bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural basis for the complex DNA binding behavior of the plant stem cell regulator WUSCHEL
Authors: Sloan Jeremy , Hakenjos Jana P. , Gebert Michael , Ermakova Olga , Gumiero Andrea , Stier Gunter , Wild Klemens , Sinning Irmgard , Lohmann Jan U. 
Published: May 2020

AbstractStem cells are one of the foundational evolutionary novelties that allowed the independent emergence of multicellularity in the plant and animal lineages. In plants, the homeodomain (HD) transcription factor WUSCHEL (WUS) is essential for the maintenance of stem cells in the shoot apical meristem. WUS has been reported to bind to diverse DNA motifs and to act as transcriptional activator and repressor. However, the mechanisms underlying this remarkable behavior have remained unclear. Here, we quantitatively delineate WUS binding to three divergent DNA motifs and resolve the relevant structural underpinnings. We show that WUS exhibits a strong binding preference for TGAA repeat sequences, while retaining the ability to weakly bind to TAAT elements. This behavior is attributable to the formation of dimers through interactions of specific residues in the HD that stabilize WUS DNA interaction. Our results provide a mechanistic basis for dissecting WUS dependent regulatory networks in plant stem cell control.
Solvent-mediated assembly of atom-precise gold–silver nanoclusters to semiconducting one-dimensional materials
Authors: Yuan Peng , Zhang Ruihua , Selenius Elli , Ruan Pengpeng , Yao Yangrong , Zhou Yang , Malola Sami , Häkkinen Hannu , Teo Boon K. , Cao Yang , Zheng Nanfeng 
Published: May 2020

AbstractBottom-up design of functional device components based on nanometer-sized building blocks relies on accurate control of their self-assembly behavior. Atom-precise metal nanoclusters are well-characterizable building blocks for designing tunable nanomaterials, but it has been challenging to achieve directed assembly to macroscopic functional cluster-based materials with highly anisotropic properties. Here, we discover a solvent-mediated assembly of 34-atom intermetallic gold–silver clusters protected by 20 1-ethynyladamantanes into 1D polymers with Ag–Au–Ag bonds between neighboring clusters as shown directly by the atomic structure from single-crystal X-ray diffraction analysis. Density functional theory calculations predict that the single crystals of cluster polymers have a band gap of about 1.3 eV. Field-effect transistors fabricated with single crystals of cluster polymers feature highly anisotropic p-type semiconductor properties with ≈1800-fold conductivity in the direction of the polymer as compared to cross directions, hole mobility of ≈0.02 cm2 V−1 s−1, and an ON/OFF ratio up to ≈4000. This performance holds promise for further design of functional cluster-based materials with highly anisotropic semiconducting properties.
Coherent multidimensional photoelectron spectroscopy of ultrafast quasiparticle dressing by light
Authors: Reutzel Marcel , Li Andi , Wang Zehua , Petek Hrvoje 
Published: May 2020

AbstractDepending on the applied strength, electromagnetic fields in electronic materials can induce dipole transitions between eigenstates or distort the Coulomb potentials that define them. Between the two regimes, they can also modify the electronic properties in more subtle ways when electron motion becomes governed by time and space-periodic potentials. The optical field introduces new virtual bands through Floquet engineering that under resonant conditions interacts strongly with the preexisting bands. Under such conditions the virtual bands can become real, and real ones become virtual as the optical fields and electronic band dispersions entangle the electronic response. We reveal optical dressing of electronic bands in a metal by exciting four-photon photoemission from the Cu(111) surface involving a three-photon resonant transition from the Shockley surface band to the first image potential band. Attosecond resolved interferometric scanning between identical pump–probe pulses and its Fourier analysis reveal how the optical field modifies the electronic properties of a solid through combined action of dipole excitation and field dressing.
The NMDA receptor regulates competition of epithelial cells in the Drosophila wing
Authors: Banreti Agnes R. , Meier Pascal 
Published: May 2020

