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Pathological Networks Involving Dysmorphic Neurons in Type ⅡFocal Cortical Dysplasia

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Neuroscience Bulletin 2022年第9期38卷 1007-1024页

作者： Yijie Shao Qianqian Ge Jiachao Yang Mi Wang Yu Zhou Jin-Xin Guo Mengyue Zhu Jiachen Shi Yiqi Hu Li Shen Zhong Chen Xiao-Ming Li Jun-Ming Zhu Jianmin Zhang Shumin Duan Jiadong Chen Center for Neuroscience and Department of Neurosurgery of the Second Affiliated Hospital NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Research and Brain-Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang University School of MedicineHangzhou310058China Department of Neurosurgery of the Second Affiliated Hospital Zhejiang University School of MedicineHangzhou310009China The MOE Key Laboratory of Biosystems Homeostasis&Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology Life Sciences InstituteZhejiang UniversityHangzhou310058China Department of Orthopedic Surgery School of Medicinethe Second Affiliated HospitalZhejiang UniversityHangzhou310009China Hangzhou Innovation Center Zhejiang UniversityHangzhou310058China Institute of Pharmacology&Toxicology NHC and CAMS Key Laboratory of Medical NeurobiologyCollege of Pharmaceutical SciencesSchool of Basic Medical SciencesZhejiang UniversityHangzhou310058China Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province College of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhou310058China Center for Neuroscience and Department of Neurology of the Second Affiliated Hospital Zhejiang University School of MedicineHangzhou310058China NHC and CAMS Key Laboratory of Medical Neurobiology Center for Brain Science and Brain-Inspired IntelligenceJoint Institute for Genetics and Genome Medicine betweenGuangdong Hong Kong Macao Greater Bay AreaZhejiang University and the University of TorontoZhejiang University School of MedicineHangzhou310058China

Focal cortical dysplasia(FCD)is one of the most common causes of drug-resistant epilepsy.Dysmorphic neurons are the major histopathological feature of typeⅡFCD,but their role in seizure genesis in FCD is unclear.Here we performed whole-cell patch-clamp recording and morphological reconstruction of cortical principal neurons in postsurgical brain tissue from drug-resistant epilepsy patients.Quantitative analyses revealed distinct morphological and electrophysiological characteristics of the upper layer dysmorphic neurons in typeⅡFCD,including an enlarged soma,aberrant dendritic arbors,increased current injection for rheobase action potential firing,and reduced action potential firing frequency.Intriguingly,the upper layer dysmorphic neurons received decreased glutamatergic and increased GABAergic synaptic inputs that were coupled with upregulation of the Na^(+)-K^(+)-Cl^(−)cotransporter.In addition,we found a depolarizing shift of the GABA reversal potential in the CamKⅡ-cre::PTENflox/flox mouse model of drug-resistant epilepsy,suggesting that enhanced GABAergic inputs might depolarize dysmorphic neurons.Thus,imbalance of synaptic excitation and inhibition of dysmorphic neurons may contribute to seizure genesis in typeⅡFCD.

关键词： Focal cortical dysplasia Dysmorphic neuron Whole-cell patch-clamp recording Morphological reconstruction Excitation-inhibition balance

Editorial Special Issue on Simulation and AI

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Journal of Systems Science and Systems Engineering 2023年第3期32卷 265-266页

作者： yijie Peng Yaodong Yang Center for Multi-Agent Research Institute for AIPeking UniversityBeijing 100871China Guanghua School of Management Peking UniversityBeijing 100871China

Simulation is an important area in Operations Research,Management Science and many disciplines,and it has many advantages in analyzing the performance of complex stochastic models.Over the last 15 years,AI has been gaining steam and fundamentally reshaped a number of current and emerging areas.Simulation plays a central role in deep learning and reinforcement learning,which are the foundation of AI,and it can continue improving the AI techniques,particularly in addressing some of its bottlenecks.

