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A novel mutation in FBN1 gene in autosomal dominant Marfan syndrome and macular degeneration in a Chinese consanguineous family

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International Journal of Ophthalmology(English edition) 2019年第5期12卷 725-730页

作者： Ping-Bo Ouyang Yuan Zhao ying-qian peng Lu-Si Zhang Jian Cao Yun Li Department of Ophthalmology the Second Xiangya Hospital of Central South University Hunan Clinical Research Center of Ophthalmic Disease Department of Cardiovascular Surgery the Second Xiangya Hospital of Central South University

AIM: To report a novel mutation in FBN1 gene in a Chinese consanguineous family with common Marfan syndrome(MFS) phenotype and an unusual bilateral macular degeneration. METHODS: Ophthalmic, cardiovascular and systemic examinations were performed, and genomic DNA extracted from all living family members. The 24-32 exon mutations of FBN1 gene were screened by Sanger Sequencing in all family members and 100 unrelated healthy Chinese individuals. RESULTS: In the four-generation family, classic MFS phenotypes were observed in all 5 patients, 2 of them had peculiar phenotype of bilateral macular degeneration. Mutation screening in FBN1 identified a heterozygous missense mutation(c.3932 A>G, p.Y1311 C) with co-segregation. This mutation was found with the MFS phenotypes in all 5 patients but not in unaffected members or unrelated controls. CONCLUSION: A Chinese consanguineous MFS family with uncommon bilateral macular degeneration and an unreported c.3932 A>G mutation in FBN1 was identified. Our finding expands the FBN1 mutation spectrum and its possible role in the pathogenesis of Marfan syndrome.

关键词： Marfan syndrome fibrillin-1 autosomal dominant heterozygous mutation

Diverse roles of macrophages in intraocular neovasculardiseases:a review

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International Journal of Ophthalmology(English edition) 2017年第12期10卷 1902-1908页

作者： Ye-Di Zhou Shigeo Yoshida ying-qian peng Yoshiyuki Kobayashi Lu-Si Zhang Luo-Sheng Tang Department of Ophthalmology the Second Xiangya HospitalCentral South UniversityChangsha 410011Hunan ProvinceChina Hunan Clinical Research Center of Ophthalmic Disease Changsha 410011Hunan ProvinceChina Department of Ophthalmology Kyushu University Graduate School of Medical SciencesFukuoka 812-8582Japan

Macrophages are involved in angiogenesis, and might also contribute to the pathogenesis of intraocular neovascular diseases. Recent studies indicated that macrophages exert different functions in the process of intraocular neovascularization, and the polarization of M1 and M2 phenotypes plays extremely essential roles in the diverse functions of macrophages. Moreover, a large number of cytokines released by macrophages not only participate in macrophage polarization, but also associate with retinal and choroidal neovascular diseases. Therefore, macrophage might be considered as a novel therapeutic target to the treatment of pathological neovascularization in the eye. This review mainly summarizes diverse roles of macrophages and discusses the possible mechanisms in retinal and choroidal neovascularization.

关键词： macrophage retinal neovascularization choroidal neovascularization proliferative diabetic retinopathy retinopathy ofprematurity age-related macular degeneration

Identification of altered microRNAs in retinas of mice with oxygen-induced retinopathy

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International Journal of Ophthalmology(English edition) 2019年第5期12卷 739-745页

作者： Lu-Si Zhang Ye-Di Zhou ying-qian peng Hui-Lan Zeng Shigeo Yoshida Tan-Tai Zhao Department of Ophthalmology the Second Xiangya Hospital of Central South University Hunan Clinical Research Center of Ophthalmic Disease Department of Ophthalmology Kurume University School of Medicine

AIM: To identify disease-related miRNAs in retinas of mice with oxygen-induced retinopathy(OIR), and to explore their potential roles in retinal pathological neovascularization. METHODS: The retinal miRNA expression profile in mice with OIR and room air controls at postnatal day 17(P17) were determined through miRNA microarray analysis. Several miRNAs were significantly up-and down-regulated in retinas of mice with OIR compared to controls by quantitative real-time reverse transcription-polymerase chain reaction(qRT-PCR). Two databases including Targetscan7.1 and MirdbV5 were used to predict target genes that associated with those significantly altered mi RNAs in retinas of mice with OIR. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analyses were also conducted to identify possible biological functions of the target genes. RESULTS: In comparison with room air controls, 3 and 8 miRNAs were significantly up-and down-regulated, respectively, in retinas of mice with OIR. The qRT-PCR data confirmed that mmu-miR-350-3 p and mmu-miR-202-3 p were significantly up-regulated, while mmu-miR-711 and mmu-miR-30 c-1-3 p were significantly down-regulated in mice with OIR compared to controls. GO analysis demonstrated that the identified target genes were related to functions such as cellular macromolecule metabolic process. KEGG pathway analysis showed a group of pathways, such as Wnt signaling pathway, transcriptionalmisregulation in cancer, Mucin type O-glycan biosynthesis, and mitogen-activated protein kinase(MAPK) signaling pathway might be involved in pathological process of retinal neovascularization. CONCLUSION: Our findings suggest that the differentially expressed miRNAs in retinas of mice with OIR might provide potential therapeutic targets for treating retinal neovascularization.

