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Mechanism of inflammatory response and therapeutic effects of stem cells in ischemic stroke:current evidence and future perspectives

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Neural Regeneration research 2025年第1期20卷 67-81页

作者： Yubo Wang Tingli Yuan Tianjie Lyu Ling Zhang Meng Wang Zhiying He Yongjun Wang Zixiao Li Vascular Neurology Department of NeurologyBeijing Tiantan HospitalCapital Medical UniversityBeijingChina China National Clinical research center for Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Shanghai Engineering research center of Stem Cells Translational Medicine ShanghaiChina National center for Healthcare Quality Management in Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Institute for Regenerative Medicine Shanghai East HospitalSchool of Life Sciences and TechnologyTongji UniversityShanghaiChina Chinese Institute for Brain research BeijingChina research Unit of artificial intelligence in Cerebrovascular Disease Chinese Academy of Medical SciencesBeijingChina Beijing Engineering research center of Digital Healthcare for Neurological Diseases BeijingChina

Ischemic stroke is a leading cause of death and disability worldwide,with an increasing trend and tendency for onset at a younger ***,in particular,bears a high burden of stroke *** recent years,the inflammatory response after stroke has become a research hotspot:understanding the role of inflammatory response in tissue damage and repair following ischemic stroke is an important direction for its *** review summarizes several major cells involved in the inflammatory response following ischemic stroke,including microglia,neutrophils,monocytes,lymphocytes,and ***,we have also highlighted the recent progress in various treatments for ischemic stroke,particularly in the field of stem cell ***,understanding the complex interactions between inflammation and ischemic stroke can provide valuable insights for developing treatment strategies and improving patient *** cell therapy may potentially become an important component of ischemic stroke treatment.

关键词： cell therapy immune cell inflammatory ischemic stroke stem cell

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Epigenetic regulation of the inflammatory response in stroke

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Neural Regeneration research 2025年第11期20卷 3045-3062页

作者： Jingyi Liang Fei Yang Zixiao Li Qian Li School of Basic medical Sciences Capital Medical UniversityBeijingChina Department of Neurobiology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Laboratory for Clinical Medicine Beijing Key Laboratory of Neural Regeneration and RepairCapital Medical UniversityBeijingChina Department of Neurology Beijing Tiantan HospitalCapital Medical UniversityBeijingChina China National Clinical research center for Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina National center for Healthcare Quality Management in Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Chinese Institute for Brain research BeijingChina research Unit of artificial intelligence in Cerebrovascular Disease Chinese Academy of Medical SciencesBeijingChina Beijing Engineering research center of Digital Healthcare for Neurological Diseases BeijingChina Department of Biochemistry and Molecular Biology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Beijing Key Laboratory of Cancer Invasion and Metastasis research Capital Medical UniversityBeijingChina

Stroke is classified as ischemic or hemorrhagic,and there are few effective treatments for either *** mechanisms play a critical role in secondary brain injury following a stroke,which manifests as cytokine release,blood–brain barrier disruption,neuronal cell death,and ultimately behavioral *** the inflammatory response has been shown to mitigate this cascade of events in experimental stroke ***,in clinical trials of anti-inflammatory agents,longterm immunosuppression has not demonstrated significant clinical benefits for *** may be attributable to the dichotomous roles of inflammation in both tissue injury and repair,as well as the complex pathophysiologic inflammatory processes in *** acute harmful inflammatory responses or inducing a phenotypic shift from a pro-inflammatory to an anti-inflammatory state at specific time points after a stroke are alternative and promising therapeutic *** agents that can modulate inflammation requires a detailed understanding of the inflammatory processes of ***,epigenetic reprogramming plays a crucial role in modulating post-stroke inflammation and can potentially be exploited for stroke *** this review,we summarize current findings on the epigenetic regulation of the inflammatory response in stroke,focusing on key signaling pathways including nuclear factor-kappa B,Janus kinase/signal transducer and activator of transcription,and mitogen-activated protein kinase as well as inflammasome *** also discuss promising molecular targets for stroke *** evidence to date indicates that therapeutic targeting of the epigenetic regulation of inflammation can shift the balance from inflammation-induced tissue injury to repair following stroke,leading to improved post-stroke outcomes.

