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Apoptosis of Lewis Lung Carcinoma Cells Induced by Microwave via p53 and Proapoptotic Proteins In vivo

Chinese Medical Journal 2017年第1期130卷 15-22页

作者： kou-dong zhang Lin-Rong Tong Shui-Ming Wang Rui-Yun Peng Hai-dong Huang Yu-Chao dong Xing-Xing zhang Qiang Li Chong Bai Department of Respiratory and Critical Care Medicine Changhai Hospital The Second Military Medical University Shanghai 200433 China Department of Respiratory Medicine Yancheng First People's Hospital Yancheng Jiangsu 224000 China Department of Respiratory Medicine Chenggong Hospital Xiamen University Xiamen Fujian 361000 China Institute of Radiation Medicine The Academy of Military Medical Sciences Beijing 100850 China

Background： Microwave therapy is a minimal invasive procedure and has been employed in clinical practice for the treatment of various types of cancers. However, its therapeutic application in non-small-cell lung cancer and the underlying mechanism remains to be investigated. This study aimed to investigate its effect on Lewis lung carcinoma （LLC） tumor in vivo. Methods： Fifty LLC tumor-bearing C57BL/6 mice were adopted to assess the effect of microwave radiation on the growth and apoptosis of LLC tumor in vivo. These mice were randomly assigned to 10 groups with 5 mice in each group. Five groups were treated by single pulse microwave at different doses for different time, and the other five groups were radiated by multiple-pulse treatment of a single dose. Apoptosis of cancer cells was determined by terminal deoxynucleotidyl transferase dUTP nick-end labeling assay. Western blotting was applied to detect the expression of proteins. Results： Single pulse of microwave radiation for 5 min had little effect on the mice. Only 15-min microwave radiation at 30 mW/cm2 significantly increased the mice body temperature （2.20 ± 0.82）℃ as compared with the other groups （0.78 ± 0.29 ℃, 1.24 ± 0.52 ℃, 0.78 ± 0.42 ℃, respectively）, but it did not affect the apoptosis of LLC tumor cells significantly. Continous microwave radiation exposure, single dose microwave radiation once per day for up to seven days, inhibited cell division and induced apoptosis of LLC tumor cells in a dose- and duration-dependent manner. It upregulated the protein levels of p53, Caspase 3, Bax and downregulated Bcl-2 protein. Conclusions： Multiple exposures of LLC-bearing mice to microwave radiation effectively induced tumor cell apoptosis at least partly by upregulating proapoptotic proteins and downregulating antiapoptotic proteins. Continuous radiation at low microwave intensity Ibr a short time per day is promising in treating non-small-cell lung cancer.

关键词： Apoptosis Lewis Lung Carcinoma Cells Microwave Radiation Non-small-cell Lung Cancer

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Heterogeneous data-driven aerodynamic modeling based on physical feature embedding

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Chinese Journal of Aeronautics 2024年第3期37卷 1-6页

作者： Weiwei zhang Xuhao PENG Jiaqing kou Xu WANG School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China Institute of Aerodynamics RWTH Aachen UniversityAachen 52062Germany

Aerodynamic surrogate modeling mostly relies only on integrated loads data obtained from simulation or experiment,while neglecting and wasting the valuable distributed physical information on the surface.To make full use of both integrated and distributed loads,a modeling paradigm,called the heterogeneous data-driven aerodynamic modeling,is presented.The essential concept is to incorporate the physical information of distributed loads as additional constraints within the end-to-end aerodynamic modeling.Towards heterogenous data,a novel and easily applicable physical feature embedding modeling framework is designed.This framework extracts lowdimensional physical features from pressure distribution and then effectively enhances the modeling of the integrated loads via feature embedding.The proposed framework can be coupled with multiple feature extraction methods,and the well-performed generalization capabilities over different airfoils are verified through a transonic case.Compared with traditional direct modeling,the proposed framework can reduce testing errors by almost 50%.Given the same prediction accuracy,it can save more than half of the training samples.Furthermore,the visualization analysis has revealed a significant correlation between the discovered low-dimensional physical features and the heterogeneous aerodynamic loads,which shows the interpretability and credibility of the superior performance offered by the proposed deep learning framework.

