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Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

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Neural Regeneration Research 2025年第5期20卷 1495-1504页

作者： Yunting Xiang Xiangxin Xing Xuyun Hua Yuwen zhang Xin Xue Jiajia wu Mouxiong Zheng He Wang Jianguang Xu School of Rehabilitation Science Shanghai University of Traditional Chinese MedicineShanghaiChina Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation Ministry of EducationShanghaiChina Department of Rehabilitation Medicine Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Department of Traumatology and Orthopedics Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghaiChina Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence(Fudan University) Ministry of EducationShanghaiChina Human Phenome Institute Fudan UniversityShanghaiChina

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected ***,differences among reconstruction strategies at the brain network level have not been *** study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve ***–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper ***-state brain functional magnetic resonance imaging was obtained 7 months after *** independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the *** in intra-network resting-state functional connectivity were compared among the *** muscle reinnervation was assessed by behavioral observation(elbow flexion)and *** results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural *** repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor *** thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve *** areas related to cognition and emotion were enhanced after end-to-side nerve *** study revealed important brain networks related to different nerve *** networks may be potential targets for enhancing motor recovery.

关键词： brain functional networks end-to-end nerve transfer end-to-side nerve transfer independent component analysis nerve repair peripheral plexus injury resting-state functional connectivity

An optimization method for metamorphic mechanisms based on multidisciplinary design optimization

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Chinese Journal of Aeronautics 2014年第6期27卷 1612-1618页

作者： zhang wuxiang wu teng Ding Xilun State Key Laboratory of Robotics and System Harbin Institute of Technology Institute of Robotics Beihang University

The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design variables and constraints in its multiple different configuration optimization models. To achieve the compatible optimized results of these coupled design variables, an optimization method for metamorphic mechanisms is developed in the paper based on the principle of multidisciplinary design optimization（MDO）. Firstly, the optimization characteristics of the metamorphic mechanism are summarized distinctly by proposing the classification of design variables and constraints as well as coupling interactions among its different configuration optimization models. Further, collaborative optimization technique which is used in MDO is adopted for achieving the overall optimization performance. The whole optimization process is then proposed by constructing a two-level hierarchical scheme with global optimizer and configuration optimizer loops. The method is demonstrated by optimizing a planar five-bar metamorphic mechanism which has two configurations,and results show that it can achieve coordinated optimization results for the same parameters in different configuration optimization models.

关键词： Configuration Mechanism Metamorphic mechanisms Method Multidisciplinary design optimization Optimization model

An Efficient Boron Source Activation Strategy for the Low‑Temperature Synthesis of Boron Nitride Nanotubes

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Nano-Micro Letters 2025年第1期17卷 548-558页

作者： Ying Wang Kai zhang Liping Ding Liyun wu Songfeng E Qian He Nanyang Wang Hui Zuo Zhengyang Zhou Feng Ding Yue Hu Jin zhang Yagang Yao National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional Materialsand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093People’s Republic of China School of Electronic Information and Artificial Intelligence Shaanxi University of Science&TechnologyXian 710000People’s Republic of China College of Bioresources Chemical and Materials Engineering Shaanxi University of Science&TechnologyXian 710000People’s Republic of China Key Laboratory of Carbon Materials of Zhejiang Province College of Chemistry and Materials EngineeringWenzhou UniversityWenzhou 325000People’s Republic of China Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518000People’s Republic of China College of Chemical and Molecular Engineering Peking UniversityBeijing 100871People’s Republic of China

Lowering the synthesis temperature of boron nitride nanotubes(BNNTs)is crucial for their *** primary reason for adopting a high temperature is to enable the effective activation of highmelting-point solid *** this study,we developed a novel approach for efficiently activating boron by introducing alkali metal compounds into the conventional MgO–B *** approach can be adopted to form various low-melting-point AM–Mg–B–O growth *** growth systems have improved catalytic capability and reactivity even under low-temperature conditions,facilitating the synthesis of BNNTs at temperatures as low as 850℃.In addition,molecular dynamics simulations based on density functional theory theoretically demonstrate that the systems maintain a liquid state at low temperatures and interact with N atoms to form BN *** findings offer novel insights into the design of boron activation and are expected to facilitate research on the low-temperature synthesis of BNNTs.

关键词： Boron nitride nanotubes Low-temperature Boron activation Density functional theory

Insights into spinal muscular atrophy from molecular biomarkers

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Neural Regeneration Research 2025年第7期20卷 1849-1863页

作者： Xiaodong Xing Xinzhu Liu Xiandeng Li Mi Li Xian wu Xiaohui Huang Ajing Xu Yan Liu Jian zhang Department of Clinical Pharmacy Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghaiChina College of Pharmacy Chongqing Medical UniversityChongqingChina

Spinal muscular atrophy is a devastating motor neuron disease characterized by severe cases of fatal muscle *** is one of the most common genetic causes of mortality among infants aged less than 2 *** research is currently receiving more attention,and new candidate biomarkers are constantly being *** review initially discusses the evaluation methods commonly used in clinical practice while briefly outlining their respective pros and *** also describe recent advancements in research and the clinical significance of molecular biomarkers for spinal muscular atrophy,which are classified as either specific or non-specific *** review provides new insights into the pathogenesis of spinal muscular atrophy,the mechanism of biomarkers in response to drug-modified therapies,the selection of biomarker candidates,and would promote the development of future ***,the successful utilization of biomarkers may facilitate the implementation of gene-targeting treatments for patients with spinal muscular atrophy.

