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肝素对大鼠系膜细胞增殖和PAI-1表达的影响

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复旦学报（医学版） 2002年第4期29卷 247-250,254,F004页

作者：秦蓉张农陈广平刘琛郭慕依复旦大学医学院病理学教研室

目的　探讨肝素在体内和体外对大鼠系膜细胞增殖及Ⅰ型纤溶酶原激活物抑制因子 (plasminogenacti vatorinhibitortype1,PAI 1)表达的影响及可能的机制 ,从而为临床防治肾小球硬化提供一个新的思路。方法　(1)利用抗大鼠Thy 1单克隆抗... 详细信息

目的　探讨肝素在体内和体外对大鼠系膜细胞增殖及Ⅰ型纤溶酶原激活物抑制因子 (plasminogenacti vatorinhibitortype1,PAI 1)表达的影响及可能的机制 ,从而为临床防治肾小球硬化提供一个新的思路。方法　(1)利用抗大鼠Thy 1单克隆抗体建立大鼠Thy 1肾炎模型 ,并应用肝素对其进行治疗 ,分别于 1、3、7、14、2 1、2 8d处死动物并提取其肾组织总RNA ,应用半定量逆转录聚合酶链式反应 (RT PCR)观察对照组 (N组 )、肾炎组 (G组 )和肝素组 (H组 )肾皮质PAI 1mRNA的表达。按常规方法培养大鼠系膜细胞 ,应用RT PCR半定量法观察肝素对大鼠系膜细胞PAI 1mRNA表达的影响。结果　 (1)细胞计数显示 ,7至 2 1d ,G组肾小球细胞数较N组明显增生 (P <0 .0 1) ,H组肾小球细胞数较G组明显减少 (P <0 .0 5或P <0 .0 1)。RT PCR结果显示 ,G组7至 2 1dPAI 1mRNA的表达明显高于N组 (P <0 .0 5 ) ;H组 3至 2 8d时PAI 1的表达较G组明显降低 (P <0 .0 5 )。 (2 )体外研究结果表明 ,当肝素浓度范围为 3～ 6 0 0 μg/mL时 ,系膜细胞生长受到明显抑制 (P <0 .0 1) ,PAI 1mRNA表达也明显降低 (P <0 .0 5 ) ,并呈剂量依赖关系。结论　肝素可能通过抑制系膜细胞增生和抑制PAI

关键词：肝素大鼠系膜细胞增殖 I型纤溶酶原激活物抑制因子逆转录聚合酶链反应 Thy-1肾炎

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凝血酶联合生长抑素对上消化道出血患者血清炎性因子及凝血功能的影响

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世界华人消化杂志 2018年第5期26卷 343-348页

作者：姚泉福张晨广董国平浙江省湖州市吴兴区人民医院内科浙江省湖州市313008 浙江省平湖市公安局看守所医务室浙江省平湖市314200

目的探讨凝血酶联合生长抑素对上消化道出血患者血清炎性因子及凝血功能的影响.方法选择2015-07/2017-06收治的上消化道出血患者70例为研究对象,采用随机数字表法分为观察组和对照组各35例.在常规对照治疗的基础上,对照组同时给予奥曲... 详细信息

目的探讨凝血酶联合生长抑素对上消化道出血患者血清炎性因子及凝血功能的影响.方法选择2015-07/2017-06收治的上消化道出血患者70例为研究对象,采用随机数字表法分为观察组和对照组各35例.在常规对照治疗的基础上,对照组同时给予奥曲肽治疗,观察组给予凝血酶联合奥曲肽治疗.比较两组血清炎性炎子、凝血功能、临床疗效、不良反应等指标.结果观察组平均止血时间明显短于对照组(16.75 h±3.12 h vs 25.46 h±3.45 h,t=11.078,P<0.01);有效率明显高于对照组[94.29%(33/35)vs 77.14%(27/35),χ2=4.200,P<0.05];血清肿瘤坏死因子-α(tumor necrosis factorα,TNF-α)、白介素-6(interleukin-6)含量明显低于对照组,血清IL-2含量明显高于对照组[(5.32 ng/L±0.75 ng/L vs 8.02 ng/L±1.24 ng/L),(20.12 ng/L±3.45 ng/L vs 31.26 ng/L±4.12 ng/L),(6.75 ng/L±1.02 ng/L vs 4.68 ng/L±0.76 ng/L)](t=11.022,12.264,10.349,P<0.01);血清凝血酶原时间、部分凝血活酶时间明显低于对照组血小板、纤维蛋白原明显高于对照组[(13.32 s±2.2 s vs 16.84 s±3.24 s),(33.12 s±4.56 s vs 40.18 s±5.35 s),(67.82× 10~9/L±8.36× 10~9/L vs 58.75× 10~9/L±6.82× 10~9/L),(315.45 g/L±45.24 g/L vs 284.72 g/L±40.15)g/L](t=5.249、5.942、4.973、3.006,P<0.05).结论凝血酶联合生长抑素治疗有助于缩短止血时间,提高临床疗效,可能与抑制患者炎症症状、改善凝血功能等因素有关.

