17 research outputs found
Regulation of Dendritic Spine Morphogenesis by Insulin Receptor Substrate 53, a Downstream Effector of Rac1 and Cdc42 Small GTPases
The small GTPases Rac1 and Cdc42 are key regulators of the morphogenesis of actin-rich dendritic spines in neurons. However, little is known about how activated Rac1/Cdc42 regulates dendritic spines. Insulin receptor substrate 53 (IRSp53), which is highly expressed in the postsynaptic density (PSD), is known to link activated Rac1/Cdc42 to downstream effectors for actin regulation in non-neural cells. Here, we report that IRSp53 interacts with two specific members of the PSD-95 family, PSD-95 and chapsyn-110/PSD-93, in brain. An IRSp53 mutant lacking the C-terminal PSD-95-binding motif shows significant loss of synaptic localization in cultured neurons. Overexpression of IRSp53 in cultured neurons increases the density of dendritic spines but does not affect their length or width. Conversely, short-interfering RNA-mediated knock-down of IRSp53 reduces the density, length, and width of spines. In addition, the density and size of spines are decreased by a dominant-negative IRSp53 with a point mutation in the Src homology 3 (SH3) domain and a dominant-negative proline-rich region of WAVE2 (Wiskott-Aldrich syndrome protein family Verprolin-homologous protein), a downstream effector of IRSp53 that binds to the SH3 domain of IRSp53. These results suggest that PSD-95 interaction is an important determinant of synaptic IRSp53 localization and that the SH3 domain of IRSp53 links activated Rac1/Cdc42 to downstream effectors for the regulation of spine morphogenesis
Development of the automatic load modelling system using PQM data on industry site
Load modelling is a very important issue for the power system analysis. It affects the results of the several simulations such as a transient analysis, voltage stability, load shedding amounts and etc. And it is very difficult to describe the load models because there are so many components which have different characteristics in the loads. KEPCO installed the power quality measurements on 154 kV industry sites and measured voltage, current, active power and reactive power. In this paper, an automatic load modelling system which uses those data is presented. It includes an algorithm for estimating load model parameters of two induction motors and ZIP load model. Parameters of load model are calculated automatically and are accumulated in the load modelling automation system server. The results of parameter estimation using the data of the real power system are also shown
Evaluation of Temporal Contribution of Groundwater to a Small Lake through Analyses of Water Quantity and Quality
Groundwater can flow into or out of surface water and thus can greatly affect the quantity and quality of surface water. In this study, we conducted a water quantity and quality analysis for 11 months in 2018 and 2019 to evaluate the temporal contribution of groundwater to surface water at Osongji, a small lake located in Jeonju-si, Jeollabuk-do, Korea. Groundwater fluxes and groundwater and surface water levels were measured using seepage meters and a piezometer, respectively. On-site water quality parameters, cations, and anions for groundwater and surface water were analyzed. Hydrogen and oxygen isotopes for groundwater, surface water, and rainwater were also analyzed. Groundwater influx did not correlate directly to precipitation, suggesting that it may be delayed after rainwater infiltration. Aqueous chemistry indicated that the hydrogeochemical characteristics of surface water were substantially affected by groundwater. The isotopic composition of surface water changed over time, indicating a different contribution of groundwater in different seasons. This study shows that water quantity and quality data can be used in combination to evaluate temporal changes in the groundwater contribution to surface water
Ferroelectricity-Coupled 2D-MXene-Based Hierarchically Designed High-Performance Stretchable Triboelectric Nanogenerator
Triboelectric nanogenerators based on the state-of-the-art functional materials and device engineering provide an exciting platform for future multifunctional electronics, but it remains challenging to realize due to the lack of in-depth understanding on the functional properties of nanomaterials that are compatible with microstructural engineering. In this study, a high-performance stretchable (similar to 60% strain) triboelectric nanogenerator is demonstrated via an interlocked microstructural device configuration sandwiched between silvernanowire-(Ag-NW) electrodes and hierarchically engineered spongy thermoplastic polyurethane (TPU) polymer composite with ferroelectric barium-titanate-coupled (BTO-coupled) 2D MXene (Ti3C2Tx) nanosheets. The use of MXene results in an increase in the dielectric constant whereas the dielectric loss is lowered via coupling with the ferroelectricity of BTO, which increases the overall output performance of the nanogenerator. The spongy nature of the composite film increases the capacitance variation under deformation, which results in improved energyconversion efficiency (similar to 79%) and pressure sensitivity (4.6 VkPa-1 and 2.5 mAkPa-1) of the device. With the quantum-mechanically calculated electronic structure, the device converts biomechanical energy to electrical energy and generates an open-circuit output voltage of 260 V, short-circuit output current of 160 mA/m2, and excellent power output of 6.65 W/m2, which is sufficient to operate several consumer electronics. Owing to its superior pressure sensitivity and efficiency, the device enables a broad range of applications including real-time clinical human vital-sign monitoring, acoustic sensing, and multidimensional gesture-sensing functionality of a robotic hand. Considering the ease of fabrication, excellent functionality of the hierarchical polymer nanocomposite, and outstanding energy-harvesting performance of nanogenerators, this work is expected to stimulate the development of next-generation self-powered technology
