bluuebunny/crossref_metadata_2025_split huggingface dataset:
Autophagy sustains glutamate and aspartate synthesis in Saccharomyces cerevisiae during nitrogen starvation
Authors: Liu Kuanqing , Sutter Benjamin M. , Tu Benjamin P. 
Published: January 2021

AbstractAutophagy catabolizes cellular constituents to promote survival during nutrient deprivation. Yet, a metabolic comprehension of this recycling operation, despite its crucial importance, remains incomplete. Here, we uncover a specific metabolic function of autophagy that exquisitely adjusts cellular metabolism according to nitrogen availability in the budding yeast Saccharomyces cerevisiae. Autophagy enables metabolic plasticity to promote glutamate and aspartate synthesis, which empowers nitrogen-starved cells to replenish their nitrogen currency and sustain macromolecule synthesis. Our findings provide critical insights into the metabolic basis by which autophagy recycles cellular components and may also have important implications in understanding the role of autophagy in diseases such as cancer.
The origin of the Moon’s Earth-like tungsten isotopic composition from dynamical and geochemical modeling
Authors: Fischer Rebecca A. , Zube Nicholas G. , Nimmo Francis 
Published: January 2021

AbstractThe Earth and Moon have identical or very similar isotopic compositions for many elements, including tungsten. However, canonical models of the Moon-forming impact predict that the Moon should be made mostly of material from the impactor, Theia. Here we evaluate the probability of the Moon inheriting its Earth-like tungsten isotopes from Theia in the canonical giant impact scenario, using 242 N-body models of planetary accretion and tracking tungsten isotopic evolution, and find that this probability is <1.6–4.7%. Mixing in up to 30% terrestrial materials increases this probability, but it remains <10%. Achieving similarity in stable isotopes is also a low-probability outcome, and is controlled by different mechanisms than tungsten. The Moon’s stable isotopes and tungsten isotopic composition are anticorrelated due to redox effects, lowering the joint probability to significantly less than 0.08–0.4%. We therefore conclude that alternate explanations for the Moon’s isotopic composition are likely more plausible.
Terahertz pulse shaping using diffractive surfaces
Authors: Veli Muhammed , Mengu Deniz , Yardimci Nezih T. , Luo Yi , Li Jingxi , Rivenson Yair , Jarrahi Mona , Ozcan Aydogan 
Published: January 2021

AbstractRecent advances in deep learning have been providing non-intuitive solutions to various inverse problems in optics. At the intersection of machine learning and optics, diffractive networks merge wave-optics with deep learning to design task-specific elements to all-optically perform various tasks such as object classification and machine vision. Here, we present a diffractive network, which is used to shape an arbitrary broadband pulse into a desired optical waveform, forming a compact and passive pulse engineering system. We demonstrate the synthesis of various different pulses by designing diffractive layers that collectively engineer the temporal waveform of an input terahertz pulse. Our results demonstrate direct pulse shaping in terahertz spectrum, where the amplitude and phase of the input wavelengths are independently controlled through a passive diffractive device, without the need for an external pump. Furthermore, a physical transfer learning approach is presented to illustrate pulse-width tunability by replacing part of an existing network with newly trained diffractive layers, demonstrating its modularity. This learning-based diffractive pulse engineering framework can find broad applications in e.g., communications, ultra-fast imaging and spectroscopy.
ZNF143 mediates CTCF-bound promoter–enhancer loops required for murine hematopoietic stem and progenitor cell function
Authors: Zhou Qiling , Yu Miao , Tirado-Magallanes Roberto , Li Bin , Kong Lingshi , Guo Mingrui , Tan Zi Hui , Lee Sanghoon , Chai Li , Numata Akihiko , Benoukraf Touati , Fullwood Melissa Jane , Osato Motomi , Ren Bing , Tenen Daniel G. 
Published: January 2021