关键词： biomarkers disease progression gene-targeting therapy neurofilaments Nusinersen spinal muscular atrophy(SMA) survival motor neuron therapeutic evaluation treatment outcomes

Knowledge Transfer Learning via Dual Density Sampling for Resource-Limited Domain Adaptation

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2269-2291页

作者： Zefeng Zheng Luyao teng Wei zhang Naiqi wu Shaohua teng the School of Computer Science and Technology Guangdong University of TechnologyGuangzhou 510006China the School of Information Engineering Guangzhou Panyu PolytechicGuangzhou 511483China the Faculty of Information Technology Monash University20 Exhibition Walk ClaytonVIC 3800Australia IEEE the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems Macao University of Science and TechnologyMacao 999078China

Most existing domain adaptation(DA) methods aim to explore favorable performance under complicated environments by ***,there are three unsolved problems that limit their efficiencies:ⅰ) they adopt global sampling but neglect to exploit global and local sampling simultaneously;ⅱ)they either transfer knowledge from a global perspective or a local perspective,while overlooking transmission of confident knowledge from both perspectives;and ⅲ) they apply repeated sampling during iteration,which takes a lot of *** address these problems,knowledge transfer learning via dual density sampling(KTL-DDS) is proposed in this study,which consists of three parts:ⅰ) Dual density sampling(DDS) that jointly leverages two sampling methods associated with different views,i.e.,global density sampling that extracts representative samples with the most common features and local density sampling that selects representative samples with critical boundary information;ⅱ)Consistent maximum mean discrepancy(CMMD) that reduces intra-and cross-domain risks and guarantees high consistency of knowledge by shortening the distances of every two subsets among the four subsets collected by DDS;and ⅲ) Knowledge dissemination(KD) that transmits confident and consistent knowledge from the representative target samples with global and local properties to the whole target domain by preserving the neighboring relationships of the target *** analyses show that DDS avoids repeated sampling during the *** the above three actions,confident knowledge with both global and local properties is transferred,and the memory and running time are greatly *** addition,a general framework named dual density sampling approximation(DDSA) is extended,which can be easily applied to other DA *** experiments on five datasets in clean,label corruption(LC),feature missing(FM),and LC&FM environments demonstrate the encouraging performance of KTL-DDS.

关键词： Cross-domain risk dual density sampling intra-domain risk maximum mean discrepancy knowledge transfer learning resource-limited domain adaptation

Adaptive Graph Embedding With Consistency and Specificity for Domain Adaptation

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2094-2107页

作者： Shaohua teng Zefeng Zheng Naiqi wu Luyao teng Wei zhang School of Computer Science and Technology Guangdong University of TechnologyGuangzhou 510006China Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems Macao University of Science and TechnologyMacao 999078China School of Information Engineering Guangzhou Panyu PolytechicGuangzhou 511483China Faculty of Information Technology Monash University20 Exhibition Walk ClaytonVIC 3800Australia IEEE

Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabeled target samples *** approaches leverage Graph Embedding Learning to explore such a subspace. Unfortunately, due to 1) the interaction of the consistency and specificity between samples, and 2) the joint impact of the degenerated features and incorrect labels in the samples, the existing approaches might assign unsuitable similarity, which restricts their performance. In this paper, we propose an approach called adaptive graph embedding with consistency and specificity(AGE-CS) to cope with these issues. AGE-CS consists of two methods, i.e., graph embedding with consistency and specificity(GECS), and adaptive graph embedding(AGE).GECS jointly learns the similarity of samples under the geometric distance and semantic similarity metrics, while AGE adaptively adjusts the relative importance between the geometric distance and semantic similarity during the iterations. By AGE-CS,the neighborhood samples with the same label are rewarded,while the neighborhood samples with different labels are punished. As a result, compact structures are preserved, and advanced performance is achieved. Extensive experiments on five benchmark datasets demonstrate that the proposed method performs better than other Graph Embedding methods.

