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State Classification via a Random-Walk-Based Quantum Neural Network

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Chinese Physics Letters 2022年第5期39卷 4-9页

作者：王露吉林嘉懿吴盛俊 institute for brain sciences and kuang yaming honors school Nanjing UniversityNanjing 210023China school of Physics Nanjing UniversityNanjing 210093China

In quantum information technology,crucial information is regularly encoded in different quantum states.To extract information,the identification of one state from the others is inevitable.However,if the states are nonorthogonal and unknown,this task will become awesomely tricky,especially when our resources are also limited.Here,we introduce the quantum stochastic neural network(QSNN),and show its capability to accomplish the binary discrimination of quantum states.After a handful of optimizing iterations,the QSNN achieves a success probability close to the theoretical optimum,no matter whether the states are pure or mixed.Other than binary discrimination,the QSNN is also applied to classify an unknown set of states into two types:entangled ones and separable ones.After training with four samples,it can classify a number of states with acceptable accuracy.Our results suggest that the QSNN has the great potential to process unknown quantum states in quantum information.

关键词： quantum classify separable

Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

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动物学研究(英文) 2023年第5期44卷 967-980页

作者： Chuxi Li Zifan Xiao Yerong Li Zhinan Chen Xun Ji Yiqun Liu Shufei Feng Zhen Zhang Kaiming Zhang Jianfeng Feng Trevor W.Robbins Shisheng Xiong Yongchang Chen Xiao Xiao school of Information Science and Technology Micro Nano System Center Fudan UniversityShanghai 200433China Department of Anesthesiology Huashan HospitalKey Laboratory of Computational Neuroscience and Brain-Inspired IntelligenceMinistry of EducationBehavioral and Cognitive Neuroscience CenterInstitute of Science and Technology for Brain-Inspired IntelligenceMOE Frontiers Center for Brain ScienceFudan UniversityShanghai 200433China kuang yaming honors school Nanjing UniversityNanjingJiangsu 210023China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingYunnan 650500China New Vision World LLC. Aliso ViejoCalifornia 92656USA Behavioural and Clinical Neuroscience institute University of CambridgeCambridgeCB21TNUK

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized assessment.In this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton features.Furthermore,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in monkeys.Using the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual detection.Mon Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

关键词： Action recognition Fine motor identification Two-stream deep model 2D skeleton Non-human primates Rett syndrome

Equilibria between the K^+ binding and cation vacancy conformations of potassium channels

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Protein & Cell 2019年第7期10卷 533-537页

作者： Yao He Bo Zhang Hao Dong Penglin Xu Xiaoying Cai Ting Zhou Mu Yu Jun Liang Xiao Zheng Changlin Tian Hefei National Laboratory for Physical sciences at the Microscale and school of Life sciences University of Science and Technology of China Hefei 230027 China kuang yaming honors school and institute for brain sciences Nanjing University Nanjing 210023 China Hefei National Laboratory for Physical sciences at the Microscale and school of Chemistry and Material sciences University of Science and Technology of China Hefei 230026 China

Dear Editor, Potassium channels are integral membrane proteins that selectively con duct K^+ ions across cell membra ne (Hille, 2001). They play essential roles in maintaining cellular ionic homoeostasis and generating action membrane potentials in excitable cells. The mechanism of K^+ selectivity has been evaluated in many biophysical and physiological studies (Zhou et al., 2001;Liu et al., 2015;Schewe et al., 2016). A highly con served signature seque nee, TVGYG, in the selectivity filter of potassium channels (e.g., KcsA) is known to coordinate K^+ ions (Zhou et al., 2001). Carbonyls of these residues point toward the pore, forming four continuous ion binding sites (S1-S4) and resulting in higher selectivity for K^+ over Na^+(Zhou et al., 2001). The NaK channel from Bacillus cereus is a norvselective cation channel that shares high structural homology with KcsA (Shi et al., 2006). Owing to a distinctive primary sequenee of 63TVGDG67, the selectivity filter of NaK preserves only two ion binding sites, allocated similarly as S3 and S4 in KcsA (Alam and Jiang, 2009a, b). Remarkably, the D66Y and N68D double mutations of NaK channel (Fig. S1) transform it into a K^+ selective channel (termed as NaK2K)(Sauer et al., 2013). Crystal structure of NaK and NaK2K have revealed distinet binding coordination of Na^+ and K^+ ions in their selectivity filter (Figs. S2 and S3)(Alam and Jiang, 2009a, b;Sauer et al., 2013). However, dynamics of the NaK and NaK2K selectivity filter with the bind泊g of Na+ or K^+ are still elusive. Especially, it has been known that the membrane environment is highly diverse from deterge nt micelles, which was con sidered to in flue nee the structure and functi on of membrane protei ns dramatically (Cross et al., 2011). Thus, it is necessary to study the cation and binding properties of NaK NaK2K channels in lipid bilayers.