AbstractCell competition is an emerging principle that eliminates suboptimal or potentially dangerous cells. For ‘unfit’ cells to be detected, their competitive status needs to be compared to the collective fitness of cells within a tissue. Here we report that the NMDA receptor controls cell competition of epithelial cells and Myc supercompetitors in the Drosophila wing disc. While clonal depletion of the NMDA receptor subunit NR2 results in their rapid elimination via the TNF/Eiger>JNK signalling pathway, local over-expression of NR2 causes NR2 cells to acquire supercompetitor-like behaviour that enables them to overtake the tissue through clonal expansion that causes, but also relies on, the killing of surrounding cells. Consistently, NR2 is utilised by Myc clones to provide them with supercompetitor status. Mechanistically, we find that the JNK>PDK signalling axis in ‘loser’ cells reprograms their metabolism, driving them to produce and transfer lactate to winners. Preventing lactate transfer from losers to winners abrogates NMDAR-mediated cell competition. Our findings demonstrate a functional repurposing of NMDAR in the surveillance of tissue fitness.
Benthic fauna declined on a whitening Antarctic continental shelf
Authors: Pineda-Metz Santiago E. A. , Gerdes Dieter , Richter Claudio 
Published: May 2020

AbstractIce retreat in West Antarctica and Antarctic Peninsula has led to important changes in seafloor communities and gains in benthic blue carbon. In most of the Antarctic, however, sea ice increased between the 1970s and 2014, but its effects on the benthos remain largely unexplored. Here, we provide a 1988–2014 record of macro- and megafauna from the north-eastern Weddell Sea shelf, where benthic biomass decreased by two thirds and composition shifted from suspension feeders to deposit feeders. Concomitant increases in sea-ice cover suggest a reduced flux of primary production to the benthos. As benthic communities are major repositories for Antarctic biodiversity and play an important role in biogeochemical cycling, the observed changes have far-reaching consequences for the Antarctic ecosystem and its feedback to the climate system. The findings underscore the importance of long-term ecological monitoring in a region vulnerable to warming and ice-shelf collapse.
Selective NMR observation of the SEI–metal interface by dynamic nuclear polarisation from lithium metal
Authors: Hope Michael A. , Rinkel Bernardine L. D. , Gunnarsdóttir Anna B. , Märker Katharina , Menkin Svetlana , Paul Subhradip , Sergeyev Ivan V. , Grey Clare P. 
Published: May 2020

AbstractWhile lithium metal represents the ultimate high-energy-density battery anode material, its use is limited by dendrite formation and associated safety risks, motivating studies of the solid–electrolyte interphase layer that forms on the lithium, which is key in controlling lithium metal deposition. Dynamic nuclear polarisation enhanced NMR can provide important structural information; however, typical exogenous dynamic nuclear polarisation experiments, in which organic radicals are added to the sample, require cryogenic sample cooling and are not selective for the interface between the metal and the solid–electrolyte interphase. Here we instead exploit the conduction electrons of lithium metal to achieve an order of magnitude hyperpolarisation at room temperature. We enhance the 7Li, 1H and 19F NMR spectra of solid–electrolyte interphase species selectively, revealing their chemical nature and spatial distribution. These experiments pave the way for more ambitious room temperature in situ dynamic nuclear polarisation studies of batteries and the selective enhancement of metal–solid interfaces in a wider range of systems.
Using Coherence-based spectro-spatial filters for stimulus features prediction from electro-corticographic recordings
Authors: Delgado Saa Jaime , Christen Andy , Martin Stephanie , Pasley Brian N. , Knight Robert T. , Giraud Anne-Lise 
Published: May 2020

AbstractThe traditional approach in neuroscience relies on encoding models where brain responses are related to different stimuli in order to establish dependencies. In decoding tasks, on the contrary, brain responses are used to predict the stimuli, and traditionally, the signals are assumed stationary within trials, which is rarely the case for natural stimuli. We hypothesize that a decoding model assuming each experimental trial as a realization of a random process more likely reflects the statistical properties of the undergoing process compared to the assumption of stationarity. Here, we propose a Coherence-based spectro-spatial filter that allows for reconstructing stimulus features from brain signal’s features. The proposed method extracts common patterns between features of the brain signals and the stimuli that produced them. These patterns, originating from different recording electrodes are combined, forming a spatial filter that produces a unified prediction of the presented stimulus. This approach takes into account frequency, phase, and spatial distribution of brain features, hence avoiding the need to predefine specific frequency bands of interest or phase relationships between stimulus and brain responses manually. Furthermore, the model does not require the tuning of hyper-parameters, reducing significantly the computational load attached to it. Using three different cognitive tasks (motor movements, speech perception, and speech production), we show that the proposed method consistently improves stimulus feature predictions in terms of correlation (group averages of 0.74 for motor movements, 0.84 for speech perception, and 0.74 for speech production) in comparison with other methods based on regularized multivariate regression, probabilistic graphical models and artificial neural networks. Furthermore, the model parameters revealed those anatomical regions and spectral components that were discriminant in the different cognitive tasks. This novel method does not only provide a useful tool to address fundamental neuroscience questions, but could also be applied to neuroprosthetics.
Effect of commercial vaginal products on the growth of uropathogenic and commensal vaginal bacteria
Authors: Hung Kristin J. , Hudson Patricia L. , Bergerat Agnes , Hesham Helai , Choksi Namit , Mitchell Caroline 
Published: May 2020

