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Assessment of causal effects of physical activity on neurodegenerative diseases:A Mendelian randomization study

Journal of Sport and Health science 2021年第4期10卷 454-461页

作者： Peng-Fei Wu Hui Lu Xiaoting Zhou Xuchen Liang Ruizhuo Li Wan Zhang Danyang Li Kun Xia Center for Medical Genetics&Hunan Provincial Key Laboratory of Medical Genetics School of Life SciencesCentral South UniversityChangsha 410008China Department of Neurology Beth Israel Deaconess Medical Center&Harvard Medical SchoolBostonMA 02115USA Department of Neurology Xuanwu HospitalCapital Medical UniversityBeijing 100053China Department of Neurology Xiangya HospitalCentral South UniversityChangsha 410008China School of Physical Education Henan UniversityKaifeng 475001China School of Medicine South China University of TechnologyGuangzhou 510006China Department of Biology College of Arts&SciencesBoston UniversityBostonMA 02215USA CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China

Background:Physical activity has been hypothesized to play a protective role in neurodegenerative ***,effect estimates previously derived from observational studies were prone to confounding or reverse ***:We performed a two-sample Mendelian randomization(MR)analysis to explore the causal association of accelerometer-measured physical activity with 3 common neurodegenerative diseases:Alzheimer’s disease(AD),Parkinson’s disease(PD),and amyotrophic lateral sclerosis(ALS).We selected genetic instrumental variants reaching genome-wide significance(p<5×10^(-8))from 2 largest meta-analyses of about 91,100 UK Biobank *** statistics for AD,PD,and ALS were retrieved from the up-to-date studies in European ancestry led by the international *** random-effect,inverse-variance weighted MR was employed as the primary method,while MR pleiotropy residual sum and outlier(MR-PRESSO),weighted median,and MR-Egger were implemented as sensitivity *** statistical analyses were performed using the R programming language(Version 3.6.1;R Foundation for Statistical Computing,Vienna,Austria).Results:Primary MR analysis and replication analysis utilized 5 and 8 instrumental variables,which explained 0.2%and 0.4%variance in physical activity,*** each set,one variant at 17q21 was significantly associated with PD,and MR sensitivity analyses indicated them it as an outlier and source of heterogeneity and *** results with the removal of outlier variants suggested odds ratios(ORs)of neurodegenerative diseases per unit increase in objectively measured physical activity were 1.52 for AD(95%confidence interval(95%CI):0.88-2.63,p=0.13)and 3.35 for PD(95%CI:1.32-8.48,p=0.01),while inconsistent results were shown in the replication set for AD(OR=1.06,95%CI:1.01-1.12,p=0.02)and PD(OR=0.99,95%CI:0.88-0.12,p=0.97).Similarly,the beneficial effect of physical activity on ALS(OR=0.51,95%CI:0.29-0.91,p=0.02)was not confirmed in

关键词： Alzheimer’s disease Amyotrophic lateral sclerosis Genetic epidemiology Mendelian randomization Parkinson’s disease Physical activity

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Co-localization of two-color rAAV2-retro confirms the dispersion characteristics of efferent projections of mitral cells in mouse accessory olfactory bulb

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Zoological Research 2020年第2期41卷 148-156页

作者： Ning Zheng Zhi-Zhong Wang Song-Wei Wang Fang-Jia Yang Xu-Tao Zhu Chen Lu Anne Manyande Xiao-Ping Rao Fu-Qiang Xu Center of Brain Science State Key Laboratory of Magnetic Resonance and Atomic and Molecular PhysicsNational Center for Magnetic Resonance in WuhanKey Laboratory of Magnetic Resonance in Biological SystemsWuhan Institute of Physics and MathematicsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhanHubei 430071China University of the Chinese Academy of Sciences Beijing 100049China Department of Automation School of Electrical EngineeringZhengzhou UniversityZhengzhouHenan 450001China School of Life Science Wuhan UniversityWuhanHubei 430072China School of Human and Social Sciences University of West LondonMiddlesex TW89GAUK Divisions of Biomedical Photonics Wuhan National Laboratory for OptoelectronicsWuhanHubei 430074China

The accessory olfactory bulb(AOB), located at the posterior dorsal aspect of the main olfactory bulb(MOB), is the first brain relay of the accessory olfactory system(AOS), which can parallelly detect and process volatile and nonvolatile social chemosignals and mediate different sexual and social behaviors with the main olfactory system(MOS). However, due to its anatomical location and absence of specific markers, there is a lack of research on the internal and external neural circuits of the AOB. This issue was addressed by singlecolor labeling and fluorescent double labeling using retrograde rAAVs injected into the bed nucleus of the stria terminalis(BST), anterior cortical amygdalar area(ACo), medial amygdaloid nucleus(MeA), and posteromedial cortical amygdaloid area(PMCo) in mice. We demonstrated the effectiveness of this AOB projection neuron labeling method and showed that the mitral cells of the AOB exhibited efferent projection dispersion characteristics similar to those of the MOB. Moreover, there were significant differences in the number of neurons projected to different brain regions, which indicated that each mitral cell in the AOB could project to a different number of neurons in different cortices. These results provide a circuitry basis to help understand the mechanism by which pheromone information is encoded and decoded in the AOS.