关键词： DNA methylation histone modification intracerebral hemorrhage ischemic stroke neuroinflammation neuroprotection non-coding RNA RNA methylation subarachnoid hemorrhage treatment

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Flexible Graphene Field‑Effect Transistors and Their application in Flexible Biomedical Sensing

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Nano-Micro Letters 2025年第2期17卷 252-313页

作者： Mingyuan Sun Shuai Wang Yanbo Liang Chao Wang Yunhong Zhang Hong Liu Yu Zhang Lin Han Institute of Marine Science and Technology Shandong UniversityQingdao 266237ShandongPeople’s Republic of China State Key Laboratory of Crystal Materials Shandong UniversityJinan 250100ShandongPeople’s Republic of China School of Integrated Circuits Shandong UniversityJinan 250100ShandongPeople’s Republic of China Shandong Engineering research center of Biomarker and artificial intelligence application Jinan250100ShandongPeople’s Republic of China

Flexible electronics are transforming our lives by making daily activities more *** to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and ***,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and *** combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical ***,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning *** ability of FGFETs to sense strains and biomolecular charges opens up diverse application *** specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical ***,we discuss the current challenges and prospects of FGFETs and their applications in biomedical *** review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

关键词： Flexible Graphene Field-effect transistor Wearable Implantable Biosensor

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Repetitive transcranial magnetic stimulation in Alzheimer’s disease:effects on neural and synaptic rehabilitation

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Neural Regeneration research 2025年第2期20卷 326-342页

作者： Yi Ji Chaoyi Yang Xuerui Pang Yibing Yan Yue Wu Zhi Geng Wenjie Hu Panpan Hu Xingqi Wu Kai Wang Department of Neurology The First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders HefeiAnhui ProvinceChina Collaborative Innovation center of Neuropsychiatric Disorders and Mental Health HefeiAnhui ProvinceChina Institute of artificial intelligence Hefei Comprehensive National Science CenterHefeiAnhui ProvinceChina Department of Psychology and Sleep Medicine The Second Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina

Alzheimer’s disease is a neurodegenerative disease resulting from deficits in synaptic transmission and *** Alzheimer’s disease brain tends to be hyperexcitable and hypersynchronized,thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life,leaving patients *** transcranial magnetic stimulation is a cost-effective,neuro-modulatory technique used for multiple neurological *** the past two decades,it has been widely used to predict cognitive decline;identify pathophysiological markers;promote neuroplasticity;and assess brain excitability,plasticity,and *** has also been applied to patients with dementia,because it can yield facilitatory effects on cognition and promote brain recovery after a neurological ***,its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of *** study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment,evaluate its effects on synaptic plasticity,and identify the associated *** review essentially focuses on changes in the pathology,amyloidogenesis,and clearance pathways,given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer’s *** mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription,which are closely related to the neural regeneration process,are also ***,we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation,with the aim to highlight future directions for better clinical translations.

关键词： Alzheimer’s disease amyloid deposition apoptotic mechanisms biomarker neural regeneration neurodegeneration repetitive transcranial magnetic stimulation synaptic plasticity

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Single-cell omics: experimental workflow, data analyses and applications

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Science China Life Sciences 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang University Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Frontier Science center for Stem Cells School of Life Sciences and TechnologyTongji University Translational medical center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University research Institute of Intelligent Computing Zhejiang Lab Shanghai research Institute for Intelligent Autonomous Systems center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of Medicine National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang University center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Beijing Institutes of Life Science Chinese Academy of Sciences Peking-Tsinghua center for Life Sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology (CQB)Peking University Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women's HospitalZhejiang University School of Medicine Key Laboratory of Advanced Theory and application in Statistics and Data Science-MOE School of StatisticsEast China Normal University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial sc RNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

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A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

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Computers, Materials & Continua 2023年第7期76卷 827-848页

作者： Junqi Guo Qingyun Xiong Minghui Yang Ziyun Zhao School of artificial intelligence Beijing Normal UniversityBeijing100875China Engineering research center of Intelligent Technology and Educational application Ministry of EducationBeijing100875China

Nowadays,smart wearable devices are used widely in the Social Internet of Things(IoT),which record human physiological data in real *** protect the data privacy of smart devices,researchers pay more attention to federated *** the data leakage problem is somewhat solved,a new challenge has *** federated learning shortens the convergence time,while it has time delay and data heterogeneity *** of the two problems harm the *** overcome these issues,we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity *** scheme improves the Delay Compensated Asynchronous Stochastic Gradient Descent(DC-ASGD)algorithm based on the second-order Taylor expansion as the delay *** adds the FedProx operator to the objective function as the heterogeneity ***,the proposed scheme motivates the federated learning process by adjusting the importance of the participants and the central *** conduct multiple sets of experiments in both conventional and heterogeneous *** experimental results show that our scheme improves the accuracy by about 5%while keeping the complexity *** can find that our scheme converges more smoothly during training and adapts better in heterogeneous environments through numerical *** proposed double-compensation-based federated learning scheme is highly accurate,flexible in terms of participants and smooth the training *** it is deemed suitable for data privacy protection of smart wearable devices.

