using the D‐parameter in both AES and X‐ray Photoelectron Spectroscopy (XPS). Differentiation of X‐ray Photoelectron Spectroscopy (XPS) and Auger Electron Spectroscopy (AES) spectra by numerical means is presented and illustrated for polymeric, such as PEEK and Nylon, as well as for graphitic materials including highly ordered pyrolytic graphite and graphene oxide. The most commonly available Savitzky–Golay method is explained mathematically and developed through the case of constructing a 5‐point quadratic polynomial convolution kernel suitable for differentiating spectra of adequate signal to noise. The concept of differentiation of spectra where signal to noise is less than adequate is also developed. Two alternative strategies to Savitzky–Golay differentiation are presented, which fit curves to data that allow derivatives to be obtained where Savitzky–Golay would otherwise fail. These alternative methods involve constructing a parametric curve that fits data over the entire energy interval of interest. Derivatives of spectra are then obtained by differentiating these parametric curves directly. A comparison of results for different materials for which specific sp 2 ‐ vs sp 3 ‐hybridized carbon proportions are of interest is used to emphasize the importance of characterizing methods used to differentiate spectra and understanding the characteristics of instrumentation used to measure spectra. The case for using Principal Component Analysis noise reduction with C KLL spectra is made for spectra collected from a heterogeneous graphene oxide sample.

Fairley, Neal↗

A localized ensemble of approximate Gaussian processes for fast sequential emulation

More attention has been given to the computational cost associated with the fitting of an emulator. Substantially less attention is given to the computational cost of using that emulator for prediction. This is primarily because the cost of fitting an emulator is usually far greater than that of obtaining a single prediction, and predictions can often be obtained in parallel. In many settings, especially those requiring Markov Chain Monte Carlo, predictions may arrive sequentially and parallelization is not possible. In this case, using an emulator procedure which can produce accurate predictions efficiently can lead to substantial time savings in practice. In this paper, we propose a global model approximate Gaussian process framework via extension of a popular local approximate Gaussian process (laGP) framework. Our proposed emulator can be viewed as a treed Gaussian process where the leaf nodes are laGP models, and the tree structure is learned greedily as a function of the prediction stream. The suggested method (called leapGP) has interpretable tuning parameters which control the time‐memory trade‐off. One reasonable choice of settings leads to an emulator with a training cost and makes predictions rapidly with an asymptotic amortized cost of .

97 MATHEMATICS AND COMPUTING↗

Effects of Supplementation in Upper Yakima River Chinook Salmon

Abstract To promote recovery of natural salmonid populations, managers are utilizing hatchery supplementation programs to increase abundance of spawners on the spawning grounds. However, studies have provided evidence that captive breeding can result in domestication, demonstrated by lower fitness of hatchery‐origin compared with natural‐origin fish. Supplementation programs, therefore, typically use natural‐origin broodstock in an effort to minimize long‐term negative fitness impacts. Here we evaluated the upper Yakima River spring supplementation program for Chinook Salmon Oncorhynchus tshawytscha , which has broodstock comprised exclusively of unmarked fish presumed to be of natural‐origin. Using 5 years of spawner data, we tested for effects of hatchery breeding and rearing on total adult returns and their individual reproductive success when spawning naturally. Our study revealed that supplementation increased overall abundance of fish spawning naturally on the spawning grounds. However, on average, compared with natural‐origin spawners, hatchery‐origin fish had reduced reproductive success, which also translated to reduced reproductive success in three out of five return years for natural‐origin fish that spawned with hatchery‐origin fish. As expected, body length and return timing were also significant predictors of reproductive success. However, more generations of data are needed to establish the extent to which reduced reproductive success is passed on to naturally produced progeny.