关键词： Equilibria K^+binding cation vacancy conformations

Synergistic regulation of intermolecular interactions to control chiral structures for chiral recognition

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Chinese Chemical Letters 2023年第3期34卷 332-336页

作者： Weilin Chen Lulu Fu Zhiqiang Zhu Jingyan Liu Linxiu Cheng Zhou Xu Hao Dong Jing Ma Yibao Li Xiaolin Fan Key Laboratory of Organo-pharmaceutical Chemistry Gannan Normal UniversityGanzhou 341000China Key Laboratory of Mesoscopic Chemistry of Ministry of Education School of Chemistry and Chemical EngineeringNanjing UniversityNanjing 210023China kuang yaming honors school and institute for brain sciences Nanjing UniversityNanjing 210023China

Understanding the regulatory mechanism of self-assembly processes is a necessity to modulate nanostructures and their properties. Herein, we have studied the mechanism of self-assembly in the C3 symmetric 1,3,5-benzentricarboxylic amino acid methyl ester enantiomers(TPE) in a mixed solvent system consisting of methanol and water. The resultant chiral structure was used for chiral recognition. The formation of chiral structures from the synergistic effect of multiple noncovalent interaction forces was confirmed by various techniques. Molecular dynamics simulations were used to characterize the time evolution of TPE structure and properties in solution. The theoretical results were consistent with the experimental results. Furthermore, the chiral structure assembled by the building blocks of TPE molecules was highly stereoselective for diamine compounds.

关键词： Supramolecular chemistry Chiral nanostructure Noncovalent interaction forces Molecular dynamics simulations Chiral recognition

Computational prediction of RNA tertiary structures using machine learning methods

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Chinese Physics B 2020年第10期29卷 17-23页

作者：黄斌杜渊洋张帅李文飞王骏张建 National Laboratory of Solid State Microstructures School of PhysicsCollaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China institute for brain sciences Kuang Yaming Honors SchoolNanjing UniversityNanjing 210093China

RNAs play crucial and versatile roles in biological processes. Computational prediction approaches can help to understand RNA structures and their stabilizing factors, thus providing information on their functions, and facilitating the design of new RNAs. Machine learning (ML) techniques have made tremendous progress in many fields in the past few years. Although their usage in protein-related fields has a long history, the use of ML methods in predicting RNA tertiary structures is new and rare. Here, we review the recent advances of using ML methods on RNA structure predictions and discuss the advantages and limitation, the difficulties and potentials of these approaches when applied in the field.

关键词： RNA structure prediction RNA scoring function knowledge-based potentials machine learning convolutional neural networks

Machine learning on properties of multiscale multisource hydroxyapatite nanoparticles datasets with different morphologies and sizes

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npj Computational Materials 2021年第1期7卷 1276-1286页

作者： Ziteng Liu Yinghuan Shi Hongwei Chen Tiexin Qin Xuejie Zhou Jun Huo Hao Dong Xiao Yang Xiangdong Zhu Xuening Chen Li Zhang Mingli Yang Yang Gao Jing Ma Key Laboratory of Mesoscopic Chemistry of Ministry of Education School of Chemistry and Chemical EngineeringNanjing UniversityNanjingP.R.China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjingP.R.China kuang yaming honors school&institute for brain sciences Nanjing UniversityNanjingP.R.China National Engineering Research Center for Biomaterials Sichuan UniversityChengduP.R.China institute of Atomic and Molecular Physics Sichuan UniversityChengduP.R.China College of Biomedical Engineering Sichuan UniversityChengduP.R.China Jiangsu Key Laboratory of Advanced Organic Materials School of Chemistry and Chemical EngineeringNanjing UniversityNanjingP.R.China

