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Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment

World Journal of Diabetes 2024年第4期15卷 735-757页

作者： jing gao Ying Zou Xiao-Yu Lv Li Chen Xin-Guo Hou Department of Endocrinology Qilu Hospital of Shandong UniversityCheeloo College of MedicineShandong UniversityJinan 250012Shandong ProvinceChina Institute of Endocrine and Metabolic Diseases Shandong UniversityJinan 250012Shandong ProvinceChina Key Laboratory of Endocrine and Metabolic Diseases Shandong Province Medicine&HealthJinan 250012Shandong ProvinceChina Department of Endocrinology Jinan Clinical Research Center for Endocrine and Metabolic DiseaseJinan 250012Shandong ProvinceChina

BACKGROUND The cognitive impairment in type 2 diabetes mellitus(T2DM)is a multifaceted and advancing state that requires further exploration to fully comprehend.Neu-roinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.METHODS To identify differentially expressed genes(DEGs)between T2DM and controls,we used data from the Gene Expression Omnibus database GSE125387.To identify T2DM module genes,we used Weighted Gene Co-Expression Network Analysis.All the genes were subject to Gene Set Enrichment Analysis.Protein-protein interaction network construction and machine learning were utilized to identify three hub genes.Immune cell infiltration analysis was performed.The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis.Validation experiments including reverse transcription quantitative real-time PCR,Western blotting and immunohistochemistry were conducted both in vivo and in vitro.To identify potential drugs associated with hub genes,we used the Comparative Toxicogenomics Database(CTD).RESULTS A total of 576 DEGs were identified using GSE125387.By taking the intersection of DEGs,T2DM module genes,and immune-related genes,a total of 59 genes associated with the immune system were identified.Afterward,machine learning was utilized to identify three hub genes(H2-T24,Rac3,and Tfrc).The hub genes were associated with a variety of immune cells.The three hub genes were validated in GSE152539.Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro,consistent with the bioinformatics analysis.Additionally,11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia.We validated the expression of three hub genes

关键词： Bioinformatics analysis Type 2 diabetes mellitus Cognitive impairment Hippocampus Immune Microglia

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Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

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Energy Engineering 2024年第2期121卷 377-404页

作者： Liang Liu Guangda Xu Yuan Zhao Yi Lu Yu Li jing gao State Grid Jibei Electric Power Research Institute(North China Electric Power Research Institute Co. Ltd.)Beijing100045China

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

关键词： Electric vehicle transportation network voltage control queuing theory

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Tumor-targeted self-assembled micelles reducing PD-L1 expression combined with ICIs to enhance chemo-immunotherapy of TNBC

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Chinese Chemical Letters 2024年第2期35卷 305-310页

作者： Hongda Zhu Kai Ma Rui Ruan Chaobo Yang Aqin Yan jing Li Qi Yu Hongmei Sun Mingxing Liu Hongmei Zheng jing gao Xiaofang Guan Zhu Dai Yao Sun Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province) Key Laboratory of Fermentation Engineering (Ministry of Education)National “111” Center for Cellular Regulation and Molecular PharmaceuticsSchool of Food and Biological EngineeringHubei University of TechnologyWuhan 430068China Hubei Cancer Hospital Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430079China National Key Laboratory of Green Pesticide College of ChemistryCentral China Normal UniversityWuhan 430079China Key Laboratory of Medical Optics Suzhou Institute of Biomedical Engineering and TechnologyChinese Academy of SciencesSuzhou 215163China Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science Ministry of EducationQingdao University of Science and TechnologyQingdao 266000China

Immune checkpoint inhibitors(ICIs)therapy targeting programmed cell death ligand 1(PD-L1)and programmed death protein 1(PD-1)had exhibited significant clinical benefits for cancer treatment such as triple negative breast cancer(TNBC).However,the relatively low anti-tumor immune response rate and ICIs drug resistance highlight the necessity of developing ICIs combination therapy strategies to improve the anti-tumor effect of immunotherapy.Herein,the immunomodulator epigallocatechin gallate palmitate(PEGCG)and the immunoadjuvant metformin(MET)self-assembled into tumor-targeted micelles via hydrogen bond and electrostatic interaction,which encapsulated the therapeutic agents doxorubicin(DOX)-loaded PEGCG-MET micelles(PMD)and combined with ICIs(anti-PD-1 antibody)as therapeutic strategy to reduce the endogenous expression of PD-L1 and improve the tumor immunosuppressive microenvironment.The results presented that PMD integrated chemotherapy and immunotherapy to enhance antitumor efficacy in vitro and in vivo,compared with DOX or anti-PD-1 antibody for the therapy of TNBC.PMD micelles might be a potential candidate,which could remedy the shortcomings of antibody-based ICIs and provide synergistic effect to enhance the antitumor effects of ICIs in tumor therapy.

