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Distinct molecular targets of ProEGCG from EGCG and superior inhibition of angiogenesis signaling pathways for treatment of endometriosis

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Journal of Pharmaceutical Analysis 2024年第1期14卷 100-114页

作者： Sze Wan hung Massimiliano Gaetani Yiran Li Zhouyurong Tan Xu Zheng Ruizhe Zhang Yang Ding Gene Chi Wai man Tao Zhang Yi Song Yao Wang Jacqueline Pui Wah Chung Tak Hang Chan Roman A.Zubarev Chi Chiu Wang Department of Obstetrics&Gynaecology The Chinese University of Hong KongHong KongChina Division of Physiological Chemistry I Department of Medical Biochemistry and BiophysicsKarolinska InstitutetStockholmSE 17177Sweden Chemical Proteomics Core Facility Department of Medical Biochemistry and BiophysicsKarolinska InstitutetStockholmSE 17177Sweden Unit of Chemical Proteomics Science for Life Laboratory(SciLifeLab)StockholmSE 17177Sweden Center for Reproductive Medicine Henan Key Laboratory of Reproduction and GeneticsThe First Affiliated Hospital of Zhengzhou UniversityZhengzhou450003China Department of Chemistry McGill UniversityMontrealH3A2K6Canada Department of Pharmacological&Technological Chemistry I.M.Sechenov First Moscow State Medical UniversityMoscow119146Russia Reproduction and Development Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongHong KongChina School of Biomedical Sciences The Chinese University of Hong KongHong KongChina Chinese University of Hong Kong-Sichuan University Joint Laboratory in Reproductive Medicine The Chinese University of Hong KongHong KongChina

Endometriosis is a common chronic gynecological disease with endometrial cell implantation outside the uterus.Angiogenesis is a major pathophysiology in endometriosis.Our previous studies have demonstrated that the prodrug of epigallocatechin gallate(ProEGCG)exhibits superior anti-endometriotic and anti-angiogenic effects compared to epigallocatechin gallate(EGCG).However,their direct binding targets and underlying mechanisms for the differential effects remain unknown.In this study,we demonstrated that oral ProEGCG can be effective in preventing and treating endometriosis.Additionally,1D and 2D Proteome Integral Solubility Alteration assay-based chemical proteomics identified metadherin(MTDH)and PX domain containing serine/threonine kinase-like(PXK)as novel binding targets of EGCG and ProEGCG,respectively.Computational simulation and BioLayer interferometry were used to confirm their binding affinity.Our results showed that MTDH-EGCG inhibited protein kinase B(Akt)-mediated angiogenesis,while PXK-ProEGCG inhibited epidermal growth factor(EGF)-mediated angiogenesis via the EGF/hypoxia-inducible factor(HIF-1a)/vascular endothelial growth factor(VEGF)pathway.In vitro and in vivo knockdown assays and microvascular network imaging further confirmed the involvement of these signaling pathways.Moreover,our study demonstrated that ProEGCG has superior therapeutic effects than EGCG by targeting distinct signal transduction pathways and may act as a novel antiangiogenic therapy for endometriosis.

关键词： Molecular targets ProEGCG EGCG Angiogenesis Treatment Endometriosis

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Identifying Brand Consistency by Product Differentiation Using CNN

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 685-709页

作者： hung-Hsiang Wang Chih-Ping Chen Department of Industrial Design National Taipei University of TechnologyTaipeiTaiwan Department of Product Design Ming Chuan UniversityTaoyuanTaiwan

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

关键词： Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse

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Data-Driven Modeling of Partially Observed Biological Systems

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Communications on Applied Mathematics and Computation 2024年第1期6卷 739-754页

作者： Wei-hung Su Ching-Shan Chou Dongbin Xiu Department of Mathematics The Ohio State UniversityColumbusOH43221USA

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical behavior.As an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at all.We demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden parameters.The learned DNN model serves as an accurate predictive tool for system analysis.Through a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction process.The learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

关键词： Deep neural network(DNN) Governing equation discovery Biological system Partial observation

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Autolysosomal acidification impairment as a mediator for TNFR1 induced neuronal necroptosis in Alzheimer’s disease

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Neural Regeneration Research 2024年第9期19卷 1869-1870页

作者： Evridiki Asimakidou Richard Reynolds Anna M.Barron Chih hung Lo Department of Clinical Neurosciences University of CambridgeCambridgeUK Department of Brain Sciences Faculty of MedicineImperial College LondonLondonUK Lee Kong Chian School of Medicine Nanyang Technological UniversitySingaporeSingapore

Neuronal necroptosis-an emerging form of regulated cell death associated with neuroinflammatory signaling:Alzheimer’s disease(AD)is characterized by the presence of extracellular amyloid-β(Aβ)plaques and intracellular tau neurofibrillary tangles as well as progressive neuronal loss.Recent evidence has suggested that prolonged neuroinflammation with increased levels of cytokines,arising from neuronal injury,innate immune responses from glial cells,and peripheral inflammation,leads to neuronal death and AD progression.