关键词： microRNAs retinal neovascularization oxygen-induced retinopathy microarray

Guaranteed Cost Attitude Tracking Control for Uncertain Quadrotor Unmanned Aerial Vehicle Under Safety Constraints

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1447-1457页

作者： qian Ma peng Jin Frank L.Lewis School of Automation Nanjing University of Science and TechnologyNanjing 210094China UTA Research Institute University of Texas at ArlingtonFort WorthTexas 76118 USA IEEE

In this paper,guaranteed cost attitude tracking con-trol for uncertain quadrotor unmanned aerial vehicle(QUAV)under safety constraints is ***,an augmented system is constructed by the tracking error system and reference *** transformation aims to convert the tracking control prob-lem into a stabilization control ***,control barrier function and disturbance attenuation function are designed to characterize the violations of safety constraints and tolerance of uncertain disturbances,and they are incorporated into the reward function as penalty *** on the modified reward function,the problem is simplified as the optimal regulation problem of the nominal augmented system,and a new Hamilton-Jacobi-Bellman equation is ***,critic-only rein-forcement learning algorithm with a concurrent learning tech-nique is employed to solve the Hamilton-Jacobi-Bellman equa-tion and obtain the optimal *** proposed algorithm can not only ensure the reward function within an upper bound in the presence of uncertain disturbances,but also enforce safety *** performance of the algorithm is evaluated by the numerical simulation.

关键词： Attitude tracking control quadrotor unmanned aerial vehicle(QUAV) reinforcement learning safety constraints uncertain disturbances.

Hierarchical vectorization for facial images

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Computational Visual Media 2024年第1期10卷 97-118页

作者： qian Fu Linlin Liu Fei Hou ying He School of Computer Science and Engineering Nanyang Technological University639798SingaporeSingapore Data61 Commonwealth Scientific and Industrial Research OrganisationSydney2015Australia Interdisciplinary Graduate School Nanyang Technological University and Alibaba Group639798SingaporeSingapore State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100049China

The explosive growth of social media means portrait editing and retouching are in high *** portraits are commonly captured and stored as raster images,editing raster images is non-trivial and requires the user to be highly *** at developing intuitive and easy-to-use portrait editing tools,we propose a novel vectorization method that can automatically convert raster images into a 3-tier hierarchical *** base layer consists of a set of sparse diffusion curves(DCs)which characterize salient geometric features and low-frequency colors,providing a means for semantic color transfer and facial expression *** middle level encodes specular highlights and shadows as large,editable Poisson regions(PRs)and allows the user to directly adjust illumination by tuning the strength and changing the shapes of *** top level contains two types of pixel-sized PRs for high-frequency residuals and fine details such as pimples and *** train a deep generative model that can produce high-frequency residuals *** to the inherent meaning in vector primitives,editing portraits becomes easy and *** particular,our method supports color transfer,facial expression editing,highlight and shadow editing,and automatic *** quantitatively evaluate the results,we extend the commonly used FLIP metric(which measures color and feature differences between two images)to consider *** new metric,illumination-sensitive FLIP,can effectively capture salient changes in color transfer results,and is more consistent with human perception than FLIP and other quality measures for portrait *** evaluate our method on the FFHQR dataset and show it to be effective for common portrait editing tasks,such as retouching,light editing,color transfer,and expression editing.