关键词： Social Internet of Things smart wearable devices data privacy asynchronous federated learning

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Integrating sequence and graph information for enhanced drug-target affinity prediction

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Science China(Information Sciences) 2024年第2期67卷 325-326页

作者： Haohuai HE Guanxing CHEN Calvin Yu-Chian CHEN artificial intelligence medical research center School of Intelligent Systems EngineeringShenzhen Campus of Sun Yat-sen University

Drug discovery is a pivotal discipline involving the identification and development of innovative pharmaceuticals designed to combat a wide array of illnesses. It plays a crucial role in advancing global health outcomes and improving the standard of living for individuals worldwide. However,drug discovery often relies on laborious in vitro experiments,

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application of Fusobacterium nucleatum as a biomarker in gastrointestinal malignancies

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World Journal of Gastrointestinal Oncology 2024年第6期16卷 2271-2283页

作者： Long-Chen Yu Ya-Ping Li Yue-Ming Xin Mai Mao Ya-Xin Pan Yi-Xuan Qu Zheng-Dong Luo Yi Zhang Xin Zhang Department of Clinical Laboratory Qilu Hospital of Shandong UniversityShandong Engineering Research Center of Biomarker and Artificial Intelligence ApplicationJinan 250012Shandong ProvinceChina

The morbidity and mortality of gastrointestinal(GI)malignancies are among the highest in the world,posing a serious threat to human *** of the insidious onset of the cancer,it is difficult for patients to be diagnosed at an early stage,and it rapidly progresses to an advanced stage,resulting in poor treatment and *** nucleatum(***)is a gram-negative,sporefree anaerobic bacterium that primarily colonizes the oral cavity and is implicated in the development of colorectal,esophageal,gastric,and pancreatic cancers via various intricate *** development in novel research suggests that *** may function as a biomarker in GI *** the abundance of *** in stool,saliva,and serum samples of patients may aid in the diagnosis,risk assessment,and prognosis monitoring of GI *** editorial systematically describes the biological roles and mechanisms of *** in GI malignancies focusing on the application of *** as a biomarker in the diagnosis and prognosis of GI malignancies to promote the clinical translation of *** and GI tumors-related research.

关键词： Gastrointestinal malignancies Fusobacterium nucleatum Biomarker Diagnosis Prognosis

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Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

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Computers, Materials & Continua 2024年第5期79卷 2063-2083页

作者： Xiaoqin Ma Jun Wang Wenchang Yu Qinli Zhang School of Big Data and artificial intelligence Chizhou UniversityChizhou247000China Anhui Education Big Data Intelligent Perception and application Engineering research center Chizhou247000China

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable *** available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal *** order to address the aforementioned issues,this paper delves into the study of attribute reduction *** of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute *** newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute ***,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute ***,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy *** effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information ***,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is *** experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction *** comprehensive analysis o

关键词： Hybrid decision information systems fuzzy conditional information entropy attribute reduction fuzzy relationship rough set theory(RST)

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Sememe knowledge computation:a review of recent advances in application and expansion of sememe knowledge bases

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Frontiers of Computer Science 2021年第5期15卷 13-23页

作者： Fanchao QI Ruobing XIE Yuan ZANG Zhiyuan LIU Maosong SUN Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Institute for artificial intelligence Tsinghua UniversityBeijing 100084China Beijing National research center for Information Science and Technology Beijing 100084China Search Product center WeChat Search Application DepartmentTencentBeijing 100080China Beijing Academy of artificial intelligence Beijing 100191China

A sememe is defined as the minimum semantic unit of languages in *** knowledge bases are built by manually annotating sememes for words and *** is the most well-known sememe knowledge *** has been extensively utilized in many natural language processing tasks in the era of statistical natural language processing and proven to be effective and helpful to understanding and using *** the era of deep learning,although data are thought to be of vital importance,there are some studies working on incorporating sememe knowledge bases like HowNet into neural network models to enhance system *** successful attempts have been made in the tasks including word representation learning,language modeling,semantic composition,*** addition,considering the high cost of manual annotation and update for sememe knowledge bases,some work has tried to use machine learning methods to automatically predict sememes for words and phrases to expand sememe knowledge ***,some studies try to extend HowNet to other languages by automatically predicting sememes for words and phrases in a new *** this paper,we summarize recent studies on application and expansion of sememe knowledge bases and point out some future directions of research on sememes.

关键词： natural language process semantics knowledge base sememe HowNet

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