关键词：上消化道出血凝血酶生长抑素炎性因子凝血功能

Research on the deformation mechanism of flexural toppling deep-seated landslides based on large centrifuge physical model testing: A case study of the Genie landslide in the Tibetan Plateau

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Journal of Earth Science 2025年

作者： Shichao Cao Xiujun Dong Changbao guo Ruian Wu Zhihua Yang guang Zheng Xiaoqiang Zhu State Key Laboratory of Geohazard Prevention and Geoenvironment Protection， Chengdu University of Technology Institute of Geomechanics， Chinese Academy of Geological Sciences Key Laboratory of Active Tectonics and Geological Safety， Ministry of Natural Resources

Flexural toppling is a widespread failure mode in natural and excavated anti-inclined rock slopes of the eastern Tibetan Plateau， which can further evolve into large deep-seated landslides， posing significant threats to the construction and operation of important infrastructure. In this study， we took the large deep-seated Genie landslide as a case study and established a centrifuge physical model to analyze the deformation mechanism and evolutionary process of flexural toppling deep-seated landslides under the effect of gravity. The results indicate that the geomechanical mode of landslide instability is characterized by flexural toppling-shearing-sliding， with the deformation process could be divided into three stages: initial slow deformation stage marked by crack generation， rapid deformation stage characterized by the expansion and fracturing of cracks， and a low-speed deformation stage characterized by creep. Notably， the sliding surfaces do not adhere strictly to predefined bending zones but develop cracks along the bending parts， which gradually expand and penetrate deeper， eventually forming multiple potential sliding surfaces. The analysis of the entire process deformation evolution of flexural toppling deep-seated landslides suggests that the rapid deformation stage is the optimal time to take action for landslide prevention and control. The study demonstrates that the shear strength also plays a key factor in the evolution of flexural toppling. The research reveals the deformation mechanism and evolutionary process of large deep-seated landslides in deep-cut canyon areas， providing valuable reference for the prediction， assessment， and prevention of such slopes and landslides.

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DCN基因转染对大鼠肾系膜细胞生长及表型改变的影响

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复旦学报（医学版） 2003年第5期30卷 414-417页

作者：王慧君张志刚刘学光陈广平陈琦郭慕依复旦大学上海医学院病理学系上海200032

目的　通过观察转染DCN基因的大鼠系膜细胞 (MsC)生长及其一些表型的改变 ,为其用作细胞载体回输入大鼠肾病模型体内进行基因治疗奠定实验基础。方法　采用MTT比色法和流式细胞仪技术 ,检测该MsC株生长情况 ;Northernblot和Westernblot... 详细信息

目的　通过观察转染DCN基因的大鼠系膜细胞 (MsC)生长及其一些表型的改变 ,为其用作细胞载体回输入大鼠肾病模型体内进行基因治疗奠定实验基础。方法　采用MTT比色法和流式细胞仪技术 ,检测该MsC株生长情况 ;Northernblot和Westernblot法检测其TGF β1mRNA、ColⅣmRNA和TGF β1蛋白表达水平 ;半定量RT PCR法检测其TIMP 2mRNA表达的改变。结果　与未转染MsC相比 ,转染DCN基因的MsC株的生长受到明显抑制 (5d时P <0 .0 5 ,6d时P <0 .0 1) ;G0 /G1期比例增加 ,S期比例降低 ,提示其生长缓慢 ;TGF β1和ColⅣmRNA表达明显降低 ,TGF β1蛋白分泌减少 ;TIMP 2mRNA表达明显下调。结论　转染DCN基因的MsC可被用作载体开展对大鼠系膜增生性肾炎的实验治疗。

关键词： DCN基因转染大鼠肾系膜细胞基因治疗基因表型 MTT比色法流式细胞仪技术系膜增生性肾炎

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Reducing the measurement errors in nonadiabatic holonomic quantum computers

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 64-70页

作者： guo-Fu Xu Department of Physics Shandong University

Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum *** quantum computation has entered the noisy intermediate-scale era, building accurate intermediate-scale nonadiabatic holonomic quantum computers is clearly necessary. Given that measurements are the sole means of extracting information, they play an indispensable role in nonadiabatic holonomic quantum computers. Accordingly, developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance. However, while much attention has been given to the research on nonadiabatic holonomic gates, the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking. In this study, we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers. The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates. Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.