AbstractCCCTC binding factor (CTCF) is an important factor in the maintenance of chromatin–chromatin interactions, yet the mechanism regulating its binding to chromatin is unknown. We demonstrate that zinc finger protein 143 (ZNF143) is a key regulator for CTCF-bound promoter–enhancer loops. In the murine genome, a large percentage of CTCF and ZNF143 DNA binding motifs are distributed 37 bp apart in the convergent orientation. Furthermore, deletion of ZNF143 leads to loss of CTCF binding on promoter and enhancer regions associated with gene expression changes. CTCF-bound promoter–enhancer loops are also disrupted after excision of ZNF143. ZNF143-CTCF-bound promoter–enhancer loops regulate gene expression patterns essential for maintenance of murine hematopoietic stem and progenitor cell integrity. Our data suggest a common feature of gene regulation is that ZNF143 is a critical factor for CTCF-bound promoter–enhancer loops.
FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation
Authors: Ramírez-Aportela Erney , Maluenda David , Fonseca Yunior C. , Conesa Pablo , Marabini Roberto , Heymann J. Bernard , Carazo Jose Maria , Sorzano Carlos Oscar S. 
Published: January 2021

AbstractIn recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure “FSC-Q”, and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.
Transkingdom interactions between Lactobacilli and hepatic mitochondria attenuate western diet-induced diabetes
Authors: Rodrigues Richard R. , Gurung Manoj , Li Zhipeng , García-Jaramillo Manuel , Greer Renee , Gaulke Christopher , Bauchinger Franziska , You Hyekyoung , Pederson Jacob W. , Vasquez-Perez Stephany , White Kimberly D. , Frink Briana , Philmus Benjamin , Jump Donald B. , Trinchieri Giorgio , Berry David , Sharpton Thomas J. , Dzutsev Amiran , Morgun Andrey , Shulzhenko Natalia 
Published: January 2021

AbstractWestern diet (WD) is one of the major culprits of metabolic disease including type 2 diabetes (T2D) with gut microbiota playing an important role in modulating effects of the diet. Herein, we use a data-driven approach (Transkingdom Network analysis) to model host-microbiome interactions under WD to infer which members of microbiota contribute to the altered host metabolism. Interrogation of this network pointed to taxa with potential beneficial or harmful effects on host’s metabolism. We then validate the functional role of the predicted bacteria in regulating metabolism and show that they act via different host pathways. Our gene expression and electron microscopy studies show that two species from Lactobacillus genus act upon mitochondria in the liver leading to the improvement of lipid metabolism. Metabolomics analyses revealed that reduced glutathione may mediate these effects. Our study identifies potential probiotic strains for T2D and provides important insights into mechanisms of their action.
Hepatitis B virus rigs the cellular metabolome to avoid innate immune recognition
Authors: Zhou Li , He Rui , Fang Peining , Li Mengqi , Yu Haisheng , Wang Qiming , Yu Yi , Wang Fubing , Zhang Yi , Chen Aidong , Peng Nanfang , Lin Yong , Zhang Rui , Trilling Mirko , Broering Ruth , Lu Mengji , Zhu Ying , Liu Shi 
Published: January 2021

AbstractGlucose metabolism and innate immunity evolved side-by-side. It is unclear if and how the two systems interact with each other during hepatitis B virus (HBV) infections and, if so, which mechanisms are involved. Here, we report that HBV activates glycolysis to impede retinoic acid-inducible gene I (RIG-I)-induced interferon production. We demonstrate that HBV sequesters MAVS from RIG-I by forming a ternary complex including hexokinase (HK). Using a series of pharmacological and genetic approaches, we provide in vitro and in vivo evidence indicating that HBV suppresses RLR signaling via lactate dehydrogenase-A-dependent lactate production. Lactate directly binds MAVS preventing its aggregation and mitochondrial localization during HBV infection. Therefore, we show that HK2 and glycolysis-derived lactate have important functions in the immune escape of HBV and that energy metabolism regulates innate immunity during HBV infection.
LTD is involved in the formation and maintenance of rat hippocampal CA1 place-cell fields
Authors: Ashby Donovan M. , Floresco Stan B. , Phillips Anthony G. , McGirr Alexander , Seamans Jeremy K. , Wang Yu Tian 
Published: January 2021

AbstractHippocampal synaptic plasticity includes both long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength, and has been implicated in shaping place field representations that form upon initial exposure to a novel environment. However, direct evidence causally linking either LTP or LTD to place fields remains limited. Here, we show that hippocampal LTD regulates the acute formation and maintenance of place fields using electrophysiology and blocking specifically LTD in freely-moving rats. We also show that exploration of a novel environment produces a widespread and pathway specific de novo synaptic depression in the dorsal hippocampus. Furthermore, disruption of this pathway-specific synaptic depression alters both the dynamics of place field formation and the stability of the newly formed place fields, affecting spatial memory in rats. These results suggest that activity-dependent synaptic depression is required for the acquisition and maintenance of novel spatial information.
Machine learned features from density of states for accurate adsorption energy prediction
Authors: Fung Victor , Hu Guoxiang , Ganesh P. , Sumpter Bobby G. 
Published: January 2021