关键词： Transonic flow Data-driven modeling Feature embedding Heterogenous data Feature visualization

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Molecular Epidemiological Study of a Human Brucellosis Outbreak—Weihai City,Shandong Province,China,2022

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China CDC weekly 2024年第12期6卷 230-234页

作者： Yan Li Yifan Yu Jian Zhao Shujun Ding Guoying zhang Xiaolin Yu Zengqiang kou Shandong Provincial Center for Disease Control and Prevention Jinan CityShandong ProvinceChina Shandong First Medical University Shandong Academy of Medical SciencesJinan CityShandong ProvinceChina Weihai Municipal Center for Disease Control and Prevention Weihai CityShandong ProvinceChina

What is already known about this topic?Brucellosis,mainly caused by Brucella melitensis(B.melitensis),is regarded as a significant zoonotic disease in China.In Weihai,located at the eastern end of the Shandong Peninsula,brucellosis has been in a low epidemic phase for the past five years.What is added by this report?This was the initial report of a brucellosis outbreak in the last five years.Strains of B.melitensis bv.3 from Weihai and other cities showed a close genetic relationship,suggesting a potential common ancestry.What are the implications for public health practice?Epidemiological investigations depend on standardized and effective molecular typing methods and analysis tools for public health laboratories to identify and trace outbreaks.Understanding the circulation patterns of livestock in free-range households in heavily affected areas is essential for controlling the spread of brucellosis.

关键词： Shandong China. break

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Thin polymer electrolyte with MXene functional layer for uniform Li^(+) deposition in all-solid-state lithium battery

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Green Energy & Environment 2024年第1期9卷 71-80页

作者： Weijie kou Yafang zhang Wenjia Wu Zibiao Guo Quanxian Hua Jingtao Wang School of Chemical Engineering Zhengzhou UniversityZhengzhou450001China

Solid polymer electrolyte(SPE) shows great potential for all-solid-state batteries because of the inherent safety and flexibility;however, the unfavourable Li+deposition and large thickness hamper its development and application. Herein, a laminar MXene functional layer-thin SPE layer-cathode integration(MXene-PEO-LFP) is designed and fabricated. The MXene functional layer formed by stacking rigid MXene nanosheets imparts higher compressive strength relative to PEO electrolyte layer. And the abundant negatively-charged groups on MXene functional layer effectively repel anions and attract cations to adjust the charge distribution behavior at electrolyte–anode interface. Furthermore,the functional layer with rich lithiophilic groups and outstanding electronic conductivity results in low Li nucleation overpotential and nucleation energy barrier. In consequence, the cell assembled with MXene-PEO-LFP, where the PEO electrolyte layer is only 12 μm, much thinner than most solid electrolytes, exhibits uniform, dendrite-free Li+deposition and excellent cycling stability. High capacity(142.8 mAh g-1), stable operation of 140 cycles(capacity decay per cycle, 0.065%), and low polarization potential(0.5 C) are obtained in this Li|MXene-PEO-LFP cell,which is superior to most PEO-based electrolytes under identical condition. This integrated design may provide a strategy for the large-scale application of thin polymer electrolytes in all-solid-state battery.

关键词： MXene nanosheet Laminar functional layer Thin polymer electrolyte Dendrite-free Liþdeposition All-solid-state lithium battery

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Targeted therapeutic effects of oral magnetically driven pectin nanoparticles containing chlorogenic acid on colon cancer

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Particuology 2024年第1期84卷 53-59页

作者： Huatai Zhu Limei zhang Fujia kou Jingyang Zhao Jiandu Lei Jing He Beijing Key Laboratory of Lignocellulosic Chemistry Beijing Forestry UniversityBeijing100083China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen518055China

Oral colonic nano-drug delivery system has attracted growing attention in treating colon cancer for their excellent characteristics.However,the unique and complex structure of the gastrointestinal tract is still an obstacle to the safe delivery of drugs targeting sites in colon tumors.Here,we designed magnetically driven dual-targeted oral colonic nanoparticles loaded with chlorogenic acid using pectin and oleic acid-modified iron oxide(Fe3O4@OA).Specific degradation of pectin by pectinase produced by colonic flora and magnetic fields applied to the colon confers specific targeting of nanoparticles to the colon.In order to overcome the challenge of preparing magnetically driven nanoparticles with small and homogeneous particle sizes by a single conventional method,we developed the combined ultrasound-emulsification technique.The average particle size of the prepared nanoparticles was 81.04±1.02 nm,which showed good drug release in the simulated colonic environment.In vitro anticancer studies,the drug-loaded nanoparticles possess an obvious toxicity and apoptosis-inducing ability against cancer cells.Meanwhile,the hemolysis results demonstrated the safety of the nanoplatform(PET/CGA/Fe_(3)O_(4)@OA).This work holds broad prospects as a new treatment modality for colon cancer.

关键词： Pectin Chlorogenic acid Ultrasound-emulsion Magnetically driven Colon cancer Colon targeted

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Enhancing Dense Small Object Detection in UAV Images Based on Hybrid Transformer

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Computers, Materials & Continua 2024年第3期78卷 3993-4013页

作者： Changfeng Feng Chunping Wang dongdong zhang Renke kou Qiang Fu Shijiazhuang Campus People Liberation Army Engineering UniversityShijiazhuang050003China School of Information and Intelligent Engineering Sanya UniversitySanya572000China

Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.