关键词： Alzheimer death tau Aβ

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Study of relationship between motion of mechanisms in gas operated weapon and its shock absorber

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Defence Technology（防务技术） 2024年第3期33卷 42-54页

作者： Jiri Balla Roman Vitek Dung Nguyen Van Zbynek Krist hung Nguyen Van Department of Weapons and Ammunition University of Defence BrnoCzech Republic Department of Weapons Le Quy Don Technical UniversityHanoiViet Nam Department of Design and Special Engineering Alexander Dubcek University of TrencinSlovakia

The article deals with the motion of the breech block carrier and the weapon casing of an automatic weapon mounted on a flexible carriage and the base of the weapon.Earlier works,which did not consider the dynamic properties of the base of the weapon,did not allow to reconcile the calculated and experimental results of the weapon casing displacement when shooting from firing rests.For the analysis of the motion of individual parts,the methods of mathematical modelling and firing experiments using a high-speed camera were chosen.Calculations show the best accord with experiment when modelling the system with 4 degrees of freedom.The oscillation of the system regarding the movement of the breech block carrier and the weapon casing was investigated under changed conditions of rate of fire,the use of a muzzle brake and different types of shock absorbers.The velocities and displacements of the weapon casing and the breech block carrier at different values of the impulse of the gases to the breech block carrier were determined.

关键词： Shock absorber Gas-operated weapon Force-impulse diagram Recoil system Breech block carrier

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Community perspectives on the effectiveness of watershed management institutions in the Himalayas

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Journal of Mountain Science 2024年第4期21卷 1119-1139页

作者： Nisha SILWAL Nabin DhungANA Rajan SUBEDI Suraj UPADHAYA Chun-hung LEE Natural Resources Conservation Nepal(NRCN) ChitwanP.O.Box 44200Nepal Department of Natural Resources and Environmental Studies College of Environmental StudiesNational Dong Hwa UniversityHualien 97401Chinese Taipei Institute of Forestry Tribhuvan UniversityPokharaP.O.Box 43Nepal School of Agriculture and Natural Resources Kentucky State UniversityFrankfortKY 40601USA Himalayan Conservation and Research Institute DolpaP.O.Box 21400Nepal

The sustainability of environmental management initiatives,such as watershed management programs,relies on the presence of effective institutions at the watershed level.However,there needs to be more empirical evidence from evaluating the effectiveness of watershed-level institutions.Therefore,this study presents a pioneering effort to evaluate the effectiveness of Nepal’s first watershed conservation committee at the watershed scale,focusing on the case of the Khageri Khola watershed in Central Nepal.The study involved conducting a household survey,key informant interviews,focus group discussions,and field observations to collect and analyze the data.Descriptive analysis,index value calculation,and chi-square statistics were then employed to summarize the results regarding local respondents’perceptions of twelve institutional characteristics,their rationalities,and their association with socio-demographic variables.The results reveal that the watershed conservation committee was perceived as performing well in managing the watershed.Specifically,good interaction,appropriate scale,technical,environmental,social,organizational,and government rationality were perceived as highly effective,with an average index value of less than 0.36.In contrast,clarity of objectives and economic rationality showed moderate effectiveness,with an average index value ranging from 0.36 to 0.65.However,the results suggested that adaptiveness,compliance capacity,and financial rationality merit increased attention,intending to improve their performance.Further,the results showed the association of socio-demographics with respondents’perceptions of various indicators of institutional characteristics and their rationalities.Therefore,the study provides valuable insights for policymakers,researchers,and development practitioners charged with designing sustainable and effective programs and institutions.To enhance the effectiveness and sustainability of watershed management programs,we recommend establishing a policy-guided institutional mec

关键词： Watershed Watershed institutions Indicators Institutional characteristics Rationalities Nepal.

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A Projection and Decomposition Approach for Multi-agent Coordinated Scheduling in Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 991-996页

作者： Haifeng Qiu Zhigang Li Hongjun Gao hung Dinh Nguyen Veerapandiyan Veerasamy Hoay Beng Gooi IEEE the School of Electrical and Electronic Engineering Nanyang Technological University School of Electric Power Engineering South China University of Technology the College of Electrical Engineering Sichuan University

Aiming at multi-agent coordinated scheduling problems in power systems under uncertainty, a generic projection and decomposition(P&D) approach is proposed in this letter. The canonical min-max-min two-stage robust optimization(TSRO) model with coupling constraints is equivalent to a concise robust optimization(RO) model in the version of mixed-integer linear programming(MILP) via feasible region projection. The decentralized decoupling of the non-convex MILP problem is realized through a dual decomposition algorithm, which ensures the fast convergence to a high-quality solution in the distributed optimization. Numerical tests verify the superior performance of the proposed P&D approach over the existing distributed TSRO method.

