A preparation strategy for protein-oriented immobilized silica magnetic beads with Spy chemistry for ligand fishing

Due to the complexity of bioactive ingredients in biological samples,the screening of target proteins is a complex process.Herein,a feasible strategy for directing protein immobilization on silica magnetic beads for ligand fishing based on SpyTag/SpyCatcher(ST/SC)-mediated anchoring is presented.Carboxyl functional groups on the surface of silica-coated magnetic beads(SMBs)were coupled with SC using the 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysulfosuccinimide method,named SC-SMBs.The green fluorescent protein(GFP),as the capturing protein model,was ST-labeled and anchored at a specific orientation onto the surface of SC-SMBs directly from relevant cell lysates via ST/SC self-ligation.The characteristics of the SC-SMBs were studied via electron microscopy,energy dispersive spectroscopy,and Fourier transform infrared spectroscopy.The spontaneity and site-specificity of this unique reaction were confirmed via electrophoresis and fluorescence analyses.Although the alkaline stability of ST-GFP-ligated SC-SMBs was not ideal,the formed isopeptide bond was unbreakable under acidic conditions(0.05 M glycine-HCl buffer,pH 1e6)for 2 h,under 20%ethanol solution within 7 days,and at most temperatures.We,therefore,present a simple and universal strategy for the preparation of diverse protein-functionalized SMBs for ligand fishing,prompting its usage on drug screening and target finding.

乙型肝炎病毒与细胞相互作用的研究进展

乙型肝炎病毒(HBV)是一种类反转录(retroid)病毒,其DNA基因组短小,编码能力有限;但HBV却能成功地在不同宿主个体中繁殖,并在人群中广泛传播。本文着重对HBV与宿主细胞关系的研究进展进行综述,以利于阐明HBV复制及其在宿主细胞内持续存在的特性。这些内容主要来自于本实验室的研究。文中讨论的HBV与宿主之间的相互作用主要包括:细胞伴侣分子在HBV反转录起始和核衣壳组装中的作用,宿主通过调控核衣壳磷酸化对病毒衣壳成熟的调节以及与HBV持续存在相关的核内附加体(episomal)病毒DNA的形成。

CAV driving safety monitoring and warning via V2X-based edge computing system

Driving safety and accident prevention are attracting increasing global interest.Current safety monitoring systems often face challenges such as limited spatiotemporal coverage and accuracy,leading to delays in alerting drivers about potential hazards.This study explores the use of edge computing for monitoring vehicle motion and issuing accident warnings,such as lane departures and vehicle collisions.Unlike traditional systems that depend on data from single vehicles,the cooperative vehicle-infrastructure system collects data directly from connected and automated vehicles(CAVs)via vehicle-to-everything communication.This approach facilitates a comprehensive assessment of each vehicle’s risk.We propose algorithms and specific data structures for evaluating accident risks associated with different CAVs.Furthermore,we examine the prerequisites for data accuracy and transmission delay to enhance the safety of CAV driving.The efficacy of this framework is validated through both simulated and real-world road tests,proving its utility in diverse driving conditions.

Reliability Evaluation of IEEE 802.11p-Based Vehicle-to-Vehicle Communication in an Urban Expressway

IEEE 802.11p/DSRC （Dedicated Short Range Communication） is considered to be a promising wireless communication standard for enhancing transportation safety and efficiency. However, IEEE 802.11p-based Vehicle- to-Vehicle （V2V） communication is still unreliable because of the complicating factors of high vehicle speed and complex radio environments. In this paper, we performed a data-based evaluation of V2V communication reliability, using real-world measurements in a typical urban expressway in Beijing. With respect to the characteristics of the urban expressway and our experimental data, we found road slope and traffic density to be the major environmental factors having a significant impact on the V2V communication＇s Line-Of-Sight （LOS） conditions. On the basis of these two factors, we propose a fuzzy classification method for the LOS conditions, and separate the real- time communication environments into different LOS cases. For each LOS case, we quantify the metrics as received signal strength indication, packet delivery rate, and communication latency. The results reveal that the communication reliability in urban expressways is very unstable because of the changing LOS conditions. This study provides a useful reference for the IEEE 802.11 p-based cooperative systems in urban expressways.

Optimal Combinations and Variable Departure Intervals for Micro Bus System

It is becoming increasingly difficult for Chinese citizens to access traditional public transport because of overcrowded community structures. Therefore, novel ideas are required to improve the transport system. In this respect, this study considers the design of a public transport scheduling model for a micro system. The model aims to minimize passenger waiting time and maximize number of passengers one bus carries, by simultaneously optimizing departure intervals and use of traditional and rapid buses. The model is superior to traditional models, as it analyzes the phenomena of vehicle overtaking, vehicle capacity limit, and passenger determination uncertainty. In addition, the model is a sophisticated nonlinear multi-objective optimization problem and contains more than one type of decision variable, therefore two composite algorithms, HPSO and GAPSO, are proposed, which are improvements of the Genetic Algorithm （GA） and Particle Swarm Optimization （PSO）. These two algorithms are compared to the classical GA with respect to stability and effect, and the results show them to be strong in both respects. In addition, the simultaneous optimization method has evident advantages compared to single-method optimizations.

A Generalized Comfort Function of Subway Systems Based on a Nested Logit Model

With rapid urbanization,subway systems are widely acknowledged as one of the best solutions to urban transportation problems.The operators or managers of subway systems should pay more attention to passenger＇s perceptions of service quality to maintain its competitive position.Taking the traffic state,efficiency,and environmental impact into consideration,the concept of generalized comfort is proposed in this paper.Based on a nested logit model,the selection probability for each factor in a generalized comfort function can be estimated using a nested structure.A certain factor is considered to be more significant in a generalized comfort function than others,when the corresponding probability of this factor is higher in value.Using stated preference and revealed preference data about passenger travel behavior obtained from the Beijing subway,the parameters of generalized comfort function are estimated by maximum likelihood techniques.