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Connecting neurodevelopment to neurodegeneration:a spotlight on the role of kinesin superfamily protein 2A(KIF2A)

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Neural Regeneration Research 2024年第2期19卷 375-379页

作者： Nuria Ruiz-Reig Janne Hakanen Fadel Tissir Universitécatholique de Louvain Institute of neuroscienceBrusselsBelgium College of Health and Life Sciences Hamad Bin Khalifa University(HBKU)DohaQatar

Microtubules play a central role in cytoskeletal changes during neuronal development and maintenance.Microtubule dynamics is essential to polarity and shape transitions underlying neural cell division,differentiation,motility,and maturation.Kinesin superfamily protein 2A is a member of human kinesin 13 gene family of proteins that depolymerize and destabilize microtubules.In dividing cells,kinesin superfamily protein 2A is involved in mitotic progression,spindle assembly,and chromosome segregation.In postmitotic neurons,it is required for axon/dendrite specification and extension,neuronal migration,connectivity,and survival.Humans with kinesin superfamily protein 2A mutations suffer from a variety of malformations of cortical development,epilepsy,autism spectrum disorder,and neurodegeneration.In this review,we discuss how kinesin superfamily protein 2A regulates neuronal development and function,and how its deregulation causes neurodevelopmental and neurological disorders.

关键词： brain disorders cortical malformations kinesin microtubules neurodegeneration neurodevelopment

Multimodal Fusion of brain Imaging Data: Methods and Applications

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Machine Intelligence Research 2024年第1期21卷 136-152页

作者： Na Luo Weiyang Shi Zhengyi Yang Ming Song Tianzi Jiang brainnetome Center and National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Excellence in brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Augmented Intelligence Zhejiang LaboratoryHangzhou 311100China

Neuroimaging data typically include multiple modalities,such as structural or functional magnetic resonance imaging,dif-fusion tensor imaging,and positron emission tomography,which provide multiple views for observing and analyzing the brain.To lever-age the complementary representations of different modalities,multimodal fusion is consequently needed to dig out both inter-modality and intra-modality information.With the exploited rich information,it is becoming popular to combine multiple modality data to ex-plore the structural and functional characteristics of the brain in both health and disease status.In this paper,we first review a wide spectrum of advanced machine learning methodologies for fusing multimodal brain imaging data,broadly categorized into unsupervised and supervised learning strategies.Followed by this,some representative applications are discussed,including how they help to under-stand the brain arealization,how they improve the prediction of behavioral phenotypes and brain aging,and how they accelerate the biomarker exploration of brain diseases.Finally,we discuss some exciting emerging trends and important future directions.Collectively,we intend to offer a comprehensive overview of brain imaging fusion methods and their successful applications,along with the chal-lenges imposed by multi-scale and big data,which arises an urgent demand on developing new models and platforms.

关键词： Multimodal fusion supervised learning unsupervised learning brain atlas cognition brain disorders

The therapeutic prospects and challenges of human neural stem cells for the treatment of Alzheimer’s Disease

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Cell Regeneration 2022年第1期11卷 293-302页

作者： Chunmei Yue Su Feng Yingying Chen Naihe Jing State Key Laboratory of Cell Biology CAS Center for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of SciencesUniversity of Chinese Academy of SciencesShanghai 200031China Department of Biological Sciences School of ScienceXi’an Jiaotong-Liverpool UniversitySuzhou 215000China Bioland Laboratory/Guangzhou Laboratory Guangzhou 510005China CAS Key Laboratory of Regenerative Biology Guangdong Provincial Key Laboratory of Stem Cell and Regenerative MedicineGuangzhou Institutes of Biomedicine and HealthChinese Academy of SciencesGuangzhou 510530China School of Life Science and Technology ShanghaiTech UniversityShanghai 201210China

Alzheimer’s disease(AD)is a multifactorial neurodegenerative disorder associated with aging.Due to its insidious onset,protracted progression,and unclear pathogenesis,it is considered one of the most obscure and intractable brain disorders,and currently,there are no effective therapies for it.Convincing evidence indicates that the irreversible decline of cognitive abilities in patients coincides with the deterioration and degeneration of neurons and synapses in the AD brain.Human neural stem cells(NSCs)hold the potential to functionally replace lost neurons,reinforce impaired synaptic networks,and repair the damaged AD brain.They have therefore received extensive attention as a possible source of donor cells for cellular replacement therapies for AD.Here,we review the progress in NSC-based transplantation studies in animal models of AD and assess the therapeutic advantages and challenges of human NSCs as donor cells.We then formulate a promising transplantation approach for the treatment of human AD,which would help to explore the disease-modifying cellular therapeutic strategy for the treatment of human AD.

