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Alzheimer’s disease early diagnostic and staging biomarkers revealed by large-scale cerebrospinal fluid and serum proteomic profiling

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The Innovation 2024年第1期5卷 118-126页

作者： Qing-Qing Tao Xue Cai Yan-Yan Xue Weigang Ge Liang Yue Xiao-Yan Li Rong-Rong Lin Guo-Ping Peng Wenhao Jiang Sainan Li kun-mu zheng Bin Jiang Jian-Ping Jia Tiannan Guo Zhi-Ying Wu Department of Neurology and Research Center of Neurology in the Second Affiliated Hospital and Key Laboratory of Medical Neurobiology of Zhejiang Province Zhejiang University School of MedicineHangzhou 310009China Liangzhu Laboratory Zhejiang UniversityHangzhou 311100China Westlake Laboratory of Life Sciences and Biomedicine Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake UniversityHangzhou 310024China Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzho 310024China Department of Neurology First Affiliated HospitalZhejiang University School of MedicineHangzhou 310009China Department of Neurology First Affiliated HospitalSchool of MedicineXiamen UniversityXiamen 361009China Innovation Center for Neurological Disorders and Department of Neurology Xuanwu HospitalCapital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijing 100053China MOE Frontier Science Center for Brain Science and Brain-machine Integration School of Brain Science and Brain MedicineZhejiang UniversityHangzhou 310058China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China

Amyloid-b,tau pathology,and biomarkers of neurodegeneration make up the core diagnostic biomarkers of Alzheimer disease(AD).However,these proteins represent only a fraction of the complex biological processes underlying AD,and individuals with other brain diseases in which AD pathology is a comorbidity also test positive for these diagnostic *** ADspecific early diagnostic and disease staging biomarkers are *** this study,we performed tandem mass tag proteomic analysis of paired cerebrospinal fluid(CSF)and serum samples in a discovery cohort comprising 98 *** biomarkers were validated by parallel reaction monitoring–based targeted proteomic assays in an independent multicenter cohort comprising 288 *** quantified 3,238 CSF and 1,702 serum proteins in the discovery cohort,identifying 171 and 860 CSF proteins and 37 and 323 serum proteins as potential early diagnostic and staging biomarkers,*** the validation cohort,58 and 21 CSF proteins,as well as 12 and 18 serum proteins,were verified as early diagnostic and staging biomarkers,*** 19-protein CSF and an 8-protein serum biomarker panels were built by machine learning to accurately classify mild cognitive impairment(MCI)due to AD from normal cognition with areas under the curve of 0.984 and 0.881,*** 19-protein CSF biomarker panel also effectively discriminated patients with MCI due to AD from patients with other neurodegenerative ***,we identified 21 CSF and 18 serum stage-associated proteins re-flecting AD *** findings provide a foundation for developing bloodbased tests for AD screening and staging in clinical practice.

关键词： cerebrospinal Alzheimer fluid

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CNKSR2 interactome analysis indicates its association with the centrosome/microtubule system

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Neural Regeneration Research 2025年第8期20卷 2420-2432页

作者： Lin Yin Yalan Xu Jie mu Yu Leng Lei Ma Yu zheng Ruizhi Li Yin Wang Peifeng Li Hai Zhu Dong Wang Jing Li Institute for Translational Medicine The Affiliated Hospital of Qingdao UniversityMedical CollegeQingdao UniversityQingdaoShandong ProvinceChina School of Basic Medicine Qingdao UniversityQingdaoShandong ProvinceChina College of Life Sciences and School of PharmacyMedical CollegeQingdao UniversityQingdaoShandong ProvinceChina Department of Urology Qingdao Municipal Hospital Affiliated to Qingdao UniversityQingdaoShandong ProvinceChina

