Sites of Alcohol Action at the GluN1/GluN2B NMDA Receptor M3-M4 Domain Intersubunit Interfaces

The N-methyl-D-aspartate (NMDA) receptor has been shown to be one of the most important target sites of alcohol in the central nervous system. We and others have identified positions in the third and fourth membrane-associated (M) domains of both GluN1 and GluN2A subunits that influence alcohol sensitivity. In the structural model of the NMDA receptor based upon the related GluA2 receptor, the outward face of the M3 domain of one subunit type is oriented toward the M4 domain of the other subunit type. We recently reported that four pairs of alcoholsensitive amino acid positions in GluN1/GluN2A NMDA receptors interact at the M3-M4 intersubunit interfaces with respect to alcohol sensitivity and receptor kinetics. Because a number of studies point to a major role for the GluN2B subunit in the action of alcohol in the brain, in the present study we used site-directed mutagenesis and electrophysiological patch-clamp recording in transfected cells to investigate the sensitivity of cognate positions in the GluN2B subunit, as well as interactions between positions in the M3 and M4 domains of the GluN1 and GluN2B subunits affecting ethanol inhibition. Although the M3 and M4 domains of GluN2A and GluN2B are highly conserved, only one of four positions in GluN2B, F637, corresponding to alcoholsensitive positions in GluN2A exhibited altered ethanol IC50 values in substitution mutants. However, we observed interactions with respect to ethanol sensitivity among three out of four pairs of positions (G638/M824, F639/L825, and M818/F637 in GluN1/GluN2B), even when single substitution mutations at one of the two positions in a pair (GluN1 M818; GluN2B M824, L825) had no effect on alcohol sensitivity. These results support the existence of sites of alcohol action formed by clusters of positions at the M3-M4 domain intersubunit interfaces of GluN1/GluN2B NMDA receptors, although they appear to differ from the corresponding sites in GluN1/GluN2A receptors reported previously

Clustering Optimized Portrait Matting Algorithm Based on Improved Sparrow Algorithm

As a result of the influence of individual appearance and lighting conditions, aberrant noise spots cause significant mis-segmentation for frontal portraits. This paper presents an accurate portrait segmentation approach based on a combination of wavelet proportional shrinkage and an upgraded sparrow search (SSA) clustering algorithm to solve the accuracy challenge of segmentation for frontal portraits. The brightness component of the human portrait in HSV space is first subjected to wavelet scaling denoising. The elite inverse learning approach and adaptive weighting factor are then implemented to optimize the initial center location of the K-Means algorithm to improve the initial distribution and accelerate the convergence speed of SSA population members. The pixel segmentation accuracy of the proposed method is approximately 70% and 15% higher than two comparable traditional methods, while the similarity of color image features is approximately 10% higher. Experiments show that the proposed method has achieved a high level of accuracy in capricious lighting conditions

SOAR: Scene-debiasing Open-set Action Recognition

Deep learning models have a risk of utilizing spurious clues to make predictions, such as recognizing actions based on the background scene. This issue can severely degrade the open-set action recognition performance when the testing samples have different scene distributions from the training samples. To mitigate this problem, we propose a novel method, called Scene-debiasing Open-set Action Recognition (SOAR), which features an adversarial scene reconstruction module and an adaptive adversarial scene classification module. The former prevents the decoder from reconstructing the video background given video features, and thus helps reduce the background information in feature learning. The latter aims to confuse scene type classification given video features, with a specific emphasis on the action foreground, and helps to learn scene-invariant information. In addition, we design an experiment to quantify the scene bias. The results indicate that the current open-set action recognizers are biased toward the scene, and our proposed SOAR method better mitigates such bias. Furthermore, our extensive experiments demonstrate that our method outperforms state-of-the-art methods, and the ablation studies confirm the effectiveness of our proposed modules.Comment: Accepted to ICCV 2023, code:https://github.com/yhZhai/SOA

Supramolecular Self-Assembly to Control Structural and Biological Properties of Multicomponent Hydrogels

Self-assembled nanofibers are ubiquitous in nature and serve as inspiration for the design of supramolecular hydrogels. A multicomponent approach offers the possibility of enhancing tunability and functionality of this class of materials. We report on the synergistic multicomponent self-assembly involving a peptide amphiphile (PA) and a 1,3:2,4-dibenzylidene-D-sorbitol (DBS) gelator to generate hydrogels with tunable nanoscale morphology, improved stiffness, enhanced self-healing, and stability to enzymatic degradation. Using induced circular dichroism of Thioflavin T (ThT), electron microscopy, small-angle neutron scattering (SANS), and molecular dynamics approaches we confirm that the PA undergoes self-sorting while the DBS-gelator acts as an additive modifier for the PA nanofibers. The supramolecular interactions between the PA and DBS gelators result in improved bulk properties and cytocompatibility of the two-component hydrogels as compared to the single component systems. The tunable mechanical properties, self-healing ability, resistance to proteolysis, and biocompatibility of the hydrogels suggest future opportunities for the hydrogels as scaffolds for tissue engineering and drug delivery vehicles