关键词： Accessory olfactory bulb Efferent projections Retrograde rAAVs Projection neuron labeling Dispersion characteristics Circuitry basis

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Glutathione-capped quantum dots for plasma membrane labeling and membrane potential imaging

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Nano Research 2019年第6期12卷 1321-1326页

作者： Guangcun Chen Yejun Zhang Zhao Peng Dehua Huang Chunyan Li Qiangbin Wang CAS Key Laboratory of Nano-Bio Interface Division of Nanobiomedicine and i-LabCAS Center for Excellence in Brain ScienceSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China School of Nano Technology and Nano Bionics University of Science and Technology of ChinaHefei 230026China College of Materials Sciences and Opto-Electronic Technology University of Chinese Academy of SciencesBeijing 100049China

The plasma membrane of cells is a crucial biological membrane that involved in a variety of cellular processes including cell signaling transduction through membrane electrical ***,monitoring membrane electrical activity using fluorescence imaging has attracted numerous attentions for its potential applications in evaluating how the nervous system ***,the development of ideal fluorescent voltage-sensitive probes with both high membrane labeling efficiency and voltage sensitivity is still retain a big ***,glutathionecapped CdSe@ZnS quantum dots (CdSe@ZnS-GSH QDs) with a size of 2.5 nm and an emission peak at 520 nm are synthesized using a facile ligand exchange method for plasma membrane labeling and membrane potential *** as-synthesized CdSe@ZnS-GSH QDs can effectively label cell membrane at neutral pH within 30 min and exhibit excellent optical stability in continuous imaging for up to 60 *** the test concentration up to 200 nM,CdSe@ZnS-GSH QDs show high biocompatibility to cells and do not affect cell proliferation,disturb cell membrane integrity or cause apoptosis and necrosis of ***,a two-component voltage sensor strategy based on fluorescence resonance energy transfer (FRET) between CdSe@ZnS-GSH QDs and the dipicrylamine (DPA) is successfully developed to monitor the membrane potential by the fluorescence of CdSe@ZnS-GSH *** study offers a facile strategy for labeling plasma membrane and monitoring the membrane potential of cells and will hold great potential in the research of signaling within intact neuronal circuits.

关键词： quantum dots membrane labeling membrane potential imaging fluorescence imaging neuron

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SYNAPSE: An international roadmap to large brain imaging

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Physics Reports 2023年第1期999卷 1-60页

作者： Stampfl, Anton P.J. Liu, Zhongdong Hu, Jun Sawada, Kei Takano, H. Kohmura, Yoshiki Ishikawa, Tetsuya Lim, Jae-Hong Je, Jung-Ho Low, Chian-Ming Teo, Alvin Tok, Eng Soon Tan, Tin Wee Ban, Kenneth Libedinsky, Camilo Tan, Francis Chee Kuan Chen, Kuan-Peng Yang, An-Cheng Chuang, Chao-Chun Chen, Nan-Yow Shih, Chi-Tin Lee, Ting-Kuo Yang, De-Nian Lai, Hsu-Chao Shuai, Hong-Han Cheng, Chang-Chieh Ching, Yu-Tai Li, Chia-Wei Charng, Ching-Che Lo, Chung-Chuan Chiang, Ann-Shyn Recur, Benoit Petibois, Cyril Cheng, Chia-Liang Chen, Hsiang-Hsin Yang, Shun-Min Hwu, Yeukuang Rojviriya, Catleya Rugmai, Supagorn Rujirawat, Saroj Margaritondo, Giorgio Australian Nuclear Science and Technology Organization Lucas Heights 2234 NSW Australia Henan university of Technology Zhengzhou China Shanghai Institute of Applied Physics Chinese Academy of Science Shanghai China RIKEN SPring-8 Center Hyogo 679-5148 Japan Pohang Accelerator Laboratory Pohang University of Science and Technology Pohang Gyeongbuk 37673 South Korea Department of Materials Science and Engineering Pohang University of Science and Technology Gyeongbuk Pohang 37673 South Korea Department of Pharmacology Department of Anaesthesia and Healthy Longevity Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore School of Chemical and Life Sciences Nanyang Polytechnic Singapore eMaGIC-Lab Department of Physics National University of Singapore Singapore National Supercomputing Center Singapore Department of Psychology The N1 Institute for Health National University of Singapore Singapore Institute of Molecular and Cell Biology A*STAR Singapore Department of Anaesthesia National University Hospital National University Health System Singapore National Center for High-Performance Computing Hsinchu Taiwan Department of Physics Tunghai University Taichung Taiwan Department of Physics National Tsing Hua University Hsinchu Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Information Technology Service Center National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Life Science National Tsing Hua University Hsinchu Taiwan Institute of Systems Neuroscience and Brain Research Center National Tsing Hua University Hsinchu Taiwan Institute of Physics Academia Sinica Taipei Taiwan Department of Physics National Dong Hwa University

Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been collaborating in a major project called “SYNAPSE” (Synchrotrons for Neuroscience: an Asia-Pacific Scientific Enterprise). They use x-ray imaging to attack in a coordinated fashion one of the major issues in modern science: the structure of animal and human brains, including neurons and connections. The objective is to develop Google-like maps also including detailed structural and functional information for selected regions of interest. The sheer mass of data needed for the objective poses huge problems for the acquisition, processing, storage and use of images. In order to complete the task within a reasonable time, the key element of the SYNAPSE strategy is the parallel and coordinated work of several facilities on the same specimens. This article reviews different aspects of the enterprise, including the foundations of synchrotron radiation, coherence and of its role in advanced imaging, electron accelerators, x-ray optics and detectors. This will provide the foundation for an extensive presentation of the different components of SYNAPSE, with an overview of results already obtained within the consortium. © 2022

关键词： brain mapping Phase contrast Radiology Supercomputing Synchrotron X-rays

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Atlas of Proteomic signatures of brain structure and its links to brain disorders

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Nature communications 2025年第1期16卷 5092页

作者： Peng Ren Xiao-He Hou Zeyu Li Jia You Yuzhu Li Wei Zhang Weikang Gong Bei Zhang Bangsheng Wu Linbo Wang Chun Shen Yujie Zhao Qing Ma Jujiao Kang Yuchao Jiang Neil Roberts Fan Xu Yong He Jin-Tai Yu Meiyun Wang Wei Cheng Institute of Science and Technology for Brain-Inspired Intelligence State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan University Shanghai China. Department of Neurology Huashan Hospital Fudan University Shanghai China. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) Ministry of Education Shanghai PR China. Department of Neurology Qingdao Hospital University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital) Qingdao China. School of Data Science Fudan University Shanghai China. Centre for Reproductive Health (CRH) Institute for Regeneration and Repair (IRR) University of Edinburgh 4-5 Little France Drive Edinburgh EH15 4UU UK. Institute of Mechanics and Computational Engineering Department of Aeronautics and Astronautics Fudan University Shanghai China. State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing China. Beijing Key Laboratory of Brain Imaging and Connectomics Beijing Normal University Beijing China. Institute of Science and Technology for Brain-Inspired Intelligence State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan University Shanghai China. jintai_yu@***. Department of Neurology Huashan Hospital Fudan University Shanghai China. jintai_yu@***. Department of Medical Imaging Henan Provincial People's Hospital & Zhengzhou University People's Hospital Zhengzhou China. mywang@***. Institute of Science and Technology for Brain-Inspired Intelligence State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan University Shanghai China. wcheng@***. Department of Neurology Huashan Hospital Fudan University Shanghai China. wcheng@***. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) Ministry of Education Shanghai PR China. wcheng@fudan.edu.cn. Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspi

Individual variation in brain structure influences deterioration due to disease and comprehensive profiling of the associated proteomic signature advances mechanistic understanding. Here, using data from 4997 UK Biobank participants, we analyzed the associations between 2920 plasma proteins and 272 neuroimaging-derived brain structure measures. We identified 5358 associations between 1143 proteins and 256 brain structure measures, with NCAN and LEP proteins showing the most associations. Functional enrichment implicated these proteins in neurogenesis, immune/apoptotic processes and neurons. Furthermore, bidirectional Mendelian randomization revealed 33 associations between 32 proteins and 23 brain structure measures, and 21 associations between nine brain structure associated proteins and ten brain disorders. Moreover, the significant associations between the identified proteins and mental health were mediated by brain volume and surface area. In summary, this study generates a comprehensive atlas mapping the patterns of association between proteome and brain structure, highlighting their potential value for studying brain disorders.