Koch, Ilana J.↗

Compressional wave velocity and effective stress in unsaturated soil: Potential application for monitoring moisture conditions in vadose zone sediments

Compressional seismic (P-wave) velocities were measured experimentally at different water potentials and confining pressure states using a variety of sediments collected from the US Department of Energy Hanford Site in southeastern Washington State. P-wave velocity was measured in variably saturated sediments using ultrasonic piezoelectric transducers and water potential was measured with a heat dissipation sensor. We propose a model to relate changes in P-wave velocity to soil stress conditions using an effective stress formulation that includes capillary stress as well as adsorptive stress. We show that compressional wave velocities can be related to water potential and confining stress using a model with five fitted parameters. A single set of parameters provides an excellent fit to data acquired from all of the sediment samples. Under very dry conditions, corresponding to low water potentials, water flow occurs in adsorptive thin films associated with very low unsaturated hydraulic conductivities. The results presented here suggest the utility of seismic methods for establishing low water potential and flow conditions within variably saturated Hanford formation sediments and providing feedback on the performance of mitigation efforts such as soil desiccation and surface infiltration barriers. Seismic methods can provide minimally invasive, three-dimensional information on relevant flow conditions in vadose zone sediments as well as changes that occur over time.

Linneman, Dorothy C.↗

Weak neutral current axial form factor using $ \left(\overline{\nu}\right)\nu $-nucleon scattering and lattice QCD inputs

We present a determination of the neutral current weak axial charge $G$ $^{Z}_{A}$(0) = –0.654(3) stat (5) sys using the strange quark axial charge $G$ $^{s}_{A}$(0) calculated with lattice QCD. We then perform a phenomenological analysis, where we combine the strange quark electromagnetic form factor from lattice QCD with (anti)neutrino-nucleon scattering differential cross section from MiniBooNE experiments in a momentum transfer region 0.24 ≲ Q 2 ≲ 0.71 GeV 2 to determine the neutral current weak axial form factor $G$ $^{Z}_{A}$(Q 2 ) in the range of 0 ≲ Q 2 ≤ 1 GeV 2 . This yields a phenomenological value of $G$ $^{Z}_{A}$(0) = –0.687(89)stat(40)sys. The value of $G$ $^{Z}_{A}$(0) constrained by the lattice QCD calculation of $G$ $^{s}_{A}$(0), when compared to its phenomenological determination, provides a significant improvement in precision and accuracy and can be used to provide a constraint on the fit to $G$ $^{Z}_{A}$(Q 2 ) for Q 2 > 0. This constrained fit leads to an unambiguous determination of (anti)neutrino-nucleon neutral current elastic scattering differential cross section near Q 2 = 0 and can play an important role in numerically isolating nuclear effects in this region. We show a consistent description of $G$ $^{Z}_{A}$(Q 2 ) obtained from the (anti)neutrino-nucleon scattering cross section data requires a nonzero contribution of the strange quark electromagnetic form factor. We demonstrate the robustness of our analysis by providing a post-diction of the BNL E734 experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the W boson mass

The W boson mass is measured using proton-proton collision data at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 1.7 fb -1 recorded during 2016 by the LHCb experiment. With a simultaneous fit of the muon $q/ρ_T$ distribution of a sample of W →$μv$ decays and the $\phi^*$ distribution of a sample of Z → $μμ$ decays the W boson mass is determined to be $m_w$ =80354±23 stat ±10 exp ±17 theory ±9 PDF MeV, where uncertainties correspond to contributions from statistical, experimental systematic, theoretical and parton distribution function sources. This is an average of results based on three recent global parton distribution function sets. The measurement agrees well with the prediction of the global electroweak fit and with previous measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Model selection and signal extraction using Gaussian Process regression

We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nucleon momentum fraction, helicity and transversity from 2+1-flavor lattice QCD