Ultra-stretchable yet tough, healable, and biodegradable triboelectric devices with microstructured and ionically crosslinked biogel
To reduce the environmental impact of non-biodegradable electronic waste, developing sustainable technology with biomass-derived biodegradable materials are essential. However, the insufficient mechanical and electrical performances of the conventional biodegradable materials with planar structures often limit their use in bioelectronics. Here, we develop a high-performance ionic biogel device based on three-dimensional (3D) microstructured design of completely healable yet fully biodegradable biogel by using ionically cross-linked biomass resource, gelatin. The stress-absorbing geometry of 3D microstructure improves the mechanical resilience and facilitates highly elastic (similar to 4000%), notch-tolerable and extremely tough (similar to 10,998 J/m(2)) ionic biogels. In addition, the interlocked feature of 3D architecture provides the ionic diode characteristics of the biogel that enhances the triboelectric energy harvesting capability from external stimuli of pressure and temperature, even under an extreme stretching condition. Our triboelectric nanogenerator based on 3D ionic biogels exhibits excellent power output (similar to 325 mW/m(2)), superior energy conversion efficiency (similar to 70.7%) and high-resolution mechano- (similar to 9 Pa) as well as thermo- (similar to 0.03 K) transduction functionalities with long-term stability. The 3D ionic biogel recovers its original electrical properties even after mechanical damage through self-healing. For proof-of-concept demonstrations, the gelatin biogel serve in soft and conformable electronic skins to monitor low-frequency vital signs and high-frequency acoustic waves, for haptic perception of surface textures, and in robotic tactile skins, providing a new benchmark as a clean and green technology for soft bio-electronic devices with zero waste
Application of Deep Reinforcement Learning to Dynamic Verification of DRAM Designs
This paper presents a deep neural network based test vector generation method for dynamic verification of memory devices. The proposed method is built on reinforcement learning framework, where the action is input stimulus on device pins and the reward is coverage score of target circuitry. The developed agent efficiently explores high-dimensional and large action space by using policy gradient method with ??-nearest neighbor search, transfer learning, and replay buffer. The generated test vectors attained the coverage score of 100% for fifteen representative circuit blocks of modern DRAM design. The output vector length was only 7% of the human-created vector length
An intramolecular interaction between the FHA domain and a coiled coil negatively regulates the kinesin motor KIF1A
Motor proteins not actively involved in transporting cargoes should remain inactive at sites of cargo loading to save energy and remain available for loading. KIF1A/Unc104 is a monomeric kinesin known to dimerize into a processive motor at high protein concentrations. However, the molecular mechanisms underlying monomer stabilization and monomer-to-dimer transition are not well understood. Here, we report an intramolecular interaction in KIF1A between the forkhead-associated (FHA) domain and a coiled-coil domain (CC2) immediately following the FHA domain. Disrupting this interaction by point mutations in the FHA or CC2 domains leads to a dramatic accumulation of KIF1A in the periphery of living cultured neurons and an enhancement of the microtubule (MT) binding and self-multimerization of KIF1A. In addition, point mutations causing rigidity in the predicted flexible hinge disrupt the intramolecular FHA–CC2 interaction and increase MT binding and peripheral accumulation of KIF1A. These results suggest that the intramolecular FHA–CC2 interaction negatively regulates KIF1A activity by inhibiting MT binding and dimerization of KIF1A, and point to a novel role of the FHA domain in the regulation of kinesin motors
Antiviral Activity of Hederasaponin B from Hedera helix against Enterovirus 71 Subgenotypes C3 and C4a
Enterovirus 71 (EV71) is the predominant cause of hand, foot and mouth disease (HFMD). The antiviral activity of hederasaponin B from Hedera helix against EV71 subgenotypes C3 and C4a was evaluated in vero cells. In the current study, the antiviral activity of hederasaponin B against EV71 C3 and C4a was determined by cytopathic effect (CPE) reduction method and western blot assay. Our results demonstrated that hederasaponin B and 30% ethanol extract of Hedera helix containing hederasaponin B showed significant antiviral activity against EV71 subgenotypes C3 and C4a by reducing the formation of a visible CPE. Hederasaponin B also inhibited the viral VP2 protein expression, suggesting the inhibition of viral capsid protein synthesis. These results suggest that hederasaponin B and Hedera helix extract containing hederasaponin B can be novel drug candidates with broad-spectrum antiviral activity against various subgenotypes of EV71.Y