The protein connector enhancer of kinase suppressor of Ras 2(CNKSR2),present in both the postsynaptic density and cytoplasm of neurons,is a scaffolding protein with several protein-binding *** of the CNKSR2 gene have been implicated in neurodevelopmental disorders,particularly intellectual disability,although the precise mechanism involved has not yet been fully *** has demonstrated that CNKSR2 plays a role in facilitating the localization of postsynaptic density protein complexes to the membrane,thereby influencing synaptic signaling and the morphogenesis of dendritic ***,the function of CNKSR2 in the cytoplasm remains to be *** this study,we used immunoprecipitation and high-resolution liquid chromatography-mass spectrometry to identify the interactors of *** a combination of bioinformatic analysis and cytological experiments,we found that the CNKSR2 interactors were significantly enriched in the proteome of the *** also showed that CNKSR2 interacted with the microtubule protein DYNC1H1 and with the centrosome marker *** colocalization analysis confirmed the centrosomal localization of *** we downregulated CNKSR2 expression in mouse neuroblastoma cells(Neuro 2A),we observed significant changes in the expression of numerous centrosomal *** manipulation also affected centrosome-related functions,including cell size and shape,cell proliferation,and ***,we found that CNKSR2 interactors were highly enriched in de novo variants associated with intellectual disability and autism spectrum *** findings establish a connection between CNKSR2 and the centrosome,and offer new insights into the underlying mechanisms of neurodevelopmental disorders.

关键词： autism spectrum disorder centrosome CNKSR2 intellectual disability interactome mass spectrometry microtubule neurodevelopmental disease protein complexes protein-protein interactions

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Increasingly important role of numerical modeling in oceanic observation design strategy: A review

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Science China Earth Sciences 2020年第11期63卷 1678-1690页

作者： kun ZHANG mu mu Qiang WANG CAS Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences and Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266071China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China CMA-FDU Joint Laboratory of Marine Meteorology Shanghai 200438China Innovation Center of Ocean and Atmosphere System Zhuhai Fudan Innovation Research InstituteZhuhai 518057China Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China College of Oceanography Hohai UniversityNanjing 210098China

Oceanic observation design is of considerable significance and has made remarkable progress during the past several *** study addresses the critical role of numerical modeling in oceanic observation *** a brief introduction of the characteristics of existing oceanic observation design studies,we present the advantages of the model-based observation design strategy and further review its decisive *** demonstrate the effectiveness of this strategy,the targeted observation applications using the conditional nonlinear optimal perturbation(CNOP)approach for improving the Kuroshio predictions are ***,the authors present their consideration for correcting model errors by targeted observations of sensitive model parameters and mitigating the model-dependency problem by utilizing multiple modeling *** on using observing system simulation experiments to validate the designed observations and extending the model-based observation design strategy into observing oceanic climatological mean states are also discussed.

关键词： Observation design Numerical modeling Targeted observation CNOP

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Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model

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Science China Earth Sciences 2017年第5期60卷 866-875页

作者： ZHANG kun mu mu WANG Qiang Key Laboratory of Ocean Circulation and Waves Institute of Oceanology Chinese Academy of Sciences Qingdao 266071 China University of Chinese Academy of Sciences Beijing 100049 China Institute of Atmospheric Sciences Fudan University Shanghai 200433 China Laboratory for Ocean and Climate Dynamics Qingdao National Laboratory for Marine Science and Technology Qingdao 266237 China

Using the conditional nonlinear optimal perturbation(CNOP) approach, sensitive areas of adaptive observation for predicting the seasonal reduction of the upstream Kuroshio transport(UKT) were investigated in the Regional Ocean Modeling System(ROMS). The vertically integrated energy scheme was utilized to identify sensitive areas based on two factors: the specific energy scheme and sensitive area size. Totally 27 sensitive areas, characterized by three energy schemes and nine sensitive area sizes, were evaluated. The results show that the total energy(TE) scheme was the most effective because it includes both the kinetic and potential components of CNOP. Generally, larger sensitive areas led to better predictions. The size of 0.5% of the model domain was chosen after balancing the effectiveness and efficiency of adaptive observation. The optimal sensitive area OSen was determined accordingly. Sensitivity experiments on OSen were then conducted, and the following results were obtained:(1) In OSen, initial errors with CNOP or CNOP-like patterns were more likely to yield worse predictions, and the CNOP pattern was the most unstable.(2) Initial errors in OSen rather than in other regions tended to cause larger prediction errors. Therefore, adaptive observation in OSen can be more beneficial for predicting the seasonal reduction of UKT.