AbstractMaterials databases generated by high-throughput computational screening, typically using density functional theory (DFT), have become valuable resources for discovering new heterogeneous catalysts, though the computational cost associated with generating them presents a crucial roadblock. Hence there is a significant demand for developing descriptors or features, in lieu of DFT, to accurately predict catalytic properties, such as adsorption energies. Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS). The model, DOSnet, is evaluated for a diverse set of adsorbates and surfaces, yielding a mean absolute error on the order of 0.1 eV. In addition, DOSnet can provide physically meaningful predictions and insights by predicting responses to external perturbations to the electronic structure without additional DFT calculations, paving the way for the accelerated discovery of materials and catalysts by exploration of the electronic space.
Single-cell transcriptome profiling of the vaginal wall in women with severe anterior vaginal prolapse
Authors: Li Yaqian , Zhang Qing-Yang , Sun Bao-Fa , Ma Yidi , Zhang Ye , Wang Min , Ma Congcong , Shi Honghui , Sun Zhijing , Chen Juan , Yang Yun-Gui , Zhu Lan 
Published: January 2021

AbstractAnterior vaginal prolapse (AVP) is the most common form of pelvic organ prolapse (POP) and has deleterious effects on women’s health. Despite recent advances in AVP diagnosis and treatment, a cell atlas of the vaginal wall in AVP has not been constructed. Here, we employ single-cell RNA-seq to construct a transcriptomic atlas of 81,026 individual cells in the vaginal wall from AVP and control samples and identify 11 cell types. We reveal aberrant gene expression in diverse cell types in AVP. Extracellular matrix (ECM) dysregulation and immune reactions involvement are identified in both non-immune and immune cell types. In addition, we find that several transcription factors associated with ECM and immune regulation are activated in AVP. Furthermore, we reveal dysregulated cell–cell communication patterns in AVP. Taken together, this work provides a valuable resource for deciphering the cellular heterogeneity and the molecular mechanisms underlying severe AVP.
Spatiotemporal profiling of cytosolic signaling complexes in living cells by selective proximity proteomics
Authors: Ke Mi , Yuan Xiao , He An , Yu Peiyuan , Chen Wendong , Shi Yu , Hunter Tony , Zou Peng , Tian Ruijun 
Published: January 2021

AbstractSignaling complexes are often organized in a spatiotemporal manner and on a minute timescale. Proximity labeling based on engineered ascorbate peroxidase APEX2 pioneered in situ capture of spatiotemporal membrane protein complexes in living cells, but its application to cytosolic proteins remains limited due to the high labeling background. Here, we develop proximity labeling probes with increased labeling selectivity. These probes, in combination with label-free quantitative proteomics, allow exploring cytosolic protein assemblies such as phosphotyrosine-mediated protein complexes formed in response to minute-scale EGF stimulation. As proof-of-concept, we systematically profile the spatiotemporal interactome of the EGFR signaling component STS1. For STS1 core complexes, our proximity proteomics approach shows comparable performance to affinity purification-mass spectrometry-based temporal interactome profiling, while also capturing additional—especially endosomally-located—protein complexes. In summary, we provide a generic approach for exploring the interactome of mobile cytosolic proteins in living cells at a temporal resolution of minutes.
How the anisotropy of surface oxide formation influences the transient activity of a surface reaction
Authors: Winkler P. , Zeininger J. , Suchorski Y. , Stöger-Pollach M. , Zeller P. , Amati M. , Gregoratti L. , Rupprechter G. 
Published: January 2021