AbstractHalf of postmenopausal women experience genitourinary syndrome of menopause, for which many use lubricating vaginal products. The effect of vaginal products on uropathogenic and commensal vaginal bacteria is poorly understood. We evaluated the effect of five common vaginal products (KY Jelly, Replens Silky Smooth lubricant, coconut oil, Replens Long-Lasting moisturizer or Trimo-San) on growth and viability ofEscherichia coliandLactobacillus crispatus. Bacteria were co-cultured products alone and in the presence of both vaginal epithelial cells and selected products. Bacterial growth was compared between conditions using an unpaired t-test or ANOVA, as appropriate. All products except for coconut oil significantly inhibited growth of laboratory and clinical strains ofEscherichia coli(p < 0.02). Only two products (Replens Long-Lasting moisturizer and Trimo-San) significantly inhibited growth ofLactobacillus crispatus(p < 0.01), while the product Replens Silky Smooth stimulated growth (p < 0.01). Co-culture of selected products in the presence of vaginal epithelial cells eliminated the inhibitory effects of the products on E. coli. In conclusion,in vitroexposure to vaginal moisturizing and lubricating products inhibited growth ofEscherichia coli, though the inhibition was mitigated by the presence of vaginal epithelial cells.Lactobacillus crispatusdemonstrated less growth inhibition thanEscherichia coli.
Reconfigurable Meta-Coupler Employing Hybrid Metal-Graphene Metasurfaces
Authors: Tavakol Mohammad Reza , Khavasi Amin 
Published: May 2020

AbstractEfficient excitation of surface wave (SW) remains one of the most challenging considerations in the photonics and plasmonics areas. Inspired by recent investigations of metasurfaces, we propose a hybrid metal-graphene transmitarray converting incident propagating wave (PW) to SW, as a solution for SW excitations–a meta-coupler. The structure comprises ultra-thin four-layer transparent metasurfaces in which H-shaped etched metal films together with graphene patches are employed, and also all four layers are identical. Full-wave simulations demonstrate that the suggested meta-coupler possesses an efficiency of 46% and a directivity of 19 dB, which is promising in the terahertz (THz) range. At the same time, in light of unique graphene characteristics, the proposed device is tunable and easily reconfigurable, i.e., the direction of converted SWs can be electrically switched from right to left and vice versa. We believe that this system responds to emerging applications such as THz communications and sensing, and furthermore the employed architecture introduce electrostatically tunable building blocks being able to develop graphene plasmonic components effectively.
Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments
Authors: Mencattini A. , Di Giuseppe D. , Comes M. C. , Casti P. , Corsi F. , Bertani F. R. , Ghibelli L. , Businaro L. , Di Natale C. , Parrini M. C. , Martinelli E. 
Published: May 2020

AbstractWe describe a novel method to achieve a universal, massive, and fully automated analysis of cell motility behaviours, starting from time-lapse microscopy images. The approach was inspired by the recent successes in application of machine learning for style recognition in paintings and artistic style transfer. The originality of the method relies i) on the generation of atlas from the collection of single-cell trajectories in order to visually encode the multiple descriptors of cell motility, and ii) on the application of pre-trained Deep Learning Convolutional Neural Network architecture in order to extract relevant features to be used for classification tasks from this visual atlas. Validation tests were conducted on two different cell motility scenarios: 1) a 3D biomimetic gels of immune cells, co-cultured with breast cancer cells in organ-on-chip devices, upon treatment with an immunotherapy drug; 2) Petri dishes of clustered prostate cancer cells, upon treatment with a chemotherapy drug. For each scenario, single-cell trajectories are very accurately classified according to the presence or not of the drugs. This original approach demonstrates the existence of universal features in cell motility (a so called “motility style”) which are identified by the DL approach in the rationale of discovering the unknown message in cell trajectories.
Algebraic Study of diatomic Molecules: homonuclear molecules H2 and N2
Authors: Amiri N. , Ghapanvari M. , Jafarizadeh M. A. 
Published: May 2020