关键词： Uncertainty Couplings Power systems Optimization Computational modeling Convergence Processor scheduling

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Highly Accurate Golden Section Search Algorithms and Fictitious Time Integration Method for Solving Nonlinear Eigenvalue Problems

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1317-1335页

作者： Chein-Shan Liu Jian-hung Shen Chung-Lun Kuo Yung-Wei Chen Center of Excellence for Ocean Engineering Taiwan Ocean UniversityKeelung202301TaiwanChina Department of Marine Engineering Taiwan Ocean UniversityKeelung202301TaiwanChina

This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less,where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector.1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues.Simultaneously,the real and complex eigenvectors can be computed very accurately.A simpler approach to the nonlinear eigenvalue problems is proposed,which implements a normalization condition for the uniqueness of the eigenvector into the eigenequation directly.The real eigenvalues can be computed by the fictitious time integration method(FTIM),which saves computational costs compared to the one-dimensional golden section search algorithm(1D GSSA).The simpler method is also combined with the Newton iterationmethod,which is convergent very fast.All the proposed methods are easily programmed to compute the eigenvalue and eigenvector with high accuracy and efficiency.

关键词： Nonlinear eigenvalue problem quadratic eigenvalue problem two new merit functions golden section search algorithm fictitious time integration method

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Role of metabolic dysfunction and inflammation along the liver-brain axis in animal models with obesity-induced neurodegeneration

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Neural Regeneration Research 2025年第4期20卷 1069-1076页

作者： Evridiki Asimakidou Eka Norfaishanty Saipuljumri Chih hung Lo Jialiu Zeng Department of Clinical Neurosciences University of CambridgeCambridgeUK School of Applied Science Republic PolytechnicSingaporeSingapore Lee Kong Chian School of Medicine Nanyang Technological UniversitySingaporeSingapore

The interaction between metabolic dysfunction and inflammation is central to the development of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease.Obesity-related conditions like type 2 diabetes and non-alcoholic fatty liver disease exacerbate this relationship.Peripheral lipid accumulation,particularly in the liver,initiates a cascade of inflammatory processes that extend to the brain,influencing critical metabolic regulatory regions.Ceramide and palmitate,key lipid components,along with lipid transporters lipocalin-2 and apolipoprotein E,contribute to neuroinflammation by disrupting blood–brain barrier integrity and promoting gliosis.Peripheral insulin resistance further exacerbates brain insulin resistance and neuroinflammation.Preclinical interventions targeting peripheral lipid metabolism and insulin signaling pathways have shown promise in reducing neuroinflammation in animal models.However,translating these findings to clinical practice requires further investigation into human subjects.In conclusion,metabolic dysfunction,peripheral inflammation,and insulin resistance are integral to neuroinflammation and neurodegeneration.Understanding these complex mechanisms holds potential for identifying novel therapeutic targets and improving outcomes for neurodegenerative diseases.

关键词： Alzheimer’s disease inflammatory cytokines insulin resistance lipid

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An Overview of Chemical Constituents, Medicinal Properties, Clinical Trials, and Patents of Twigs of Morus alba(Ramulus Mori)

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World Journal of Traditional Chinese Medicine 2024年第2期10卷 149-158页

作者： Eric Wei Chiang Chan hung Tuck Chan Siu Kuin Wong Department of Food Science and Nutrition Faculty of Applied Sciences UCSI University Secretariat of International Society for mangrove Ecosystems Faculty of Agriculture University of the Ryukyus School of Foundation Studies Xiamen University Malaysia

The rich chemical constituents and diverse pharmacological properties of Ramulus Mori(RM) or the twig of Morus alba with evidence supported by clinical trials and patents are reviewed. Known as Sangzhi in Chinese, RM is widely used in traditional Chinese medicine to treat gout, arthritis, and rheumatism. Chemical constituents include flavonoids, benzofurans, alkaloids, stilbenes, chalcones, phenolic acids, and coumarins. Bioactivities of RM include antidiabetic, anti-obesity, anti-inflammatory, antityrosinase, neuroprotective, antioxidant, hepatoprotective, cytoprotective, renoprotective, antihyperuricemic, analgesic, antifungal, DNA protective, anticancer, gastroprotective, cardioprotective, anti-hair aging, anti-arthritic, and antiplatelet aggregation properties. The most active compounds from RM are mulberrin, oxyresveratrol, and mulberroside A. All four clinical trials on RM are focused on the treatment of diabetes. The patents entail using RM extracts as cosmetics for skin whitening and as agents for hypoglycemia. Topics for further research on RM are suggested.

关键词： Clinical trials mulberrin mulberroside A oxyresveratrol patents Sangzhi

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