Machine learning models for exploring structure-property relation for hydroxyapatite nanoparticles(HANPs)are still lacking.A multiscale multisource dataset is presented,including both experimental data(TEM/SEM,XRD/crystallinity,ROS,anti-tumor effects,and zeta potential)and computation results(containing 41,976 data samples with up to 9768 atoms)of nanoparticles with different sizes and morphologies at density functional theory(DFT),semi-empirical DFTB,and force field,respectively.Three geometric descriptors are set for the explainable machine learning methods to predict surface energies and surface stress of HANPs with satisfactory performance.To avoid the pre-determination of features,we also developed a predictive deep learning model within the framework of graph convolution neural network with good generalizability.Energies with DFT accuracy are achievable for largesized nanoparticles from the learned correlations and scale functions for mapping different theoretical levels and particle sizes.The simulated XRD spectra and crystallinity values are in good agreement with experiments.

关键词： sizes sized property

Carbon-halogen bond activation by a structurally constrained phosphorus(Ⅲ)platform

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Chinese Chemical Letters 2021年第4期32卷 1432-1436页

作者： Penglong Wang Qin Zhu Yi Wang Guixiang Zeng Jun Zhu Congqing Zhu State Key Laboratory of Coordination Chemistry Jiangsu Key Laboratory of Advanced Organic MaterialsSchool of Chemistry and Chemical EngineeringNanjing UniversityNanjing 210093China kuang Yarning honors school Institute for Brain SciencesNanjing UniversityNanjing 210093China State Key Laboratory of Physical Chemistry of Solid Surfaces and Collaborative Innovation Center of Chemistry for Energy Materials(iChEM) and Department of ChemistryCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China

Theσ-bond activation by main group element has received enormous attention from theoretical and experimental chemists.Here,the reaction of C-X(X=Cl,Br,I)bonds in benzyl and allyl halides with a pincer-type phosphorus(Ⅲ)species was reported.A series of structurally robust phosphorus(Ⅴ)compounds were formed via the formal oxidative addition reactions of C-X bonds to the phosphorus(Ⅲ)center.Density functional theory calculations show that the nucleophilic addition process is more favorable than the direct oxidative addition mechanism.Isomerization of bent structures of phosphorus(Ⅲ)compound to poorly nucleophilic compounds to undergo further C-X bond activation can be rationalized by frontier molecule orbital analysis.This study not only provides a deep understanding of the reactivity of phosphorus(Ⅲ)species but also demonstrates a potential of main group elements for the small-molecule activation.

关键词： Pincer ligand Phosphorus C-X bond activation Main group element

Cis-interaction of ligands on a supported lipid bilayer afects their binding to cell adhesion receptors

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Science China(Physics,Mechanics & Astronomy) 2021年第10期64卷 113-122页

作者： Long Li Jinglei Hu Huaping Wu Fan Song State Key Laboratory of Nonlinear Mechanics(LNM)and Beijing Key Laboratory of Engineered Construction and Mechanobiology Institute of MechanicsChinese Academy of SciencesBeijing 100190China kuang Yarning honors school&institute for brain sciences Nanjing UniversityNanjing 210023China Shenzhen Research institute Nanjing UniversityShenzhen 518057China College of Mechanical Engineering Zhejiang University of TechnologyHangzhou 310023China school of Engineering Science University of Chinese Academy of SciencesBeijing 100049China

Cell adhesion on a supported lipid bilayer(SLB) functionalized with ligand proteins is a widely-used cell-mimetic model for the study of the trans receptor-ligand interaction that mediates the adhesion, and has been shown to play an important role in unravelling the molecular players in cell adhesion. Experimental studies of such cell-SLB adhesion systems often assume that there is no cis interactions between the ligands. An important question remains whether the cis-interaction afects the trans receptor-ligand interaction. Using a statistical-mechanical model and Monte Carlo simulations with biologically relevant parameters, we find that the attractive cis-interaction of strength 1 kBT between adjacent ligands on the SLB can lead to an amplification of both the affinity and cooperativity of the receptor-ligand binding, thereby facilitating the phase separation within the adhering cell membrane. In contrast, the adhesion system is less sensitive to the repulsive cis-interaction between adjacent ligands on the SLB.Our results suggest that the ligand-ligand cis-interaction should be carefully considered in the cell-SLB adhesion experiments.

关键词： cell adhesion ligand-ligand cis-interaction receptor-ligand interaction phase behavior

Optimized scorpion toxin selectively targets Hv1 channel and inhibits ROS production in white blood cells

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Optimized scorpion toxin selectively targets Hv1 channel and...