5,075 research outputs found

    Activation of extracellular signal-regulated protein kinase 5 is essential for cystitis- and nerve growth factor-induced calcitonin gene-related peptide expression in sensory neurons

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    Background Cystitis causes considerable neuronal plasticity in the primary afferent pathways. The molecular mechanism and signal transduction underlying cross talk between the inflamed urinary bladder and sensory sensitization has not been investigated. Results In a rat cystitis model induced by cyclophosphamide (CYP) for 48 h, the mRNA and protein levels of the excitatory neurotransmitter calcitonin gene-related peptide (CGRP) are increased in the L6 dorsal root ganglia (DRG) in response to bladder inflammation. Cystitis-induced CGRP expression in L6 DRG is triggered by endogenous nerve growth factor (NGF) because neutralization of NGF with a specific NGF antibody reverses CGRP up-regulation during cystitis. CGRP expression in the L6 DRG neurons is also enhanced by retrograde NGF signaling when NGF is applied to the nerve terminals of the ganglion-nerve two-compartmented preparation. Characterization of the signaling pathways in cystitis- or NGF-induced CGRP expression reveals that the activation (phosphorylation) of extracellular signal-regulated protein kinase (ERK)5 but not Akt is involved. In L6 DRG during cystitis, CGRP is co-localized with phospho-ERK5 but not phospho-Akt. NGF-evoked CGRP up-regulation is also blocked by inhibition of the MEK/ERK pathway with specific MEK inhibitors U0126 and PD98059, but not by inhibition of the PI3K/Akt pathway with inhibitor LY294002. Further examination shows that cystitis-induced cAMP-responsive element binding protein (CREB) activity is expressed in CGRP bladder afferent neurons and is co-localized with phospho-ERK5 but not phospho-Akt. Blockade of NGF action in vivo reduces the number of DRG neurons co-expressing CGRP and phospho-CREB, and reverses cystitis-induced increases in micturition frequency. Conclusions A specific pathway involving NGF-ERK5-CREB axis plays an essential role in cystitis-induced sensory activation

    Higher-order Graph Attention Network for Stock Selection with Joint Analysis

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    Stock selection is important for investors to construct profitable portfolios. Graph neural networks (GNNs) are increasingly attracting researchers for stock prediction due to their strong ability of relation modelling and generalisation. However, the existing GNN methods only focus on simple pairwise stock relation and do not capture complex higher-order structures modelling relations more than two nodes. In addition, they only consider factors of technical analysis and overlook factors of fundamental analysis that can affect the stock trend significantly. Motivated by them, we propose higher-order graph attention network with joint analysis (H-GAT). H-GAT is able to capture higher-order structures and jointly incorporate factors of fundamental analysis with factors of technical analysis. Specifically, the sequential layer of H-GAT take both types of factors as the input of a long-short term memory model. The relation embedding layer of H-GAT constructs a higher-order graph and learn node embedding with GAT. We then predict the ranks of stock return. Extensive experiments demonstrate the superiority of our H-GAT method on the profitability test and Sharp ratio over both NSDAQ and NYSE datasetsComment: 12 pages, 6 figures

    Analysis of Linkage Effects among Currency Networks Using REER Data

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    We modeled the currency networks through the use of REER (real effective exchange rate) instead of a bilateral exchange rate in order to overcome the confusion in selecting base currencies. Based on the MST (minimum spanning tree) approach and the rolling-window method, we constructed time-varying and correlation-based networks with which we investigate the linkage effects among different currencies. In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. The study demonstrated that obvious linkage effects existed among currency networks and the euro (EUR) was confirmed as the predominant world currency. Additionally, we used the rollingwindow method to investigate the stability of linkage effects, doing so by calculating the mean correlations and mean distances as well as the normalized tree length and degrees of those currencies. The results showed that financial crises during the study period had a great effect on the currency network's topology structure and led to more clustered currency networks. Our results suggested that it is more appropriate to estimate the linkage effects among currency networks through the use of REER data

    Polycyclic Aromatic Hydrocarbons Concentration in Straw Biochar with different Particle Size

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    AbstractBiochar, a carbon-rich material formed by a biomass pyrolyzed at relatively low temperatures (≤700°C), showed attractive sorption capacity on both organic pollutants and heavy metals and wildly used in various areas of environmental engineering. However, polycyclic aromatic hydrocarbons (PAHs) may also be assumed to be produced for the oxygen-limited pyrolysis condition in biochar production process. It is not well known about the affect of particle size in concentration and distributing characteristic of PAHs of biochar. In the current study, twenty-seven PAHs concentration in maize straw biochar produced with different powder particle size (9.31, 20.26, 60.77, 71.07, 101.9μm) were quantified, and the ∑27PAHs, total LMW PAHs, total MMW PAHs and total HMW PAHs concentration were analyzed. As the particle size increase, the ∑27PAHs concentrations show a trend of firstly increase and then decrease, and the maximum appears at 60.77μm (166.52 ng/g) and the minimum appears at 101.90μm (14.63 ng/g). LMW total PAHs and total MMW PAHs concentrations firstly increase and then decrease, with the particle size increasing from 9.31μm to 101.9μm. Meanwhile, the total HMW PAH concentrations decrease gradually when biochar particle size increasing. Compared to US, UK background soil concentrations and Canada standards, it is appropriate to conclude that PAHs in straw biochar have minimal effects after application to soil especially at 101.9μm

    Electrical switching of a moir\'{e} ferroelectric superconductor

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    Electrical control of superconductivity is critical for nanoscale superconducting circuits including cryogenic memory elements, superconducting field-effect transistors (FETs), and gate-tunable qubits. Superconducting FETs operate through continuous tuning of carrier density, but there has not yet been a bistable superconducting FET, which could serve as a new type of cryogenic memory element. Recently, unusual ferroelectricity in Bernal-stacked bilayer graphene aligned to its insulating hexagonal boron nitride (BN) gate dielectrics was discovered. Here, we report the observation of ferroelectricity in magic-angle twisted bilayer graphene (MATBG) with aligned BN layers. This ferroelectric behavior coexists alongside the strongly correlated electron system of MATBG without disrupting its correlated insulator or superconducting states. This all-van der Waals platform enables configurable switching between different electronic states of this rich system. To illustrate this new approach, we demonstrate reproducible bistable switching between the superconducting, metallic, and correlated insulator states of MATBG using gate voltage or electric displacement field. These experiments unlock the potential to broadly incorporate this new moir\'{e} ferroelectric superconductor into highly tunable superconducting electronics
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