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| 1 | Chondroitin sulfate proteoglycan 4 functions as the cellular receptor for Clostridium difficile toxin B显示文摘作为克积极的、形成孢子的厌氧的杆菌, Clostridium 顽固(C。顽固) 为严重、致命的 pseudomembranous 大肠炎负责,并且形成世界范围的最迫切的抗菌素抵抗威胁。流行 C。顽固全球性是联系抗菌素的腹泻的领先的原因,特别由于 hypervirulent 的出现,种类与高死亡和病态联系了的腹泻。TcdB,关键毒力因素之一由这个细菌藏匿了,通过糟糕理解的机制进入主人房间得到它的病原的效果。这里,我们报导 TcdB 细胞的受体的第一鉴定, chondroitin 硫酸盐 proteoglycan 4 (CSPG4 ) 。CSPG4 开始从屏蔽的一个整个染色体的人的 shRNAmir 图书馆被孤立,并且它的角色被证实由调停 TALEN 并且在人的房间的 CRISPR/Cas9-mediated 基因大美人。CSPG4 为对房间表面有约束力的 TcdB 是批评的,导致细胞骨架混乱和房间死亡。在 CSPG4 的 N 终点和 TcdB 的 C 终点之间的一个直接相互作用被证实,并且 CSPG4 的毒素绑定领域的可溶的肽能保护房间免受 TcdB 的行动的伤害。尤其是, CSPG4/NG2 的完全的损失减少了在没有显著地影响动物死亡的老鼠的被触发 TcdB 的 interleukin-8 正式就职。基于两个在里面 vitro 并且在 vivo 研究,我们为 TcdB endocytosis 建议一个双受体的模型。第一 TcdB 受体的发现为 CSPG4 揭示一个以前不受怀疑的角色并且为 C 的处理提供一个新治疗学的目标。顽固感染。 | Pengfei Yuan Hongmin Zhang Changzu Cai Shiyou Zhu Yuexin Zhou Xiaozhou Yang Ruina He Chan Li Shengjie Guo Shan Li Tuxiong Huang Gregorio Perez-Cordon Hanping Feng Wensheng Wei | 2015 | Cell Research2015，25，2： | 6 |
| 2 | Nondestructive diagnostics of soluble sugar,total nitrogen and their ratio of tomato leaves in greenhouse by polarized spectra-hyperspectral data fusion显示文摘Polarized spectra-hyperspectral data fusion technique was used to estimate the soluble sugar(SS),total nitrogen(N),and their ratio(SS/N),of greenhouse tomato leaves.Fresh tomato leaves of five different growth stages(seedling,flowering,initial fruiting,mid-fruiting and picking stage)and five different nitrogen treatments(severe stress 25%,moderate stress 50%,mild stress 75%,normal 100%,and excess 150%)at every stage were collected for spectra acquisition and SS and N determination.Polarized reflectance spectra were acquired with a polarization reflectance spectrum spectro-goniophotometer system and four polarization degree features were extracted.Hyperspectral data were collected with a hyperspectral imaging system and four reflectance spectrum features and eight image features were extracted.Initially,models were built with polarization degree features,image features,and spectral features respectively.Linear and nonlinear fusion methods were comparatively used for modeling based on normalized data of the three sources.The results suggest that the performances of SS/N models are better than those of N and SS models,and the prediction capability of the Support Vector Machine(SVM)models of N and SS/N are superior to those obtained with single kind feature.This work indicates that the polarized spectrum-hyperspectral multidimensional information detecting method can feasibly judge the tomato nutrient stress conditions.Multi-features data fusion analysis technique can enhance the prediction accuracy of spectral diagnostics technology in precision agriculture. | Wenjing Zhu Jinyang Li Lin Li Aichen Wang Xinhua Wei Hanping Mao | 2020 | International Journal of Agricultural and Biological Engineering2020，13，2： | 5 |
| 3 | A method of improving the properties of digital chaotic system 显示文摘 | Hu Hanping Xu Ya Zhu Ziqi | 2008 | Chaos Solitons and Fractals2008，38，43： | 1 |