关键词： UAV images transformer dense small object detection

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Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments

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The Innovation 2024年第1期5卷 127-138页

作者： Zhen zhang Chun Li Wenhui Wang Zheng dong Gongfa Liu Yuhui dong Yi zhang National Synchrotron Radiation Laboratory University of Science and Technology of ChinaHefei 230029China Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China

Synchrotron tomography experiments are transitioning into multifunctional,cross-scale,and dynamic characterizations,enabled by new-generation synchrotron light sources and fast developments in beamline instrumentation.However,with the spatial and temporal resolving power entering a new era,this transition generates vast amounts of data,which imposes a significant burden on the data processing end.Today,as a highly accurate and efficient data processing method,deep learning shows great potential to address the big data challenge being encountered at future synchrotron beamlines.In this review,we discuss recent advances employing deep learning at different stages of the synchrotron tomography data processing pipeline.We also highlight how applications in other data-intensive fields,such as medical imaging and electron tomography,can be migrated to synchrotron tomography.Finally,we provide our thoughts on possible challenges and opportunities as well as the outlook,envisioning selected deep learning methods,curated big models,and customized learning strategies,all through an intelligent scheduling solution.

关键词： processing pipeline outlook

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Synthesis and Modulation of Low-Dimensional Transition Metal Chalcogenide Materials via Atomic Substitution

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Nano-Micro Letters 2024年第9期16卷 49-94页

作者： Xuan Wang Akang Chen XinLei Wu Jiatao zhang Jichen dong Leining zhang Key Laboratory of Cluster Science Ministry of Education of ChinaBeijing Key Laboratory of Photoelectronic and Electrophonic Conversion MaterialsSchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081People’s Republic of China Beijing National Laboratory for Molecular Sciences Key Laboratory of Organic SolidsInstitute of Chemistry Chinese Academy of SciencesBeijing 100190People’s Republic of China

In recent years,low-dimensional transition metal chalcogenide(TMC)materials have garnered growing research attention due to their superior electronic,optical,and catalytic properties compared to their bulk counterparts.The controllable synthesis and manipulation of these materials are crucial for tailoring their properties and unlocking their full potential in various applications.In this context,the atomic substitution method has emerged as a favorable approach.It involves the replacement of specific atoms within TMC structures with other elements and possesses the capability to regulate the compositions finely,crystal structures,and inherent properties of the resulting materials.In this review,we present a comprehensive overview on various strategies of atomic substitution employed in the synthesis of zero-dimensional,one-dimensional and two-dimensional TMC materials.The effects of substituting elements,substitution ratios,and substitution positions on the structures and morphologies of resulting material are discussed.The enhanced electrocatalytic performance and photovoltaic properties of the obtained materials are also provided,emphasizing the role of atomic substitution in achieving these advancements.Finally,challenges and future prospects in the field of atomic substitution for fabricating low-dimensional TMC materials are summarized.

关键词： Transition metal chalcogenides Atomic substitution Ion exchange Low-dimensional materials Controllable synthesis

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Snap-through behaviors and nonlinear vibrations of a bistable composite laminated cantilever shell:an experimental and numerical study

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 779-794页

作者： Lele REN Wei zhang Ting dong Yufei zhang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Department of Mechanics Guangxi UniversityNanning 530004China Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Structures College of Mechanical EngineeringBeijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

The snap-through behaviors and nonlinear vibrations are investigated for a bistable composite laminated cantilever shell subjected to transversal foundation excitation based on experimental and theoretical approaches.An improved experimental specimen is designed in order to satisfy the cantilever support boundary condition,which is composed of an asymmetric region and a symmetric region.The symmetric region of the experimental specimen is entirely clamped,which is rigidly connected to an electromagnetic shaker,while the asymmetric region remains free of constraint.Different motion paths are realized for the bistable cantilever shell by changing the input signal levels of the electromagnetic shaker,and the displacement responses of the shell are collected by the laser displacement sensors.The numerical simulation is conducted based on the established theoretical model of the bistable composite laminated cantilever shell,and an off-axis three-dimensional dynamic snap-through domain is obtained.The numerical solutions are in good agreement with the experimental results.The nonlinear stiffness characteristics,dynamic snap-through domain,and chaos and bifurcation behaviors of the shell are quantitatively analyzed.Due to the asymmetry of the boundary condition and the shell,the upper stable-state of the shell exhibits an obvious soft spring stiffness characteristic,and the lower stable-state shows a linear stiffness characteristic of the shell.

关键词： bistable composite laminated cantilever shell snap-through behavior nonlinear vibration nonlinear stiffness characteristic chaos and bifurcation

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Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for Power Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3267-3282页

作者： Bin Li Linghui Kong Xiangyi zhang Bochuo kou Hui Yu Bowen Liu State Grid Beijing Urban District Power Supply Company Beijing100034China

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

关键词： Secure transmission deep learning power Internet of Things sensor-transmission-computing

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