关键词： Immunotherapy Tumor-targeted Self-assembled micelles Metformin Reducing PD-L1 expression TNBC

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Carbon nanotube-supported mixed-valence Mn_(3)O_(4) electrodes for high-performance lithium-oxygen batteries

ChemPhysMater

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ChemPhysMater 2024年第1期3卷 94-102页

作者： Yuting Zhu jing gao Zhongxiao Wang Rui Sun Longwei Yin Chengxiang Wang Zhiwei Zhang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationSchool of Materials Science and EngineeringShandong UniversityJinan 250061China

Lithium-oxygen batteries(LOBs)have extensive applications because of their ultra-high energy densities.However,the practical application of LOBs is limited by several factors,such as a high overpotential,poor cycle stability,and limited rate capacity.In this paper,we describe the successful uniform loading of Mn_(3)O_(4) nanoparticles onto multi-walled carbon nanotubes(Mn_(3)O_(4)@CNT).CNTs form a conductive network and expose numerous catalytically active sites,and the one-dimensional porous structure provides a convenient channel for the transmission of Li+and O2 in LOBs.The electronic conductivity and electrocatalytic activity of Mn_(3)O_(4)@CNT are significantly better than those of MnO@CNT because of the inherent driving force facilitating charge transfer between different valence metal ions.Therefore,the Mn_(3)O_(4)@CNT cathode obtains a low overpotential(0.76 V at a limited capacity of 1000 mAh g^(-1)),high initial discharge capacity(16895 mAh g^(-1) at 200 mA g^(-1)),and long cycle life(97 cycles at 200 mA g^(-1)).This study provides evidence that transition metal oxides with mixed-valence states are suitable for application as efficient cathodes for LOBs.

关键词： Mixed-valence states Carbon nanotube Electrode reaction kinetics Lithium–oxygen batteries

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Three-Dimensional Multi-Phase Microscopic Simulation of Service Life of Recycled Large Aggregate Self-Compacting Concrete

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Journal of Materials Science and Chemical Engineering 2024年第4期12卷 126-135页

作者： jing Li Lina gao Libo Liu Liao Zhang Jianhua Zheng jing gao College of Pipeline and Civil Engineering China University of Petroleum (East China) Qingdao China China Huanqiu Contracting & Engineering Co. Ltd. Beijing China School of Civil and Transportation Engineering Beijing University of Civil Engineering and Architecture Beijing China The Fourth Construction Co. Ltd. of China Construction Eighth Engineering Division Qingdao China

Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .

关键词： Recycled Large Aggregate Self-Compacting Concrete Mesoscopic Mode Chloride Ion Diffusion Numerical Analysis

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Practice of Perioperative Rational Use of Antibacterial Drugs Based on Drug Pathway

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Medicinal Plant 2024年第2期15卷 57-60,64页

作者： Changkai ZHOU Fanbo jing Haijun QU jing gao The Third People s Hospital of Qingdao Qingdao 266041China The Affiliated Hospital of Qingdao University Qingdao 266100China

[Objectives]To establish a new management model for rational use of perioperative antibacterial drugs in surgical departments.[Methods]Based on evidence-based medicine,the department s drug pathway was formulated,and the new mode of rational drug use control was established by using fine pharmaceutical technology intervention,and the intervention effect was evaluated by the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs.[Results]After adopting drug pathway in departments,the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs decreased significantly,and the effect of rational drug use control was remarkable.[Conclusions]The drug pathway provides a new management and control mode for the rational use of perioperative antibacterial drugs in surgical departments of hospitals.Thus,it is worthy of popularization and application.

关键词： Perioperative period Antibacterial drugs Drug pathway Rational drug use Management model

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Advances in Research of Anti-tumor Effect of Aconiti Radix

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Medicinal Plant 2024年第2期15卷 80-83页

作者： jing gao Fanbo jing Lifang FENG Wen XU Changkai ZHOU The Third People s Hospital of Qingdao Qingdao 266041China The Affiliated Hospital of Qingdao University Qingdao 266100China

In this paper,the anti-tumor effects of Aconiti Radix were reviewed and summarized,and the clinical feasibility of Aconiti Radix as a potential anti-tumor drug was analyzed,in order to provide a useful reference for t... 详细信息