关键词： Adaptive adjustment consistency and specificity domain adaptation graph embedding geometrical and semantic metrics

Enhanced electrochemical CO_(2)reduction coupled with urea oxidation using bifunctional atomically dispersed CuNi catalysts

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Nano Research 2025年第1期18卷 208-216页

作者： Wenjie wu Haoyang Zhou Ying Liu Yifei Pan Qingqing Chen Yu zhang Junjie Mao Wenjie Ma Ping Yu Beijing National Laboratory for Molecular Sciences Key Laboratory of Analytical Chemistry for Living BiosystemsInstitute of ChemistryChinese Academy of Sciences(CAS)Beijing 100190China College of Chemistry and Materials Science Anhui Normal UniversityWuhu 241002China University of Chinese Academy of Sciences Beijing 100049China

The electrochemical conversion of carbon dioxide(CO_(2))into chemical fuels represents a promising approach for addressing global carbon balance ***,this process is hindered by the kinetic limitations of anodic reactions,usually the oxygen evolution reaction,resulting in less efficient production of high value-added ***,we report an integrated electrocatalytic system that couples CO_(2)reduction reaction(CO_(2)RR)with urea oxidation reaction(UOR)using a bifunctional electrocatalyst with atomically dispersed dual-metal CuNi sites anchored on bamboo-like nitrogen-doped carbon nanotubes(CuNi-CNT),which were synthesized through a one-step pyrolysis *** bifunctional CuNi-CNT catalyst exhibits a near 100%CO Faraday efficiency for CO_(2)RR over a wide potential range and outstanding UOR performance with a negatively shifted potential of 210 mV at 10 mA·cm^(-2).In addition,we assemble a two-electrode electrolyzer using bifunctional CuNi-CNT-modified carbon fiber paper electrodes as both cathode and anode,capable of operating at a remarkably low cell voltage of 1.81 V at 10 mA·cm-2,significantly lower than conventional *** study provides a novel avenue to achieving an efficient carbon cycle with reduced electric power consumption.

关键词： electrochemical conversion bimetallic site catalyst bifunctional electrocatalyst carbon dioxide reduction urea oxidation

SVM-DT-Based Adaptive and Collaborative Intrusion Detection

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 108-118页

作者： Shaohua teng Naiqi wu Haibin Zhu Luyao teng Wei zhang School of Computer Science and Technology Guangdong University of Technology Guangzhou 510006 China Institute of Systems Engineering Macao University of Science and Technology Macao 999078 China school of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou 510006 China Collaborative Systems Laboratory Nipissing University North Bay Ontario PICILZ Canada College of Engineering and Science Victoria University Ballarat Rd Footscray VIC 3011 Australia IEEE

As a primary defense technique, intrusion detection becomes more and more significant since the security of the networks is one of the most critical issues in the world. We present an adaptive collaboration intrusion detection method to improve the safety of a network. A self-adaptive and collaborative intrusion detection model is built by applying the Environmentsclasses, agents, roles, groups, and objects(E-CARGO) model. The objects, roles, agents, and groups are designed by using decision trees(DTs) and support vector machines(SVMs), and adaptive scheduling mechanisms are set up. The KDD CUP 1999 data set is used to verify the effectiveness of the method. The experimental results demonstrate the feasibility and efficiency of the proposed collaborative and adaptive intrusion detection method. Also, the proposed method is shown to be more predominant than the methods that use a set of single type support vector machine(SVM) in terms of detection precision rate and recall rate.

关键词： Adaptive and collaborative intrusion detection decision tree(DT) support vector machines(SVM)

Hemoglobin integrated red blood cell membrane-coated metalorganic framework nano-platform for improving the self-adaptive blood glucose management

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Nano Research 2025年第1期18卷 618-627页

作者： Shuai wu Li Zhu Sheng Ni Xiong Zhao Meng Yan Yuan Zhong Karissa Kusuma Yi Liang Kaiwen Bao Kai Qu Xian Qin Kun zhang wuquan Deng Da Sun Wei wu Key Laboratory of Biorheological Science and Technology Ministry of EducationCollege of BioengineeringChongqing UniversityChongqing 400044China Chongqing University Three Gorges Hospital Chongqing Municipality Clinical Research Center for Endocrinology and Metabolic DiseasesChongqing 404000China Institute of Life Sciences&Biomedical Collaborative Innovation Center of Zhejiang Province Wenzhou UniversityWenzhou 325035China Department of Endocrinology School of MedicineChongqing Emergency Medical CenterChongqing University Central HospitalChongqing 400014China

Diabetes,a prevalent chronic metabolic disorder,often leads to severe ***,existing treatment methods may pose life-threatening risks due to poor patient compliance and inaccurate dosing of subcutaneous insulin ***,a biomimetic red blood cell(RBC)membrane-coated glucose-responsive nanoplatform is developed for controlling insulin *** nanoplatforms with RBC membrane can prolong the half-life of nano-formulation in vivo mediated by the biomimetic immune ***,the cascade catalytic effect of glucose oxidase(GOx)encapsulated in metal-organic frameworks(MOFs)and hemoglobin(Hb)in the RBC membrane are able to not only facilitate glucose-responsive insulin release,but also eliminate the detrimental by-product hydrogen peroxide(H_(2)O_(2))resulting from the Hb mediated H_(2)O_(2)*** in vitro and in vivo studies have demonstrated the favorable glucose-responsive performances of this advanced nano-platform with a single intravenous injection maintaining blood glucose balance in Type 1 Diabetes(T1D)mice for an extended duration without the hypoglycemia ***,this biomimetic insulin delivery system is poised to function as a strategy for the intravenous insulin administration,offering a promising drug candidate for the self-adaptive long-term T1D treatment.

关键词： glucose-responsive metal-organic frameworks red blood cell membrane insulin delivery glucose oxidase hemoglobin