Simulation analysis on seismic dynamic response of pile supported tunnels in deep backfill area of soil-rock mixture

To reveal the seismic dynamic response of the pile-supported tunnel group in the soil-rock mixture deep backfill region, a three-dimensional finite element model was established based on the engineering conditions of the subway section and three tunnels with close access lines. Subsequently, the seismic dynamic response of the tunnel lining structure was studied. The results show that: Under the action of seismic, the soil-rock mixture stratum presents nonlinear characteristics with shear failure and plastic deformation. In addition, the acceleration and earth pressure of the soil-rock mixture stratum is in a “saturated” state; The seismic dynamic response of the three tunnels influences each other. The bending moments in the X and Y directions of the tunnel lining cross-section are distributed in “X” and inverted “V” shapes, respectively. Meanwhile, the tensile stress and shear stress are distributed in an “X” shape; Under the action of seismic, the main failure form of tunnel lining is tension shear failure, and the most vulnerable position is the left and right arch foot, followed by the left and right arch shoulder; The bending moment of the pile body changes nonlinearly in the height direction. The most significant bending moment value appears at the top 1/5 of the pile length and the junction of different strata. Furthermore, the most significant horizontal displacement of the lining structure occurs at the tunnel vault

Named Data Networking based File Access for XRootD

We present the design and implementation of a Named Data Networking (NDN) based Open Storage System plug-in for XRootD. This is an important step towards integrating NDN, a leading future internet architecture, with the existing data management systems in CMS. This work outlines the first results of data transfer tests using internal as well as external 100 Gbps testbeds, and compares the NDN-based implementation with existing solutions

Rational design of hydrogels for immunomodulation

The immune system protects organisms against endogenous and exogenous harm and plays a key role in tissue development, repair and regeneration. Traditional immunomodulatory biologics exhibit limitations including degradation by enzymes, short half-life and lack of targeting ability. Encapsulating or binding these biologics within biomaterials is an effective way to address these problems. Hydrogels are promising immunomodulatory materials because of their prominent biocompatibility, tuneability and versatility. However, to take advantage of these opportunities and optimize material performance, it is important to more specifically elucidate, and leverage on, how hydrogels affect and control the immune response. Here, we summarize how key physical and chemical properties of hydrogels affect the immune response. We first provide an overview of underlying steps of the host immune response upon exposure to biomaterials. Then, we discuss recent advances in immunomodulatory strategies where hydrogels play a key role through (i) physical properties including dimensionality, stiffness, porosity and topography; (ii) chemical properties including wettability, electric property and molecular presentation;and (iii) the delivery of bioactive molecules via chemical or physical cues. Thus, this review aims to build a conceptual and practical toolkit for the design of immune-instructive hydrogels capable of modulating the host immune response

Covalent co-assembly between resilin-like polypeptide and peptide amphiphile into hydrogels with controlled nanostructure and improved mechanical properties

Covalent co-assembly holds great promise for the fabrication of hydrogels with controllable nanostructure, versatile chemical composition, and enhanced mechanical properties given its relative simplicity, high efficiency, and bond stability. This report describes our approach to designing functional multicomponent hydrogels based on photo-induced chemical interactions between an acrylamide-functionalized resilin-like polypeptide (RLP) and a peptide amphiphile (PA). Circular dichroism (CD) spectroscopy, electron microscopy, and amplitude sweep rheology were used to demonstrate that the co-assembled hydrogel systems acquired distinct structural conformations, tunable nanostructures, and enhanced elasticity in a PA concentration-dependent manner. We envisage the use of these materials in numerous biomedical applications such as controlled drug release systems, microfluidic devices, and scaffolds for tissue engineering

In-Orbit Instrument Performance Study and Calibration for POLAR Polarization Measurements

POLAR is a compact space-borne detector designed to perform reliable measurements of the polarization for transient sources like Gamma-Ray Bursts in the energy range 50-500keV. The instrument works based on the Compton Scattering principle with the plastic scintillators as the main detection material along with the multi-anode photomultiplier tube. POLAR has been launched successfully onboard the Chinese space laboratory TG-2 on 15th September, 2016. In order to reliably reconstruct the polarization information a highly detailed understanding of the instrument is required for both data analysis and Monte Carlo studies. For this purpose a full study of the in-orbit performance was performed in order to obtain the instrument calibration parameters such as noise, pedestal, gain nonlinearity of the electronics, threshold, crosstalk and gain, as well as the effect of temperature on the above parameters. Furthermore the relationship between gain and high voltage of the multi-anode photomultiplier tube has been studied and the errors on all measurement values are presented. Finally the typical systematic error on polarization measurements of Gamma-Ray Bursts due to the measurement error of the calibration parameters are estimated using Monte Carlo simulations.Comment: 43 pages, 30 figures, 1 table; Preprint accepted by NIM