关键词： has shaped continue

A probabilistic model based on the peak-over-threshold approach for risk assessment of airport controllers’performance

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Journal of Safety Science and Resilience 2024年第1期5卷 110-118页

作者： Lili Zu yijie Lu Min Dong College of Economics and Management Nanjing University of Aeronautics and AstronauticsNanjing 211106China School of Engineering and Applied Science George Washington UniversityWashington DC 20052USA College of Civil Aviation Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Airport tower control plays an instrumental role in ensuring airport safety.However,obtaining objective,quantitative safety evaluations is challenging due to the unavailability of pertinent human operation data.This study introduces a probabilistic model that combines aircraft dynamics and the peak-over-threshold(POT)approach to assess the safety performance of airport controllers.We applied the POT approach to model reaction times extracted from a radiotelephony dataset via a voice event detection algorithm.The model couples the risks of tower control and aircraft operation to analyze the influence of human factors.Using data from radiotele-phony communications and the Base of Aircraft Data(BADA)database,we compared risk levels across scenarios.Our findings revealed heightened airport control risks under low demand(0.374)compared to typical conditions(0.197).Furthermore,the risks associated with coupling under low demand exceeded those under typical de-mand,with the final approach stage presenting the highest risk(4.929×107).Our model underscores the significance of human factors and the implications of mental disconnects between pilots and controllers for safety risks.Collectively,these consistent findings affirm the reliability of our probabilistic model as an evaluative tool for evaluating the safety performance of airport tower controllers.The results also illuminate the path toward quantitative real-time safety evaluations for airport controllers within the industry.We recommend that airport regulators focus on the performance of airport controllers,particularly during the final approach stage.

关键词： Safety evaluation Performance Probabilistic model Task demand Airport controller

Dry-type AMDT Fault Detection Based on Vibration Signal Analysis by Wavelet Packet

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中国电工技术学会电机与系统学报(英文) 2023年第3期7卷 341-349页

作者： Daosheng Liu Peng Li yijie Chen IEEE Jiangxi University of Science and Technology GanzhouChina341000 School of Electrical Engineering and Automation Jiangxi University of Science and Technology

Amorphous metal distribution transformers(AMDT)are widely used in power grids due to their low no-load loss.Many scholars have carried out research on the fault detection of transformer windings,tap changers and the other parts.However,due to the high magnetostriction of the amorphous alloy,the vibration generated by AMDT during operation will cause various mechanical failures.This paper studies the vibration characteristics of SCBH 15-200/100 AMDT through no-load tests to find some mechanical failures of AMDT.The installation position of the vibration sensor in AMDT are determined according to finite element analysis(FEA)of the magnetic flux density distribution and modal analysis,and the vibration analyses are performed under different operating conditions of AMDT.The wavelet packet transform(WPT)is used to perform detailed analysis of the vibration signal in the time domain and frequency domain to obtain the energy characteristic value of each frequency band,and it includes the frequency spectrum and waveform data under normal and fault conditions.After obtaining the energy characteristic thresholds of different frequency bands under different conditions,the operating status can be detected by comparing test data with the thresholds.The operation condition including mechanical failures induced by magnetostrictive actions can be accurately determined by the energy characteristic value,such as loose nuts and stress,etc.

关键词： AMDT FEA WPT Energy eigenvalue Mechanical failures

大补元煎联合运动通过调控PI3K/Akt/GSK-3β信号通路改善AD大鼠学习记忆能力

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中国实验方剂学杂志 2022年第20期28卷 1-7页

作者：江曦孙傲张毅洁王平邵玉萍湖北中医药大学基础医学院武汉430065 武汉体育学院健康科学学院武汉430079 湖北中医药大学老年医学研究所武汉430065 湖北中医药大学体育健康学院武汉430065

目的:研究大补元煎灌胃联合4周的跑台运动对阿尔茨海默病(AD)大鼠磷脂酰肌醇3-激酶(PI3K)/蛋白激酶B(Akt)/糖原合成酶激酶-3β(GSK-3β)信号通路及相关细胞凋亡蛋白的调节作用,探讨其改善AD大鼠认知功能的作用机制。方法:将50只雄性SD... 详细信息