AbstractIt is the aim of this study to discuss for two-body systems like homonuclear molecules in which eigenvalues and eigenfunctions are obtained by exact solutions of the solvable models based on SU(1, 1) Lie algebras. Exact solutions of the solvable Hamiltonian regarding the relative motion in a two-body system on Lie algebras were obtained. The U(1) ↔ O(2), U(3) ↔ O(4) and Uq(3) ↔ Oq(4) transitional Hamiltonians are employed to described for H2 and N2 molecules. Applications to the rotation-vibration spectrum for the diatomic molecule indicate that complicated Hamiltonian can be easily determined via the exactly solvable method. The results confirm the mixing of both vibrating and rotating structures in H2 and N2 molecules.
The cherry 6+9K SNP array: a cost-effective improvement to the cherry 6K SNP array for genetic studies
Authors: Vanderzande Stijn , Zheng Ping , Cai Lichun , Barac Goran , Gasic Ksenija , Main Dorrie , Iezzoni Amy , Peace Cameron 
Published: May 2020

AbstractCherry breeding and genetic studies can benefit from genome-wide genetic marker assays. Currently, a 6K SNP array enables genome scans in cherry; however, only a third of these SNPs are informative, with low coverage in many genomic regions. Adding previously detected SNPs to this array could provide a cost-efficient upgrade with increased genomic coverage across the 670 cM/352.9 Mb cherry whole genome sequence. For sweet cherry, new SNPs were chosen following a focal point strategy, grouping six to eight SNPs within 10-kb windows with an average of 0.6 cM (627 kb) between focal points. Additional SNPs were chosen to represent important regions. Sweet cherry, thefruticosasubgenome of sour cherry, and cherry organellar genomes were targeted with 6942, 2020, and 38 new SNPs, respectively. The +9K add-on provided 2128, 1091, and 70 new reliable, polymorphic SNPs for sweet cherry and theaviumand thefruticosasubgenomes of sour cherry, respectively. For sweet cherry, 1241 reliable polymorphic SNPs formed 237 informative focal points, with another 2504 SNPs in-between. The +9K SNPs increased genetic resolution and genome coverage of the original cherry SNP array and will help increase understanding of the genetic control of key traits and relationships among individuals in cherry.
Enhanced stability of quantum Hall skyrmions under radio-frequency radiations
Authors: Pan W. , Reno J. L. , Reyes A. P. 
Published: May 2020

AbstractWe present in this paper the results from a recent study on the stability of the quantum Hall skyrmions state at a Landau level filling factor (ν) close to ν = 1 in a narrow GaAs quantum well. Consistent with previous work, a resonant behavior is observed in the resistively detected NMR measurements. In the subsequent current-voltage (I-V) measurements to examine its breakdown behavior under radio frequency radiations, we observe that the critical current assumes the largest value right at the 75As nuclear resonant frequency. We discuss possible origin for this unexpectedly enhanced stability.
Comparisons between small ribosomal RNA and theoretical minimal RNA ring secondary structures confirm phylogenetic and structural accretion histories
Authors: Demongeot Jacques , Seligmann Hervé 
Published: May 2020