关键词： brain disorders Alzheimer’s disease Stem cell-based replacement therapy Neural subtype-specific transplantation brain region-specific transplantation Cognitive ability

Sensor-Based Gait Analysis for Parkinson’s Disease Prediction

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Intelligent Automation & Soft Computing 2023年第5期36卷 2085-2097页

作者： Sathya Bama B Bevish Jinila Y Sathyabama Institute of Science and Technology Chennai600119Tamil NaduIndia

Parkinson’s disease is identiﬁed as one of the key neurodegenerative disorders occurring due to the damages present in the central nervous system.The cause of such brain damage seems to be fully explained in many research studies,but the understanding of its functionality remains to be impractical.Speciﬁcally,the development of a quantitative disease prediction model has evolved in recent decades.Moreover,accelerometer sensor-based gait analysis is accepted as an important tool for recognizing the walking behavior of the patients during the early prediction and diagnosis of Parkinson’s disease.This type of minimal infrastructure equipment helps in analyzing the Parkinson’s gait properties without affecting the common behavioral patterns during the clinical practices.Therefore,the Accelerometer Sensor-based Parkinson’s Disease Identi-ﬁcation System(ASPDIS)is introduced with a kernel-based support vector machine classiﬁer model to make an early prediction of the disease.consequently,the proposed classiﬁer can easily predict various severity levels of Parkinson’s disease from the sensor data.The performance of the proposed classiﬁer is com-pared against the existing models such as random forest,decision tree,and k-near-est neighbor classiﬁers respectively.As per the experimental observation,the proposed classiﬁer has more capability to differentiate Parkinson’s from non-Parkinson patients depending upon the severity levels.Also,it is found that the model has outperformed the existing classiﬁers concerning prediction time and accuracy respectively.

关键词： brain disorders gait analysis Parkinson’s disease support vector machine classiﬁer healthcare system

An update on stem cell therapy for neurological disorders: cell death pathways as therapeutic targets

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Chinese Neurosurgical Journal 2017年第2期3卷 98-105页

作者： Sydney Corey Shaila Ghanekar Jake Sokol John H.Zhang Cesar V.Borlongan Center of Excellence for Aging & brain Repair Department of Neurosurgery and Brain Repair University of South Florida College of Medicine 12901 Bruce B.Downs Blvd Tampa Florida 33612 USA Departments of Anesthesiology Neurosurgery Neurology and Physiology Loma Linda University Medical Center 11234 Anderson St Loma Linda CA 92354 USA

Here, we compiled ten papers detailing recent strides in the field of stem cell therapy, which address critical issues relevant to pursuing this experimental treatment for clinical applications in brain disorders. Topics include efficacy, safety, and mechanism of action underlying cell therapy, emerging technologies and combination pharmacotherapies with cell transplantation directed at improving the functional outcomes, and evaluation of key translational components of advancing novel therapeutics to the clinic, including the need for vis-à-vis comparisons with the gold standard of treatment post-injury (i.e., physical rehabilitation). A bioethics paper is also incorporated here to further appreciate the current status of cell therapy in the community setting. The overall goal of this special volume is to provoke a meaningful assessment of the lessons we have learned in recent years and to use such knowledge to carefully translate safe and effective applications of cell therapy, and its mechanism of action for the treatment of neurological disorders.

关键词： brain disorders Cell transplantation Safety Efficacy Mechanism Clinical trials Bioethics Biomaterials

brain asymmetry: a novel perspective on hemispheric network

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brain Science Advances 2023年第2期9卷 56-77页

作者： Bin Wang Lan Yang Wenjie Yan Weichao An Jie Xiang Dandan Li College of Computer Science and Technology Taiyuan University of TechnologyJinzhong 030600ShanxiChina Graduate School of Interdisciplinary Science and Engineering in Health Systems Okayama UniversityOkayamaJapan

brain asymmetry,involving structural and functional differencesbetween the two hemispheres,is a major organizational principle ofthe human brain.The structural and functional connectivity withineach hemisphere defines the hemispheric network or connectome.Elucidating left-right differences of the hemispheric network providesopportunities for brain asymmetry exploration.This review examinesthe asymmetry in the hemispheric white matter and functionalnetwork to assess health and brain disorders.In this article,the brain asymmetry in structural and functional connectivity includingnetwork topologies of healthy individuals,involving brain cognitivesystems and the development trend,is highlighted.Moreover,theabnormal asymmetry of the hemispheric network related to cognition changes in brain disorders,such as Alzheimer’s disease,schizophrenia,autism spectrum disorder,attention deficit hyperactivity disorder,and bipolar disorder,is presented.This review suggests that thehemispheric network is highly conserved for measuring human brain asymmetries and has potential in the study of the cognitivesystem and brain disorders.

关键词： hemispheric network brain asymmetry graph theory cognition system brain disorders