AbstractScanning photoelectron microscopy (SPEM) and photoemission electron microscopy (PEEM) allow local surface analysis and visualising ongoing reactions on a µm-scale. These two spatio-temporal imaging methods are applied to polycrystalline Rh, representing a library of well-defined high-Miller-index surface structures. The combination of these techniques enables revealing the anisotropy of surface oxidation, as well as its effect on catalytic hydrogen oxidation. In the present work we observe, using locally-resolved SPEM, structure-sensitive surface oxide formation, which is summarised in an oxidation map and quantitatively explained by the novel step density (SDP) and step edge (SEP) parameters. In situ PEEM imaging of ongoing H2 oxidation allows a direct comparison of the local reactivity of metallic and oxidised Rh surfaces for the very same different stepped surface structures, demonstrating the effect of Rh surface oxides. Employing the velocity of propagating reaction fronts as indicator of surface reactivity, we observe a high transient activity of Rh surface oxide in H2 oxidation. The corresponding velocity map reveals the structure-dependence of such activity, representing a direct imaging of a structure-activity relation for plenty of well-defined surface structures within one sample.
Dose-dependent response to infection with SARS-CoV-2 in the ferret model and evidence of protective immunity
Authors: Ryan Kathryn A. , Bewley Kevin R. , Fotheringham Susan A. , Slack Gillian S. , Brown Phillip , Hall Yper , Wand Nadina I. , Marriott Anthony C. , Cavell Breeze E. , Tree Julia A. , Allen Lauren , Aram Marilyn J. , Bean Thomas J. , Brunt Emily , Buttigieg Karen R. , Carter Daniel P. , Cobb Rebecca , Coombes Naomi S. , Findlay-Wilson Steve J. , Godwin Kerry J. , Gooch Karen E. , Gouriet Jade , Halkerston Rachel , Harris Debbie J. , Hender Thomas H. , Humphries Holly E. , Hunter Laura , Ho Catherine M. K. , Kennard Chelsea L. , Leung Stephanie , Longet Stephanie , Ngabo Didier , Osman Karen L. , Paterson Jemma , Penn Elizabeth J. , Pullan Steven T. , Rayner Emma , Skinner Oliver , Steeds Kimberley , Taylor Irene , Tipton Tom , Thomas Stephen , Turner Carrie , Watson Robert J. , Wiblin Nathan R. , Charlton Sue , Hallis Bassam , Hiscox Julian A. , Funnell Simon , Dennis Mike J. , Whittaker Catherine J. , Catton Michael G. , Druce Julian , Salguero Francisco J. , Carroll Miles W. 
Published: January 2021

AbstractThere is a vital need for authentic COVID-19 animal models to enable the pre-clinical evaluation of candidate vaccines and therapeutics. Here we report a dose titration study of SARS-CoV-2 in the ferret model. After a high (5 × 106 pfu) and medium (5 × 104 pfu) dose of virus is delivered, intranasally, viral RNA shedding in the upper respiratory tract (URT) is observed in 6/6 animals, however, only 1/6 ferrets show similar signs after low dose (5 × 102 pfu) challenge. Following sequential culls pathological signs of mild multifocal bronchopneumonia in approximately 5–15% of the lung is seen on day 3, in high and medium dosed groups. Ferrets re-challenged, after virus shedding ceased, are fully protected from acute lung pathology. The endpoints of URT viral RNA replication & distinct lung pathology are observed most consistently in the high dose group. This ferret model of SARS-CoV-2 infection presents a mild clinical disease.
Microscopic mechanism of unusual lattice thermal transport in TlInTe2
Authors: Pal Koushik , Xia Yi , Wolverton Chris 
Published: January 2021

AbstractWe investigate the microscopic mechanism of ultralow lattice thermal conductivity (κl) of TlInTe2 and its weak temperature dependence using a unified theory of lattice heat transport, that considers contributions arising from the particle-like propagation as well as wave-like tunneling of phonons. While we use the Peierls–Boltzmann transport equation (PBTE) to calculate the particle-like contributions (κl(PBTE)), we explicitly calculate the off-diagonal (OD) components of the heat-flux operator within a first-principles density functional theory framework to determine the contributions (κl(OD)) arising from the wave-like tunneling of phonons. At each temperature, T, we anharmonically renormalize the phonon frequencies using the self-consistent phonon theory including quartic anharmonicity, and utilize them to calculate κl(PBTE) and κl(OD). With the combined inclusion of κl(PBTE), κl(OD), and additional grain-boundary scatterings, our calculations successfully reproduce the experimental results. Our analysis shows that large quartic anharmonicity of TlInTe2 (a) strongly hardens the low-energy phonon branches, (b) diminishes the three-phonon scattering processes at finite T, and (c) recovers the weaker than T−1 decay of the measured κl.
Emergence and control of complex behaviors in driven systems of interacting qubits with dissipation
Authors: Andreev A. V. , Balanov A. G. , Fromhold T. M. , Greenaway M. T. , Hramov A. E. , Li W. , Makarov V. V. , Zagoskin A. M. 
Published: January 2021