A detailed analysis of the systematic uncertainties in the calculation of the isovector momentum fraction, ( x ) u - d , helicity moment, ( x ) Δ u - Δ d , and the transversity moment, ( x ) δu - δd , of the nucleon is presented using high-statistics data on seven ensembles of gauge configurations generated by the JLab/W&M/LANL/MIT collaborations using 2 + 1-flavors of dynamical Wilson-clover quarks. The much higher statistics have facilitated better control over all systematics compared to previous lattice calculations. The least understood systematic — excited-state contamination — is quantified by studying the variation of the results as a function of different estimates of the mass gap of the first excited state, obtained from two- and three-point correlation functions, and as a function of the pion mass M π . The final results are obtained using a simultaneous fit in the lattice spacing a , pion mass M π and the finite volume parameter M π L keeping leading order corrections. The data show no significant dependence on the lattice spacing and some evidence for finite-volume corrections. Our final results, in the $ \overline{\mathrm{MS}} $ scheme at 2 GeV, are ( x ) u - d = 0 . 155(17)(20), ( x ) Δ u - Δ d = 0 . 183(14)(20) and ( x ) δu - δd = 0 . 220(18)(20), where the first error is the overall analysis uncertainty assuming excited-state contributions have been removed, and the second is an additional systematic uncertainty due to possible residual excited-state contributions. These results are consistent with phenomenological global fit values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mirror twin Higgs cosmology: constraints and a possible resolution to the H$_{0}$ and S$_{8}$ tensions

The mirror twin Higgs model (MTH) is a solution to the Higgs hierarchy problem that provides well-predicted cosmological signatures with only three extra parameters: the temperature of the twin sector, the abundance of twin baryons, and the vacuum expectation value (VEV) of twin electroweak symmetry breaking. These parameters specify the behavior of twin radiation and the acoustic oscillations of twin baryons, which lead to testable effects on the cosmic microwave background (CMB) and large-scale structure (LSS). While collider searches can only probe the twin VEV, through a fit to cosmological data we show that the existing CMB (Planck18 TTTEEE+lowE+lowT+lensing) and LSS (KV450) data already provide useful constraints on the remaining MTH parameters. Additionally, we show that the presence of twin radiation in this model can raise the Hubble constant H$_{0}$ while the scattering twin baryons can reduce the matter fluctuations S$_{8}$, which helps to relax the observed H$_{0}$ and S$_{8}$ tensions simultaneously. This scenario is different from the typical ΛCDM + ΔN$_{eff}$ model, in which extra radiation helps with the Hubble tension but worsens the S$_{8}$ tension. For instance, when including the SH0ES and 2013 Planck SZ data in the fit, we find that a universe with ≳ 20% of the dark matter comprised of twin baryons is preferred over ΛCDM by ~ 4σ. If the twin sector is indeed responsible for resolving the H$_{0}$ and S$_{8}$ tensions, future measurements from the Euclid satellite and CMB Stage 4 experiment will further measure the twin parameters to O(1 - 10%)-level precision. Our study demonstrates how models with hidden naturalness can potentially be probed using precision cosmological data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simultaneous CTEQ-TEA extraction of PDFs and SMEFT parameters from jet and $t\bar{t}$ data

Recasting phenomenological Lagrangians in terms of SM effective field theory (SMEFT) provides a valuable means of connecting potential BSM physics at momenta well above the electroweak scale to experimental signatures at lower energies. In this work we jointly fit the Wilson coefficients of SMEFT operators as well as the PDFs in an extension of the CT18 global analysis framework, obtaining self-consistent constraints to possible BSM physics effects. Global fits are boosted with machine-learning techniques in the form of neural networks to ensure efficient scans of the full PDF+SMEFT parameter space. We focus on several operators relevant for top-quark pair and jet production at hadron colliders and obtain constraints on the Wilson coefficients with Lagrange Multiplier scans. We find mild correlations between the extracted Wilson coefficients, PDFs, and other QCD parameters, and see indications that these correlations may become more prominent in future analyses based on data of higher precision. This work serves as a new platform for joint analyses of SM and BSM physics based on the CTEQ-TEA framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