关键词： Aconiti Radix Anti-tumor Research advances Feasibility analysis

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Research on the IL-Bagging-DHKELM Short-Term Wind Power Prediction Algorithm Based on Error AP Clustering Analysis

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Computers, Materials & Continua 2024年第6期79卷 5017-5030页

作者： jing gao Mingxuan Ji Hongjiang Wang Zhongxiao Du School of Electric Power Shenyang Institute of EngineeringShenyang100083China

With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data,a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine(IL-Bagging-DHKELM)error affinity propagation cluster analysis is proposed.The algorithm effectively combines deep hybrid kernel extreme learning machine(DHKELM)with incremental learning(IL).Firstly,an initial wind power prediction model is trained using the Bagging-DHKELM model.Secondly,Euclidean morphological distance affinity propagation AP clustering algorithm is used to cluster and analyze the prediction error of wind power obtained from the initial training model.Finally,the correlation between wind power prediction errors and Numerical Weather Prediction(NWP)data is introduced as incremental updates to the initial wind power prediction model.During the incremental learning process,multiple error performance indicators are used to measure the overall model performance,thereby enabling incremental updates of wind power models.Practical examples show the method proposed in this article reduces the root mean square error of the initial model by 1.9 percentage points,indicating that this method can be better adapted to the current scenario of the continuous increase in wind power penetration rate.The accuracy and precision of wind power generation prediction are effectively improved through the method.

关键词： Short-term wind power prediction deep hybrid kernel extreme learning machine incremental learning error clustering

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Advances in bio-inspired electrocatalysts for clean energy future

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Nano Research 2024年第2期17卷 515-533页

作者： jing-Wen Duan Mu Min-Rui gao Division of Nanomaterials&Chemistry Hefei National Laboratory for Physical Sciences at the MicroscaleDepartment of ChemistryUniversity of Science and Technology of ChinaHefei 230026China

Electrocatalysis can enable efficient energy storage and conversion and thus is an effective way to achieve carbon neutrality.The unique structure and function of organisms can offer many ideas for the design of electrocatalysts,which has become one of the most promising research directions.Recently,the understanding of the mechanism of bio-inspired electrocatalysis has become clearer,which has promoted the design of bio-inspired catalysts and catalytic systems.Various bio-inspired catalysts(enzyme-like catalysts,layered porous catalysts,superhydrophobic/superhydrophilic surfaces,and so on)have been developed to enable efficient electrocatalytic reactions.Herein,we discuss the key advances in the field of bio-inspired electrocatalysts progressed in recent years.First,the role of bio-inspiration in increasing the intrinsic activity and number of active sites of catalysts is introduced.Then,the structure and mechanism of layered porous catalytic systems that mimic biological transport systems are comprehensively discussed.Subsequently,the design of three-phase interfaces from micro-nanoscale to atomic scale is highlighted,including the wettability of the electrode surface and the transport system near the electrode.We conclude the review by identifying challenges in bio-inspired electrocatalysts and providing insights into future prospects for the exciting research field.

关键词： bio-inspired electrocatalysts active sites layered porous structure three-phase interface

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Recorded recurrent deep reinforcement learning guidance laws for intercepting endoatmospheric maneuvering missiles

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Defence Technology（防务技术） 2024年第1期31卷 457-470页

作者： Xiaoqi Qiu Peng Lai Changsheng gao Wuxing jing Department of Aerospace Engineering Harbin Institute of TechnologyHarbin150001China Shanghai Electro-Mechanical Engineering Institute Shanghai Academy of Spaceflight TechnologyShanghai201100China

This work proposes a recorded recurrent twin delayed deep deterministic(RRTD3)policy gradient algorithm to solve the challenge of constructing guidance laws for intercepting endoatmospheric maneuvering missiles with uncertainties and observation noise.The attack-defense engagement scenario is modeled as a partially observable Markov decision process(POMDP).Given the benefits of recurrent neural networks(RNNs)in processing sequence information,an RNN layer is incorporated into the agent’s policy network to alleviate the bottleneck of traditional deep reinforcement learning methods while dealing with POMDPs.The measurements from the interceptor’s seeker during each guidance cycle are combined into one sequence as the input to the policy network since the detection frequency of an interceptor is usually higher than its guidance frequency.During training,the hidden states of the RNN layer in the policy network are recorded to overcome the partially observable problem that this RNN layer causes inside the agent.The training curves show that the proposed RRTD3 successfully enhances data efficiency,training speed,and training stability.The test results confirm the advantages of the RRTD3-based guidance laws over some conventional guidance laws.

关键词： Endoatmospheric interception Missile guidance Reinforcement learning Markov decision process Recurrent neural networks

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