关键词： Sensitive area Adaptive observation The upstream Kuroshio transport Conditional nonlinear optimal perturbation(CNOP)

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Recent Progress in Applications of the Conditional Nonlinear Optimal Perturbation Approach to Atmosphere-Ocean Sciences

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Chinese Annals of Mathematics,Series B 2022年第6期43卷 1033-1048页

作者： mu mu kun ZHANG Qiang WANG Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China CMA-FDU Joint Laboratory of Marine Meteorology Shanghai 200438China Shanghai Frontiers Science Center of Atmosphere-Ocean Interaction Shanghai 200438China CAS Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences and Qingdao National Laboratory for Marine Science and TechnologyQingdao 266071China Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China College of Oceanography Hohai UniversityNanjing 210098China

The conditional nonlinear optimal perturbation(CNOP for short) approach is a powerful tool for predictability and targeted observation studies in atmosphere-ocean sciences. By fully considering nonlinearity under appropriate physical constraints, the CNOP approach can reveal the optimal perturbations of initial conditions, boundary conditions, model parameters, and model tendencies that cause the largest simulation or prediction uncertainties. This paper reviews the progress of applying the CNOP approach to atmosphere-ocean sciences during the past five years. Following an introduction of the CNOP approach, the algorithm developments for solving the CNOP are ***, recent CNOP applications, including predictability studies of some high-impact ocean-atmospheric environmental events, ensemble forecast, parameter sensitivity analysis, uncertainty estimation caused by errors of model tendency or boundary condition, are reviewed. Finally, a summary and discussion on future applications and challenges of the CNOP approach are presented.

关键词： Conditional nonlinear optimal perturbation Atmosphere Ocean Targeted observation Predictability

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Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach

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Journal of Oceanology and Limnology 2020年第5期38卷 1382-1393页

作者： GAO Yongli mu mu ZHANG kun Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China College of Science China University of Petroleum(East China)Qingdao 266580China Institute of Atmospheric Sciences Fudan UniversityShanghai 200433China Qingdao National Laboratory for Marine Science and Technology Qingdao 266237China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China

Parameter uncertainty is a primary source of uncertainty in ocean ecosystem *** deep chlorophyll maximum(DCM)is a ubiquitous ecological phenomenon in the *** a theoretical nutrients-phytoplankton model and the conditional nonlinear optimal perturbation approach related to parameters,we investigated the eff ects of parameter uncertainties on DCM ***,the sensitivity of single parameter was *** sensitivity ranking of 10 parameters was obtained by analyzing the top four specifi *** most sensitive parameter(background turbidity)aff ects the light supply for DCM formation,whereas the other three parameters(nutrient content of phytoplankton,nutrient recycling coeffi cient,and vertical turbulent diff usivity)control nutrient *** explore the interactions among diff erent parameters,the sensitivity of multiple parameters was further studied by examining combinations of four *** results show that background turbidity is replaced by the phytoplankton loss rate in the optimal parameter *** addition,we found that interactions among these parameters are responsible for such diff ***,we found that reducing the uncertainties of sensitive parameters could improve DCM simulations *** with the sensitive parameters identifi ed in the single parameter analysis,reducing parameter uncertainties in the optimal combination produced better model *** study shows the importance of nonlinear interactions among various parameters in identifying sensitive *** the future,the conditional nonlinear optimal perturbation approach related to parameters,especially optimal parameter combinations,is expected to greatly improve DCM simulations in complex ecosystem models.

关键词： deep chlorophyll maximum(DCM)simulation parameter uncertainty conditional nonlinear optimal perturbation related to parameters(CNOP-P) sensitivity

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A semi-analytical method to compute acoustic nonlinearity parameter of Cu,Ag and Au

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Rare Metals 2023年第3期42卷 1050-1055页

作者： Zi-mu Chen zheng Zhang School of Materials Science and Engineering Beihang UniversityBeijing 100191China

In this paper,a semi-analytical method was proposed to evaluate the acoustic nonlinearity parameter for single crystals of Cu,Ag and *** acoustic nonlinearity parameter can be derived analytically by general expressions in terms of the interatomic potentials with the distances between each pair of atoms in these transition *** evaluate the acoustic nonlinearity parameter,one needs to conduct one step molecular static simulation and obtain the equilibrium positions of all the ***,based on this method,numerical experiments with molecular dynamic code LAMMPS were given to compute the acoustic nonlinearity parameter of Cu,Ag and *** illustrate the validity of these expressions,comparison was made between calculation results and data in the *** agreement is *** of the analytical nature of this method,it provides a fundamental understanding of the nonlinear elastic behavior of these transition metals.