关键词： quantum holonomy quantum computation measurement errors

Perovskite LiBaH3 for photo-assisted dinitrogen fixation

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Science China Chemistry 2025年

作者： Kaixun Cui Yeqin Guan Yongli Cai Runze Wang Qianru Wang Wenbo Gao Jianping guo ping Chen Department of Chemical Physics University of Science and Technology of China Dalian Institute of Chemical Physics Chinese Academy of Sciences Center of Materials and Optoelectronics Engineering University of Chinese Academy of Sciences

Establishing supply chains for future ammonia energy systems requires the development of efficient materials and processes for ammonia production under mild conditions. Recent researches disclose unique functionalities of binary alkali and alkaline earth metal hydrides in mediating ammonia synthesis. Thanks to the rich compositional and structural properties of the metalhydrogen system, we herein report that LiBaH3, as a narrow band gap perovskite hydride, exhibits a strong response to visible light illumination. Specifically, hydridic hydrogen undergoes reductive elimination of producing H2and creates an electron-rich surface. Such an environment favors dinitrogen fixation to form N–H bonds. Based on this chemical property, a chemical looping ammonia synthesis process mediated by LiBaH3and driven by both photo and thermal energies was proposed and *** work demonstrates that hydride perovskites are promising candidates for mediating photo-assisted nitrogen fixation reactions.

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Anomaly Detection of Controllable Electric Vehicles through Node Equation against Aggregation Attack

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Computers, Materials & Continua 2025年第1期82卷 427-442页

作者： Jing guo Ziying Wang Yajuan guo Haitao Jiang State Grid Jiangsu Electric Power Co. Ltd.Research InstituteState Grid Corporation of ChinaNanjing211100China

The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids *** study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation *** approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation *** employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter *** xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging *** results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging ***,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 *** research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.

关键词： Anomaly detection electric vehicle aggregation attack deep cross-network

Insight into the particle shape on the impact of dry granular flow against a rigid barrier: A DEM study

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Journal of Earth Science 2025年

作者： Rui-Xiao Zhan Dong Su Xiang-Sheng Chen Yuan-Jun Jiang guo-ping Lei Jing-Jing Yu Key Laboratory for Resilient Infrastructures of Coastal Cities (MOE)， Shenzhen University College of Civil and Transportation Engineering， Shenzhen University School of Architecture and Urban Planning， Shenzhen University Shenzhen Key Laboratory of Green， Efficient and Intelligent Construction of Underground Metro Station， Shenzhen University Institute of Mountain Hazards and Environment， Chinese Academy of Sciences School of Transportation， Civil Engineering & Architecture， Foshan University

The effect of particle shape on the impact of dry granular flow remains an open area for further investigation. Five distinct particle shapes were examined in this study using discrete element simulations after calibrating the numerical model using a published work. The findings indicated that the particle shape had a significant influence on granular mobility. With negligible variations in normalized kinetic energy between particles of different shapes， the effect of particle shape on the increasing rate of kinetic energy became more obvious. All irregular particle scenarios had longer accumulated particle lengths down the channel than spherical particles. Variations in particle shape led to adjustments in the distribution of impact forces on the barrier. These findings substantially enhance our understanding of the distinctive effects of particle shapes on the impact mechanism of dry granular flow.

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DIGNN-A:Real-Time Network Intrusion Detection with Integrated Neural Networks Based on Dynamic Graph

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Computers, Materials & Continua 2025年第1期82卷 817-842页

作者： Jizhao Liu Minghao guo College of Computer Zhongyuan University of TechnologyZhengzhou450007China

The increasing popularity of the Internet and the widespread use of information technology have led to a rise in the number and sophistication of network attacks and security *** detection systems are crucial to network security,playing a pivotal role in safeguarding networks from potential ***,in the context of an evolving landscape of sophisticated and elusive attacks,existing intrusion detection methodologies often overlook critical aspects such as changes in network topology over time and interactions between *** address these issues,this paper proposes a real-time network intrusion detection method based on graph neural *** proposedmethod leverages the advantages of graph neural networks and employs a straightforward graph construction method to represent network traffic as dynamic graph-structured ***,a graph convolution operation with a multi-head attention mechanism is utilized to enhance the model’s ability to capture the intricate relationships within the graph structure ***,it uses an integrated graph neural network to address dynamic graphs’structural and topological changes at different time points and the challenges of edge embedding in intrusion detection *** edge classification problem is effectively transformed into node classification by employing a line graph data representation,which facilitates fine-grained intrusion detection tasks on dynamic graph node feature *** efficacy of the proposed method is evaluated using two commonly used intrusion detection datasets,UNSW-NB15 and NF-ToN-IoT-v2,and results are compared with previous studies in this *** experimental results demonstrate that our proposed method achieves 99.3%and 99.96%accuracy on the two datasets,respectively,and outperforms the benchmark model in several evaluation metrics.

关键词： Intrusion detection graph neural networks attention mechanisms line graphs dynamic graph neural networks