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Diffusion Adaptive Filtering Algorithm Based on the Fair Cost Function

Research Square

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Research Square 2021年

作者： Guan, Sihai Cheng, Qing Zhao, Yong Biswal, Bharat College of Electronic and Information Southwest Minzu University China Key Laboratory of Electronic and Information Engineering State Ethnic Affairs Commission China Sichuan Vocational College of Finance and Economics Chengdu China School of Mechanical and Power Engineering Henan Polytechnic University Jiaozuo China The Clinical Hospital of Chengdu Brain Science Institute MOE Key Laboratory for Neuroinformation Center for Information in Medicine School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China NewarkNJ United States

To better perform distributed estimation, this paper, by combining the Fair cost function and adapt-then-combine scheme at all distributed network nodes, a novel diffusion adaptive estimation algorithm is proposed from an M-estimator perspective, which is called the diffusion Fair (DFair) adaptive filtering algorithm. The stability of the mean estimation error and the computational complexity of the DFair are theoretically analyzed. Compared with the RDLMS, DNLMM, DGCLD, and DPLMS algorithms, the simulation experiment results show that the DFair algorithm is more robust to input signals and impulsive interference. In conclusion, Theoretical analysis and simulation results show that the DFair algorithm performs better when estimating an unknown linear system in the changeable impulsive interference environments. © 2021, CC BY.

关键词： Cost functions

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Learning across multi-stimulus enhances target recognition methods in SSVEP-based BCIs

Learning across multi-stimulus enhances target recognition m...

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作者： Wong, Chi Man Wan, Feng Wang, Boyu Wang, Ze Nan, Wenya Lao, Ka Fai Mak, Peng Un Vai, Mang I. Rosa, Agostinho Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China Centre for Cognitive and Brain Sciences Institute of Collaborative Innovation University of Macau China Department of Computer Science University of Western Ontario LondonON Canada Department of Psychology Shanghai Normal University Shanghai China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China LaSEEB-ISR-LARSyS Universidade de Lisboa Lisbon Portugal

Objective. Latest target recognition methods that are equipped with learning from the subject's calibration data, represented by the extended canonical correlation analysis (eCCA) and the ensemble task-related component analysis (eTRCA), can achieve extra high performance in the steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), however their performance deteriorate drastically if the calibration trials are insufficient. This paper develops a new scheme to learn from limited calibration data. Approach. A learning across multiple stimuli scheme is proposed for the target recognition methods, which applies to learning the data corresponding to not only the target stimulus but also the other stimuli. The resulting optimization problems can be simplified and solved utilizing the prior knowledge and properties of SSVEPs across different stimuli. With the new learning scheme, the eCCA and the eTRCA can be extended to the multi-stimulus eCCA (ms-eCCA) and the multi-stimulus eTRCA (ms-eTRCA), respectively, as well as a combination of them (i.e. ms-eCCA+ms-eTRCA) that incorporates their merits. Main results. Evaluation and comparison using an SSVEP-BCI benchmark dataset with 35 subjects show that the ms-eCCA (or ms-eTRCA) performs significantly better than the eCCA (or eTRCA) method while the ms-eCCA+ms-eTRCA performs the best. With the learning across stimuli scheme, the existing target recognition methods can be further improved in terms of the target recognition performance and the ability against insufficient calibration. Significance. A new learning scheme is proposed towards the efficient use of the calibration data, providing enhanced performance and saving calibration time in the SSVEP-based BCIs. © 2020 IOP Publishing Ltd.

关键词： brain computer interface

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Signal Detection,Processing and Challenges of Non-invasive brain-computer interface technology

Signal Detection,Processing and Challenges of Non-invasive B...

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2019中国智能自动化大会(CIAC 2019)

作者： Xiaoyuan Li Feng Chen Yaohui Jia Xinyu Liu School of Electrical Engineering Zhengzhou University Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou University School of Intelligent Manufacturing Huanghuai University China Shipping Heavy Industry 713 Research Institute

Non-invasive brain-computer interface(BCI) technology is becoming more and more popular in current BCI application study due to its safety,non-invasive and low *** main problem of non-invasive BCI technology is that the spatial resolution of signal is low and it is easy to be drowned by ***,this paper reviews the key technologies and the existing challenges of non-invasive BCI technology from the aspect of signal detection and processing,and discusses its future application ***,it is still a great challenge for non-invasive BCI technology to become the mainstream in the future.