关键词： Nondestructive testing Semi-analytical Acoustic nonlinearity parameter Molecular static simulation

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A POSITIVITY-PRESERVING FINITE ELEMENT METHOD FOR QUANTUM DRIFT-DIFFUSION MODEL

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Journal of Computational Mathematics 2023年第5期41卷 909-932页

作者： Pengcong mu Weiying zheng School of Mathematical Science University of Chinese Academy of SciencesBeijing 100049China LSEC NCMISInstitute of Computational Mathematics and Scientific ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

In this paper,we propose a positivity-preserving finite element method for solving the three-dimensional quantum drift-diffusion *** model consists of five nonlinear elliptic equations,and two of them describe quantum corrections for quasi-Fermi *** propose an interpolated-exponential finite element(IEFE)method for solving the two quantum-correction *** IEFE method always yields positive carrier densities and preserves the positivity of second-order differential operators in the Newton linearization of quantum-correction ***,we solve the two continuity equations with the edge-averaged finite element(EAFE)method to reduce numerical oscillations of quasi-Fermi *** Poisson equation of electrical potential is solved with standard Lagrangian finite *** prove the existence of solution to the nonlinear discrete problem by using a fixed-point iteration and solving the minimum problem of a new discrete functional.A Newton method is proposed to solve the nonlinear discrete *** experiments for a three-dimensional nano-scale FinFET device show that the Newton method is robust for source-to-gate bias voltages up to 9V and source-to-drain bias voltages up to 10V.

关键词： Quantum drift-diffusion model Positivity-preserving finite element method Newton method FinFET device High bias voltage

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Methods,progresses,and opportunities of materials informatics

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InfoMat 2023年第8期5卷 37-66页

作者： Chen Li kun zheng Beijing Key Lab of Microstructure and Properties of Solids Faculty of Materials and ManufacturingBeijing University of TechnologyBeijingthe People's Republic of China

As an implementation tool of data intensive scientific research methods,machine learning(ML)can effectively shorten the research and development(R&D)cycle of new materials by half or even *** shows great potential in the combination with other scientific research technologies,especially in the processing and classification of large amounts of material data from theoretical calculation and experimental *** is very important to systematically understand the research ideas of material informatics to accelerate the exploration of new ***,we provide a comprehensive introduction to the most commonly used ML modeling methods in material informatics with classic ***,we review the latest progresses of prediction models,which focus on new processing–structure–properties–performance(PSPP)relationships in some popular material systems,such as perovskites,catalysts,alloys,two-dimensional materials,and *** addition,we summarize the recent pioneering researches in innovation of material research technology,such as inverse design,ML interatomic potentials,and microtopography characterization assistance,as new research directions of material ***,we comprehensively provide the most significant challenges and outlooks related to the future innovation and development in the field of material *** review provides a critical and concise appraisal for the applications of material informatics,and a systematic and coherent guidance for material scientists to choose modeling methods based on required materials and technologies.

关键词： features machine learning materials materials informatics modeling

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High Order IMEX Stochastic Galerkin Schemes for Linear Transport Equation with Random Inputs and Diffusive Scalings

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Communications on Applied Mathematics and Computation 2024年第1期6卷 325-339页

作者： zheng Chen Lin mu Department of Mathematics University of Massachusetts Dartmouth285 Old Westport RoadDartmouth02747MAUSA Department of Mathematics University of GeorgiaAthens30602GAUSA

In this paper,we consider the high order method for solving the linear transport equations under diffusive scaling and with random *** tackle the randomness in the problem,the stochastic Galerkin method of the generalized polynomial chaos approach has been ***,the high order implicit-explicit scheme under the micro-macro decomposition framework and the discontinuous Galerkin method have been *** provide several numerical experiments to validate the accuracy and the stochastic asymptotic-preserving property.

关键词： Stochastic Galerkin scheme linear transport equations generalized polynomial approach stochastic asymptotic-preserving property

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