AbstractProgress in the creation of large-scale, artificial quantum coherent structures demands the investigation of their nonequilibrium dynamics when strong interactions, even between remote parts, are non-perturbative. Analysis of multiparticle quantum correlations in a large system in the presence of decoherence and external driving is especially topical. Still, the scaling behavior of dynamics and related emergent phenomena are not yet well understood. We investigate how the dynamics of a driven system of several quantum elements (e.g., qubits or Rydberg atoms) changes with increasing number of elements. Surprisingly, a two-element system exhibits chaotic behaviors. For larger system sizes, a highly stochastic, far from equilibrium, hyperchaotic regime emerges. Its complexity systematically scales with the size of the system, proportionally to the number of elements. Finally, we demonstrate that these chaotic dynamics can be efficiently controlled by a periodic driving field. The insights provided by our results indicate the possibility of a reduced description for the behavior of a large quantum system in terms of the transitions between its qualitatively different dynamical regimes. These transitions are controlled by a relatively small number of parameters, which may prove useful in the design, characterization, and control of large artificial quantum structures.
Spiny mouse (Acomys): an emerging research organism for regenerative medicine with applications beyond the skin
Authors: Gaire Janak , Varholick Justin A. , Rana Sabhya , Sunshine Michael D. , Doré Sylvain , Barbazuk W. Brad , Fuller David D. , Maden Malcolm , Simmons Chelsey S. 
Published: January 2021

AbstractThe spiny mouse (Acomys species) has emerged as an exciting research organism due to its remarkable ability to undergo scarless regeneration of skin wounds and ear punches. Excitingly, Acomys species demonstrate scar-free healing in a wide-range of tissues beyond the skin. In this perspective article, we discuss published findings from a variety of tissues to highlight how this emerging research organism could shed light on numerous clinically relevant human diseases. We also discuss the challenges of working with this emerging research organism and suggest strategies for future Acomys-inspired research.
Strong and tunable spin–orbit interaction in a single crystalline InSb nanosheet
Authors: Chen Yuanjie , Huang Shaoyun , Pan Dong , Xue Jianhong , Zhang Li , Zhao Jianhua , Xu H. Q. 
Published: January 2021

AbstractA dual-gate InSb nanosheet field-effect device is realized and is used to investigate the physical origin and the controllability of the spin–orbit interaction in a narrow bandgap semiconductor InSb nanosheet. We demonstrate that by applying a voltage over the dual gate, efficiently tuning of the spin–orbit interaction in the InSb nanosheet can be achieved. We also find the presence of an intrinsic spin–orbit interaction in the InSb nanosheet at zero dual-gate voltage and identify its physical origin as a build-in asymmetry in the device layer structure. Having a strong and controllable spin–orbit interaction in an InSb nanosheet could simplify the design and realization of spintronic deceives, spin-based quantum devices, and topological quantum devices.
Machine learning-based prediction of COVID-19 diagnosis based on symptoms
Authors: Zoabi Yazeed , Deri-Rozov Shira , Shomron Noam 
Published: January 2021

AbstractEffective screening of SARS-CoV-2 enables quick and efficient diagnosis of COVID-19 and can mitigate the burden on healthcare systems. Prediction models that combine several features to estimate the risk of infection have been developed. These aim to assist medical staff worldwide in triaging patients, especially in the context of limited healthcare resources. We established a machine-learning approach that trained on records from 51,831 tested individuals (of whom 4769 were confirmed to have COVID-19). The test set contained data from the subsequent week (47,401 tested individuals of whom 3624 were confirmed to have COVID-19). Our model predicted COVID-19 test results with high accuracy using only eight binary features: sex, age ≥60 years, known contact with an infected individual, and the appearance of five initial clinical symptoms. Overall, based on the nationwide data publicly reported by the Israeli Ministry of Health, we developed a model that detects COVID-19 cases by simple features accessed by asking basic questions. Our framework can be used, among other considerations, to prioritize testing for COVID-19 when testing resources are limited.