目的:研究大补元煎灌胃联合4周的跑台运动对阿尔茨海默病(AD)大鼠磷脂酰肌醇3-激酶(PI3K)/蛋白激酶B(Akt)/糖原合成酶激酶-3β(GSK-3β)信号通路及相关细胞凋亡蛋白的调节作用,探讨其改善AD大鼠认知功能的作用机制。方法:将50只雄性SD大鼠随机均分为假手术组(Sham组)、运动组(EX组)、模型组(AD组)、大补元煎组(TCM组)、运动+大补元煎组(EX+TCM组),每组10只。采用海马区注射β淀粉样蛋白25-35(Aβ25-35)寡聚体溶液建立AD大鼠模型,EX组进行6 d/周的跑台训练。TCM组予大补元煎水煎液灌胃(5.36 g·kg^(-1)),EX+TCM组在跑台训练同时进行大补元煎水煎液灌胃,Sham组、AD组及EX组给予等容纯水灌胃。Morris水迷宫评价大鼠的学习记忆,苏木素-伊红(HE)染色观察大鼠海马神经元的形态变化,透射电镜观察海马神经元超微结构的改变,蛋白免疫印迹法(Western blot)检测大鼠海马中蛋白激酶B(Akt)、磷酸化(p)-Akt、GSK-3β、p-GSK-3β、β-连环蛋白(β-catenin)、B细胞淋巴瘤-2(Bcl-2)、Bcl-2相关X蛋白(Bax)、剪切的胱天蛋白酶-3(cleaved Caspase-3)蛋白表达水平。结果:与Sham组比较,AD组大鼠逃避潜伏期和游泳总路程显著增加,目标象限停留时间显著减少(P<0.01),海马锥体细胞排列疏松紊乱,密度降低;海马超微结构出现髓鞘样改变,线粒体肿胀模糊;Bcl-2、p-Akt、p-GSK-3β的水平显著降低、β-catenin表达明显下降(P<0.05,P<0.01)、cleaved Caspase-3表达明显上调(P<0.05)。与AD组比较,EX组、TCM组、EX+TCM组大鼠逃避潜伏期和游泳路程明显减少,目标象限停留时间明显增加(P<0.05,P<0.01);锥体细胞排列规律,细胞数量增加,透射电镜下可见髓鞘样改变减轻,线粒体肿胀改善;Bcl-2、p-Akt、p-GSK-3β表达升高,cleaved Caspase-3表达水平明显降低(P<0.05,P<0.01),且EX+TCM组β-catenin水平升高而EX组、TCM组与AD组比较差异无统计学意义。与EX+TCM组比较,EX组与TCM组逃避潜伏期和游泳路程增加(P<0.05,P<0.01),目标象限停留时间显著减少(P<0.01);锥体细胞排列疏松,电镜下突触完整性下降;Bcl-2、p-Akt、p-GSK-3β、β-catenin的水平明显降低(P<0.05,P<0.01),cleaved Caspase-3表达明显升高(P<0.05)。结论:有氧运动结合大补元煎可改善AD大鼠认知功能障碍,其机制可能与升高PI3K/Akt/GSK-3β信号通路中的关键蛋白表达有关,且联合使用优于运动或药物单独使用。

关键词：大补元煎有氧运动阿尔茨海默病认知功能障碍

Solving Inventory Management Problems through Deep Reinforcement Learning

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Journal of Systems Science and Systems Engineering 2022年第6期31卷 677-689页

作者： Qinghao Wang yijie Peng Yaodong Yang Center for Multi-Agent Research Institute for AIPeking UniversityBeijing 100871China Guanghua School of Management Peking UniversityBeijing 100871China College of Engineering Peking UniversityBeijing 100871China

Inventory management(e.***.lost sales)is a central problem in supply chain management.Lost sales inventory systems with lead times and complex cost function are notoriously hard to optimize.Deep reinforcement learning(DRL)methods can learn optimal decisions based on trails and errors from the environment due to its powerful complex function representation capability and has recently shown remarkable successes in solving challenging sequential decision-making problems.This paper studies typical lost sales and multi-echelon inventory systems.We first formulate inventory management problem as a Markov Decision Process by taking into account ordering cost,holding cost,fixed cost and lost-sales cost and then develop a solution framework DDLS based on Double deep Q-networks(DQN).In the lost-sales scenario,numerical experiments demonstrate that increasing fixed ordering cost distorts the ordering behavior,while our DQN solutions with improved state space are flexible in the face of different cost parameter settings,which traditional heuristics find challenging to handle.We then study the effectiveness of our approach in multi-echelon scenarios.Empirical results demonstrate that parameter sharing can significantly improve the performance of DRL.As a form of information sharing,parameter sharing among multi-echelon suppliers promotes the collaboration of agents and improves the decisionmaking efficiency.Our research further demonstrates the potential of DRL in solving complex inventory management problems.

