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Dysfunction of synaptic endocytic trafficking in Parkinson's disease

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Neural Regeneration Research 2024年第12期19卷 2649-2660页

作者： Xin Yi ng Mian Cao Programme in Neuroscience and Behavioural Disorders Duke-NUS Medical SchoolSingaporeSingapore Department of Physiology National University of SingaporeSingaporeSingapore

Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive.Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease.Notably,several of these genes are linked to the synaptic vesicle recycling process,particularly the clathrinmediated endocytosis pathway.This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease,followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a"dying back"mechanism.Recently,several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized.These models faithfully recapitulate certain Parkinson's disease-like features at the animal,circuit,and cellular levels,and exhibit defects in synaptic membrane trafficking,further supporting the findings from human genetics and clinical studies.In this review,we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins:auxilin(DNAJC6/PARK19)and synaptojanin 1(SYNJ1/PARK20).The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect.Subsequently,we will delve into the involvement of several clathrin-mediated endocytosis-related proteins(GAK,endophilin A1,SAC2/INPP5 F,synaptotagmin-11),identified as Parkinson's disease risk factors through genome-wide association studies,in Parkinson's disease pathogenesis.We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins(alpha-synuclein(PARK1/4),Parkin(PARK2),and LRRK2(PARK8))in synaptic endocytic trafficking.Additionall

关键词： autophagy auxilin/PARK19 clathrin-mediated endocytosis dopamine neurons neurodegeneration nigrostriatal pathway Parkinson's disease synaptic vesicle recycling synaptojanin1/PARK20

Stability and Generalization of Hypergraph Collaborative Networks

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Machine Intelligence Research 2024年第1期21卷 184-196页

作者： Michael K.ng Hanrui Wu Andy Yip Institute of Data Science The University of Hong KongHong KongChina Department of Mathematics The University of Hong KongHong KongChina College of Information Science and Technology Jinan UniversityGuangzhou 510006China

Graph neural networks have been shown to be very effective in utilizing pairwise relationships across samples.Recently,there have been several successful proposals to generalize graph neural networks to hypergraph neural networks to exploit more com-plex relationships.In particular,the hypergraph collaborative networks yield superior results compared to other hypergraph neural net-works for various semi-supervised learning tasks.The collaborative network can provide high quality vertex embeddings and hyperedge embeddings together by formulating them as a joint optimization problem and by using their consistency in reconstructing the given hy-pergraph.In this paper,we aim to establish the algorithmic stability of the core layer of the collaborative network and provide generaliz--ation guarantees.The analysis sheds light on the design of hypergraph filters in collaborative networks,for instance,how the data and hypergraph filters should be scaled to achieve uniform stability of the learning process.Some experimental results on real-world datasets are presented to illustrate the theory.

关键词： Hypergraphs vertices hyperedges collaborative networks graph convolutional neural networks(CNNs) stability generalization guarantees

Perspectives in human brain plasticity sparked by glioma invasion:from intraoperative(re)mappings to neural reconfigurations

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Neural Regeneration Research 2024年第5期19卷 947-948页

作者： Sam ng Hugues Duffau Guillaume Herbet Department of Neurosurgery Gui de Chauliac HospitalMontpellier University Medical CenterMontpellierFrance Institute of Functional Genomics University of MontpellierCNRSINSERMMontpellierFrance Praxiling Laboratory UMR5267CNRSPaul Valéry-Montpellier 3 UniversityMontpellierFrance

Exploring the aptitude of the human brain to compensate functional consequences of a lesion damaging its structural architecture is a key challenge to improve patient care in various neurological diseases,to optimize neuroscientifically-informed strategies of postlesional rehabilitation,and ultimately to develop innovative neuro-regenerative therapies.The term‘plasticity’,initially referring to the intrinsic propensity of neurons to modulate their synaptic transmission in a learning situation,was progressively transposed to brain injury research and clinical neurosciences.Indeed,in the event of brain damage,adaptive mechanisms of compensation allow a partial reshaping of the structure and activities of the central nervous system,thus permitting to some extent the maintenance of brain functions.

关键词： plasticity figuration consequences

Defined hydrogels for spinal cord organoids:challenges and potential applications

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Neural Regeneration Research 2024年第11期19卷 2329-2330页

作者： Wai Hon Chooi Yuewen Wu Shi-Yan ng Institute of Molecular and Cell Biology(IMCB) Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore Department of Physiology Yong Loo Lin School of MedicineNational University of Singapore(NUS)SingaporeSingapore

Organoids of the central nervous system,primarily derived from pluripotent stem cells or neural stem cells,are three-dimensional tissue cultures with self-organizing properties.When exposed to the right combinations of signals,they differentiate into a 3D tissue consisting of complex cytoarchitecture and native cell types,including various neuron subtypes and glial cells.These features closely mimic native tissues,making them invaluable for developmental studies and disease modeling.In recent years,spinal cord organoids(SCOs)have been developed to investigate spinal cord development,injuries,and various neurological disorders.As an integral part of the central nervous system,SCOs play a vital role and serve as a site for studying both neurodevelopment and neurodegenerative diseases.