| 4 | Model for thermoacoustic emission from solids显示文摘 | Hu Hanping Zhu Tao Xu Jun | 2010 | Appl Phys Lett2010，96，21： | 1 |
| 5 | Application of the Singularity-Separating Method to American Exotic Option Pricing显示文摘 | You-lan Zhu Bin-mu Chen Hongliang Ren Hanping Xu | 2003 | Advances in Computational Mathematics (-)2003，，1： | 1 |
| 6 | 植物生长调节剂通过克隆整合对空心莲子草顶端和基部生长的不同作用显示文摘入侵植物不仅对全球生物多样性造成了巨大的威胁,同时也严重影响了农业生产与粮食安全。克隆整合使得相连植株进行资源共享,能促进入侵植物的生长从而获得优势。然而,入侵杂草在植物调节剂(plant growth regulators,PGRs)影响下的克隆整合作用则很少有报道。PGRs被广泛应用于农作物生产上,并能通过土壤淋溶、侵蚀和径流作用,影响分布在作物附近的农田杂草的生长。本研究采用两种PGRs赤霉素(gibberellins,GA)和多效唑(paclobutrazol,PAC)处理恶性入侵杂草空心莲子草(Alternanthera philoxeroides)基端,并保持或者通过剪切达到控制基端与顶端的连通,从而探究克隆整合作用在空心莲子草响应两种农业常用PGRs中的作用。研究结果表明,GA和PAC对空心莲子草生长的作用相反。GA通过克隆整合作用显著促进顶端植株的地上生长。相反地,PAC显著抑制基端和顶端的地上生长,但是能够通过克隆整合作用显著促进基端和顶端的地下生长。这些研究结果解释了克隆整合作用能促进PGRs对空心莲子草生长的促进作用,这很可能是外来杂草能够成功入侵人为干扰较多的农业生态系统的重要原因之一。 | Shanshan Qi Susan Rutherford Furong He Bi-Cheng Dong Bin Zhu Zhicong Dai Weiguo Fu Hanping Mao Daolin Du | 2022 | Journal of Plant Ecology2022，15，3： | 0 |
| 7 | Isolation and Growth Characteristics of SARS-CoV-2 in Vero Cell显示文摘Dear Editors,The coronavirus disease 2019(COVID-19),caused by SARS-CoV-2,broke out in early December 2019 has escalated into a global pandemic(Lai et al.2020).Till the May 20 th 2020,more than 4,700,000 people were infected and the number is still increasing especially in Europe,North America and Asia(http://gffzze7c39cdc9e894ca6suu6kvpckqcqx6b6k.ffgz.tsg.suse.edu.cn/). | Pingping Yao Yachun Zhang Yisheng Sun Yulin Gu Fang Xu Bo Su Chen Chen Hangjing Lu Dehui Wang Zhangnv Yang Biao Niu Jiancai Chen Lixia Xie Lei Chen Yajing Zhang Hui Wang Yuying Zhao Yue Guo Juncheng Ruan Zhiyong Zhu Zhenfang Fu Dayong Tian Qi An Jianmin Jiang Hanping Zhu | 2020 | Virologica Sinica2020，35，3： | 0 |
| 8 | An evolving trajectory-from PD,logistics,SCM to the theory of material flow显示文摘The growing interest in the material flow(MF)theory has invoked much interesting research in recent years.Although the MF theory is relatively new,a review of the related literature from a historical perspective shows that MF theory represents a new stage of the evolutionary development of interrelated subjects such as Physical Distribution(PD),Logistics,and Supply Chain Management(SCM).The purpose of this paper is to provide a summative review of the evolution of the subjects of PD,Logistics,and SCM,and their new development,MF theory.The paper aims at tracing how concepts and findings in PD,Logistics,SCM,and MF have been developed and have evolved.The study shows that PD evolved to Logistics in middle of the 1980s;starting from the late 1990s,Logistics has evolved to SCM;and today PD,Logistics,and SCM can be considered to be under the umbrella provided by a new theory called MF theory.This paper points out that MF theory is a necessity to deal with the overwhelming complexity of material flow systems in the global economy of the twenty-first century. | Hanping Hou Mikhail Yu Kataev Zuopeng(Justin)Zhang Sohail Chaudhry Huiqi Zhu Liuliu Fu Mingli Yu | 2015 | Journal of Management Analytics2015，2，2： | 0 |
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