AbstractRibosomal RNAs are complex structures that presumably evolved by tRNA accretions. Statistical properties of tRNA secondary structures correlate with genetic code integration orders of their cognate amino acids. Ribosomal RNA secondary structures resemble those of tRNAs with recent cognates. Hence, rRNAs presumably evolved from ancestral tRNAs. Here, analyses compare secondary structure subcomponents of small ribosomal RNA subunits with secondary structures of theoretical minimal RNA rings, presumed proto-tRNAs. Two independent methods determined different accretion orders of rRNA structural subelements: (a) classical comparative homology and phylogenetic reconstruction, and (b) a structural hypothesis assuming an inverted onion ring growth where the three-dimensional ribosome’s core is most ancient and peripheral elements most recent. Comparisons between (a) and (b) accretions orders with RNA ring secondary structure scales show that recent rRNA subelements are: 1. more like RNA rings with recent cognates, indicating ongoing coevolution between tRNA and rRNA secondary structures; 2. less similar to theoretical minimal RNA rings with ancient cognates. Our method fits (a) and (b) in all examined organisms, more with (a) than (b). Results stress the need to integrate independent methods. Theoretical minimal RNA rings are potential evolutionary references for any sequence-based evolutionary analyses, independent of the focal data from that study.
The role of reagent adding sequence in the NH4+-N recovery by MAP method
Authors: He Caiqing , Chen Yunnen , Liu Chen , Jiang Yang , Yin Ruoyu , Qiu Tingsheng 
Published: May 2020

AbstractAmmonium-nitrogen (NH4+-N) recovery from high concentration of NH4+-N-containing wastewater by struvite (MgNH4PO4·6H2O, MAP) precipitation method has been realized, but whether NH4+-N recovery under different reagent adding sequence of NaOH, solid Mg salt and P salt can generate different effects, remains ambiguous. In view of the problem, four modes to add reagents were investigated in detail on the formation of struvite. The results show that the Mode IV (M-IV, i.e. using 50% NH4+-N wastewater to dissolve completely the Mg salt and the P salt, respectively and then simultaneously poured into a beaker to mix the solution evenly and adjust the pH to 9.5.) has the highest NH4+-N recovery efficiency (90.80%) and the maximum mass of precipitates (896 mg) because of the more amount of alkali and initial seed formation. From the morphology of the obtained precipitates, it can be seen that sample M-IV is more loose and porous than the others. XRD patterns show that the four products under the different modes basically agree with the standard MAP.
Detection of Tuberculosis by The Analysis of Exhaled Breath Particles with High-resolution Mass Spectrometry
Authors: Chen Dapeng , Bryden Wayne A. , Wood Robin 
Published: May 2020

AbstractTuberculosis remains a global health threat killing over 1 million people per year. Current sputum-based diagnostics are specific but lack sensitivity resulting in treatment of many sputum negative cases. In this proof-of-concept study, we used high-resolution mass spectrometry to identify specific lipids in peripheral lung fluid samples of TB patients and controls, captured using a novel non-invasive sampling system. Exhaled respiratory particles were collected in liquid and after concentration and lipid extraction directly infused into a high-resolution mass spectrometer. High-resolution mass spectrometric data collection was conducted in a dual ion mode and chemical compositions were constructed using accurate mass measurement. Over 400 features with high segregating capacity were extracted and optimized using feature selection algorithm and machine learning, from which the accuracy of detection of positive tuberculosis patients was estimated. This current strategy provides sensitivity offered by high-resolution mass spectrometry and can be readily susceptible for developing a novel clinical assay exploring peripheral lung fluid for the detection of active TB cases.
Accuracy of ancestral state reconstruction for non-neutral traits
Authors: Holland Barbara R. , Ketelaar-Jones Saan , O’Mara Aidan R. , Woodhams Michael D. , Jordan Gregory J. 
Published: May 2020

AbstractThe assumptions underpinning ancestral state reconstruction are violated in many evolutionary systems, especially for traits under directional selection. However, the accuracy of ancestral state reconstruction for non-neutral traits is poorly understood. To investigate the accuracy of ancestral state reconstruction methods, trees and binary characters were simulated under the BiSSE (Binary State Speciation and Extinction) model using a wide range of character-state-dependent rates of speciation, extinction and character-state transition. We used maximum parsimony (MP), BiSSE and two-state Markov (Mk2) models to reconstruct ancestral states. Under each method, error rates increased with node depth, true number of state transitions, and rates of state transition and extinction; exceeding 30% for the deepest 10% of nodes and highest rates of extinction and character-state transition. Where rates of character-state transition were asymmetrical, error rates were greater when the rate away from the ancestral state was largest. Preferential extinction of species with the ancestral character state also led to higher error rates. BiSSE outperformed Mk2 in all scenarios where either speciation or extinction was state dependent and outperformed MP under most conditions. MP outperformed Mk2 in most scenarios except when the rates of character-state transition and/or extinction were highly asymmetrical and the ancestral state was unfavoured.