关键词： brain-computer interface Non-invasive BCI technology Signal detection Pattern recognition

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Cognitive deficits and Alzheimer-like neuropathological impairments during adolescence in a rat model of type 2 diabetes mellitus

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Neural Regeneration Research 2018年第11期13卷 1995-2004页

作者： Li Jin Yi-Pei Li Qiong Feng Li Ren Fang Wang Guo-Jia Bo Li Wang Department of Pathophysiology Henan Medical College Henan Key Laboratory of Degenerative Brain Disease Henan Medical College Department of Pathophysiology School of Basic Medicine and the Collaborative Innovation Center for Brain ScienceKey Laboratory of Ministry of Education of China for Neurological DisordersTongji Medical CollegeHuazhong University of Science and Technology Department of Pathology Wuhan Children's Hospital

Numerous studies have shown that many patients who suffer from type 2 diabetes mellitus exhibit cognitive dysfunction and neuronal synaptic impairments. Therefore, growing evidence suggests that type 2 diabetes mellitus has a close relationship with occurrence and progression of neurodegeneration and neural impairment in Alzheimer＇s disease. However, the relationship between metabolic disorders caused by type 2 diabetes mellitus and neurodegeneration and neural impairments in Alzheimer＇s disease is still not fully determined. Thus, in this study, we replicated a type 2 diabetic animal model by subcutaneous injection of newborn Sprague-Dawley rats with monosodium glutamate during the neonatal period. At 3 months old, the Barnes maze assay was performed to evaluate spatial memory function. Microelectrodes were used to measure electrophysiological function in the hippocampal CA1 region. Western blot assay was used to determine expression levels of glutamate ionotropic receptor NMDA type subunit 2 A（GluN2A） and GluN2B in the hippocampus. Enzyme-linked immunosorbent assay was used to determine levels of interleukin-1β, tumor necrosis factor α, and interleukin-6 in the hippocampus and cerebral cortex, as well as hippocampal amyloid beta（Aβ）1-40 and Aβ_（1-42） levels. Our results showed that in the rat model of type 2 diabetes mellitus caused by monosodium glutamate exposure during the neonatal period, latency was prolonged and the number of errors increased in the Barnes maze. Further, latency was increased and time in the escape platform quadrant shortened. Number of times crossing the platform was also reduced in the Morris water maze. After high frequency stimulation of the hippocampus, synaptic transmission was inhibited, expression of GluN2A and GluN2B were decreased in the hippocampus, expression of interleukin 1β, interleukin 6, and tumor necrosis factor α was increased in the hippocampus and cortex, and levels of Aβ_（1-40） and Aβ_（1-42） were increased in the hippoc

关键词： nerve regeneration type 2 diabetes mellitus Alzheimer＇s disease monosodium glutamate neonatal period cognitive deficits hyperglycemia hyperinsulinemia insulin resistance neural regeneration

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Quantum Mechanical Tunnelling Probes with Redox Cycling for Ultra-Sensitive Detection of Biomolecules

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Angewandte Chemie 2025年

作者： Long Yi Tao Jiang Dr. Ren Ren Prof. Ji Cao Prof. Joshua B. Edel Prof. Aleksandar P. Ivanov Prof. Longhua Tang State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and Engineering Zhejiang University Hangzhou 310027 China Nanhu Brain-Computer Interface Institute Second Affiliated Hospital School of Medicine Hangzhou Zhejiang 311100 China Department of Chemistry Molecular Science Research Hub Imperial College London White City Campus 82 Wood Lane London W12 0BZ UK Institute of Pharmacology and Toxicology Zhejiang Province Key Laboratory of Anti-Cancer Drug Research College of Pharmaceutical Sciences Zhejiang University Hangzhou China

Quantum mechanical tunnelling sensors (QMTs) have emerged as a promising technology for next-generation single-molecule detection. Furthermore, QMT sensors can be combined with redox species resulting in repeated oxidation and reduction (redox cycling).. We developed robust QMT probes with electrode gap distances below 2 nm. Using the generator-collector (GC) mode, we verified that redox cycling of the ferrocyanide/ferricyanide (Fe(CN) 6 3−/4− ) couple occurs both in the tunnelling regime and on the electrode surface. Our findings indicated that the current enhancement is affected by both the gap distance and surface modifications of the probes. These QMT probes exhibited remarkable sensitivity, capable of detecting Fe(CN) 6 3−/4− concentrations down to sub-picomolar levels. Utilising this ability to modulate redox reactions, we adapted the QMT probes to serve as electrochemical sensors for detecting viral proteins. By modifying the electrode surfaces, our functionalised QMT probes achieved sub-pM detection limits with high selectivity in biofluids such as nasopharyngeal secretions. These findings highlight the potential of QMT probes to develop into a new class of electrochemical tunnelling sensors, offering significant advancements in biomedical diagnostics.

关键词： quantum tunnelling sensors redox cycling reaction single-molecular detection biosensor

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