关键词： properties injuries primarily

Mg/MgO interfaces as efficient hydrogen evolution cathodes causing accelerated corrosion of additive manufactured Mg alloys:A DFT analysis

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Journal of Magnesium and Alloys 2024年第1期12卷 110-119页

作者： Man-Fai ng Kai Xiang Kuah Teck Leong Tan Daniel John Blackwood Department of Materials Science&Engineering National University of Singapore9 Engineering Drive 1Singapore 117575Republic of Singapore Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A∗STAR)1 Fusionopolis Way#16-16 ConnexisSingapore 138632Republic of Singapore

The corrosion rates of additive-manufactured Mg alloys are higher than their as-cast counterparts,possibly due to increased kinetics for the hydrogen evolution reaction on secondary phases,which may include oxide inclusions.Scanning Kelvin Probe Force Microscopy demonstrated that MgO inclusions could act as cathodes for Mg corrosion,but their low conductivity likely precludes this.However,the density of state calculations through density functional theory using hybrid HSE06 functional revealed overlapping electronic states at the Mg/MgO interface,which facilitates electron transfers and participates in redox reactions.Subsequent determination of the hydrogen absorption energy at the Mg/MgO interface reveals it to be an excellent catalytic site,with HER being found to be a factor of 23x more efficient at the interface than on metallic Mg.The results not only support the plausibility of the Mg/MgO interface being an effective cathode to the adjacent anodic Mg matrix during corrosion but also contribute to the understanding of the enhanced cathodic activities observed during the anodic dissolution of magnesium.

关键词： Magnesium Magnesium oxide Interface Hydrogen evolution DFT

Advances of machine learning in materials science: Ideas and techniques

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Frontiers of physics 2024年第1期19卷 155-194页

作者： Sue Sin Chong Yi Sheng ng Hui-Qiong Wang Jin-Cheng Zheng Department of New Energy Science and Engineering Xiamen University MalaysiaSepang 43900Malaysia Engineering Research Center of Micro-nano Optoelectronic Materials and Devices Ministry of EducationFujian Key Laboratory of Semiconductor Materials and ApplicationsCI Center for OSEDand Department of PhysicsXiamen UniversityXiamen 361005China

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field, in both the computational and experimental departments. With the advent of machine learning-based techniques, there has been a paradigm shift: materials can now be screened quickly using ML models and even generated based on materials with similar properties;ML has also quietly infiltrated many sub-disciplinary under materials science. However, ML remains relatively new to the field and is expanding its wing quickly. There are a plethora of readily-available big data architectures and abundance of ML models and software;The call to integrate all these elements in a comprehensive research procedure is becoming an important direction of material science research. In this review, we attempt to provide an introduction and reference of ML to materials scientists, covering as much as possible the commonly used methods and applications, and discussing the future possibilities.

关键词： machine learning materials science

FE65:a hub for neurodevelopment

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Neural Regeneration Research 2024年第9期19卷 1883-1884页

作者： Yuqi Zhai Laura Lok-Haang ng Dennis Dik-Long Chau Kwok-Fai Lau School of Life Sciences Faculty of ScienceThe Chinese University of Hong KongHong Kong Special Administrative RegionChina

FE65,initially identified as a binding partner of amyloid precursor protein(APP),is an adaptor protein enriched in the brain and regulated during development.FE65 belongs to the FE65 protein family.This family is comp... 详细信息

关键词： family development partner

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

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Asian Journal of Andrology 2024年第1期26卷 20-24页

作者： John Shung-Lai Leung Wai-Kit Ma Brian Sze-Ho Ho Stacia Tsun-Tsun Chun Rong Na Yongle Zhan Chi-Yuen ng Chi-Ho Ip Ada Tsui-Lin ng Yiu-Chung Lam Division of Urology Department of SurgeryQueen Mary HospitalUniversity of Hong KongHong KongChina Division of Urology Department of SurgeryPrincess Margaret HospitalHongKongChina

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging.Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers(Queen Mary Hospital and Princess Margaret Hospital,Hong Kong,China)between January 2017 and June 2022 were included.Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing.Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed.Out of the 747 patients,47.3%had Prostate Imaging Reporting and Data System score 3 lesions only.The detection rate of clinically significant prostate cancer in this group was 15.0%.The cancer detection rates of clinically significant prostate cancer had statistically significant differences:5.3%in prostate health indexng the patients,26.9%could have avoided a biopsy with a prostate health indexng clinically significant prostate cancer.Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions.Biopsies could be avoided in patients with low prostate health index,with a small risk of missing clinically significant prostate cancer.

关键词： biopsy fusion biopsy magnetic resonance imaging prostate cancer prostate health index

Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection

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Machine Intelligence Research 2024年第1期21卷 89-103页

作者： Chaojie Wu Mingyang Li Ying Gao Xinyan Xie Wing W.Y.ng Ahmad Musyafa School of Computer Science and Engineering South China University of TechnologyGuangzhou 511442China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People's HospitalGuangzhou 510180China

The problem of art forgery and infringement is becoming increasingly prominent,since diverse self-media contents with all kinds of art pieces are released on the Internet every day.For art paintings,object detection and localization provide an efficient and ef-fective means of art authentication and copyright protection.However,the acquisition of a precise detector requires large amounts of ex-pensive pixel-level annotations.To alleviate this,we propose a novel weakly supervised object localization(WSOL)with background su-perposition erasing(BSE),which recognizes objects with inexpensive image-level labels.First,integrated adversarial erasing(IAE)for vanilla convolutional neural network(CNN)dropouts the most discriminative region by leveraging high-level semantic information.Second,a background suppression module(BSM)limits the activation area of the IAE to the object region through a self-guidance mechanism.Finally,in the inference phase,we utilize the refined importance map(RIM)of middle features to obtain class-agnostic loc-alization results.Extensive experiments are conducted on paintings,CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.

关键词： Weakly supervised object localization erasing method deep learning computer vision art authentication and copyright protection