关键词： Inventory management deep reinforcement learning parameter sharing lost sales multiechelonmodels

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单纯性先天性上睑下垂危险因素分析

中华实验眼科杂志 2023年第3期41卷 266-270页

作者：邵霁汪伊洁楼丽霞徐宇峰叶娟浙江大学医学院附属第二医院眼科杭州310009

目的探究单纯性先天性上睑下垂的危险因素。方法采用病例对照研究方法,选取2018年10月至2021年1月于浙江大学医学院附属第二医院就诊的单纯性先天性上睑下垂患儿106例为病例组,以同期无先天性异常且性别相匹配的儿童106例为对照组。对... 详细信息

目的探究单纯性先天性上睑下垂的危险因素。方法采用病例对照研究方法,选取2018年10月至2021年1月于浙江大学医学院附属第二医院就诊的单纯性先天性上睑下垂患儿106例为病例组,以同期无先天性异常且性别相匹配的儿童106例为对照组。对所有受检者进行睑裂高度、睑缘反射点距离1等眼科检查,并对患儿母亲进行问卷调查。问卷内容包括:人口统计信息、妊娠期疾病史和妊娠期医疗及环境暴露情况。采用单变量分析比较病例组与对照组间各变量的差异。将P<0.20的变量纳入多因素Logistic回归分析单纯性先天性上睑下垂的危险因素。模型拟合度采用Hosmer-Lemeshow检验,以方差扩大因子(VIF)评价各因素的共线性。结果病例组与对照组孕周<37周、胎次≥2次、母亲年龄、孕早期抗生素药物摄入、父亲吸烟≥半包/d以及妊娠期母亲被动吸烟例数比较,均P<0.20。多因素Logistic回归分析结果显示,孕周<37周[比值比(OR)=4.58;95%置信区间(CI):1.24~16.85],父亲吸烟≥半包/d(OR=2.28;95%CI:1.22~4.28)以及母亲妊娠期被动吸烟(OR=3.13;95%CI:1.16~8.41)是单纯性先天性上睑下垂的危险因素。各个危险因素之间无显著共线性关系(均VIF<5)。结论早产、父亲吸烟、母亲妊娠期被动吸烟是单纯性先天性上睑下垂的独立危险因素。

关键词：先天性上睑下垂危险因素早产吸烟

Maintenance Strategy of Multi-Component System Due to Degradation and Shock

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Journal of Harbin Institute of Technology(New Series) 2023年第2期30卷 73-83页

作者： yijie Chen Jian Tian Basic Department Software Engineering Institute of GuangzhouGuangzhou 510900GuangdongChina

The proposed maintenance strategy uses component grades and survival signature to describe and update system structure. A system dynamic stress-strength reliability(SSR) model was established to describe component failure processes because of internal degradation and external shock. Besides, a corrective maintenance rule and two-level preventive maintenance rule made up the proposed maintenance strategy. The former combined sequentially minimal repair and corrective replacement(SMRCR) based on system structure updating. The latter considered group importance measure based on the system dynamic SSR and preventive maintenance cost. Further, a cost model was developed by the proposed strategy, and the optimal decision variables were found by genetic algorithm. Finally, using a case system to illustrate the above strategy improved system and reduced maintenance costs.

关键词： survival signature system structure updating system dynamic stress-strength reliability group importance measure

A Deep Learning Drug-Target Binding Affinity Prediction Based on Compound Microstructure and Its Application in COVID-19 Drug Screening

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Journal of Beijing Institute of Technology 2023年第4期32卷 396-405页

作者： yijie Guo Xiumin Shi Han Zhou School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China

Drug target relationship(DTR)prediction is a rapidly evolving area of research in com-putational drug discovery.Despite recent advances in computational solutions that have overcome the challenges of in vitro and in vivo experiments,most computational methods still focus on binary classification.They ignore the importance of binding affinity,which correctly distinguishes between on-targets and off-targets.In this study,we propose a deep learning model based on the microstruc-ture of compounds and proteins to predict drug-target binding affinity(DTA),which utilizes topo-logical structure information of drug molecules and sequence semantic information of proteins.In this model,graph attention network(GAT)is used to capture the deep features of the compound molecular graph,and bidirectional long short-term memory(BiLSTM)network is used to extract the protein sequence features,and the pharmacological context of DTA is obtained by combining the two.The results show that the proposed model has achieved superior performance in both cor-rectly predicting the value of interaction strength and correctly discriminating the ranking of bind-ing strength compared to the state-of-the-art baselines.A case study experiment on COVID-19 con-firms that the proposed DTA model can be used as an effective pre-screening tool in drug discovery.

关键词： compound microstructure drug-target interaction binding affinity deep learning COVID-19