关键词： face editing vectorization Poisson editing color transfer illumination editing expression editing

Influence of laser parameters on the microstructures and surface properties in laser surface modification of biomedical magnesium alloys

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Journal of Magnesium and Alloys 2024年第1期12卷 72-97页

作者： Chee ying Tan Cuie Wen Hua qian Ang School of Engineering RMIT UniversityMelbourneVictoria 3001Australia

Biodegradable implants from magnesium(Mg)alloys have emerged in the biomedical field especially in the orthopedic and cardiovascular stent applications owing to their low density,high specific strength,excellent machinability,good biocompatibility,and *** primary shortcoming of Mg-based implants is their low corrosion resistance in the physiological environment,which results in premature mechanical integrity loss before adequate healing and the production of excessive hydrogen gas,which is harmful to the body tissues and negatively affects the biocompatibility of the *** surface modification has recently received attention because it can improve the surface properties such as surface chemistry,roughness,topography,corrosion resistance,wear resistance,hydrophilicity,and thus cell response to the surface of the *** composition and microstructures including textures and phases of laser-treated surfaces depend largely on the laser processing parameters(input laser power,laser scan velocity,frequency,pulse duration,pressure,gas circulation,working time,spot size,beam focal position,and laser track overlap)and the thermophysical properties of the substrate(solubility,melting point,and boiling point).This review investigates the impacts of various laser surface modification techniques including laser surface melting,laser surface alloying,laser cladding,laser surface texturing,and laser shock peening,and highlights their significance in improving the surface properties of biodegradable Mg alloys for implant ***,we explore how different laser process parameters affect its composition,microstructure,and surface properties in each laser surface modification technique.

关键词： Biocompatibility Biodegradability Corrosion Implant applications Laser surface modification Magnesium alloys

DDI-Transform:A neural network for predicting drug-drug interaction events

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Quantitative Biology 2024年第2期12卷 155-163页

作者： Jiaming Su ying qian School of Computer Science and Technology Shanghai Frontiers Science Center of Molecule Intelligent SynthesesEast China Normal UniversityShanghaiChina

Drug-drug interaction(DDI)event prediction is a challenging problem,and accurate prediction of DDI events is critical to patient health and new drug ***,many machine learning-based techniques have been proposed for predicting DDI ***,most of the existing methods do not effectively integrate the multidimensional features of drugs and provide poor mitigation of noise to get effective feature *** address these limitations,we propose a DDI-Transform neural network framework for DDI event *** DDI-Transform,we design a drug structure information feature extraction module and a drug bind-protein feature extraction module to obtain multidimensional feature information.A stack of DDI-Transform layers in the DDI-Transform network module are then used for adaptive learning,thus adaptively selecting the effective feature information for *** results show that DDI-Transform can accurately predict DDI events and outperform the state-of-the-art *** on different scale datasets confirm the robustness of the method.

关键词： adaptive learning graph convolutional networks interaction prediction meta-path

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

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China Foundry 2024年第2期21卷 101-115页

作者： Hao-ran Zhou Hao Yang Huai-qian Li ying-chun Ma Sen Yu Jian shi Jing-chang Cheng peng Gao Bo Yu Zhi-quan Miao Yan-peng Wei National Key Laboratory of Advanced Casting Technologies Shenyang Research Institute of Foundry Co.Ltd.CAMShenyang 110022China Department of Mechanical Engineering Tsinghua UniversityBeijing 100084China Key Laboratory of Space Physics Beijing 100076China School of Materials Science and Engineering Nanyang Technological University639798Singapore

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric ***,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high *** learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new *** paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process ***,it introduces the background and significance of machine learning-assisted design in additive manufacturing *** then further delves into the application of machine learning in additive manufacturing,focusing on model design and process ***,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

关键词： additive manufacturing machine learning material design process optimization intersection of disciplines embedded machine learning

An axisymmetric characteristic model for enhancing prediction of centrifugal compressor characteristics

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Chinese Journal of Aeronautics 2024年第4期37卷 203-215页

作者： peng REN Xiangjun FANG Zeyu JIAO ying HAN School of Energy and Power Engineering Beihang UniversityBeijing 100191China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China

Rapid and accurate determination of compressor characteristic maps is essential for the initial design of centrifugal compressors in aircraft power systems. The accuracy of existing methodologies, which rely on combinations of loss models, varies significantly depending on the compressor's geometry and operational range. This variance necessitates substantial experimental or Computational Fluid Dynamics(CFD) data for coefficient calibration. To address this challenge, this study presents an axisymmetric characteristic model for compressor performance assessment. This model incorporates the factors of blade angle, meridional passage area, and the radial deflection angle of meridional streamlines of the compressor. These factors are derived from fundamental aerodynamic equations encompassing mass, momentum, and energy conservation of the compressor. In contrast to conventional one-dimensional approaches, the proposed method reduces the number of loss coefficients and more effectively accounts for the impact of geometric alterations on centrifugal compressor properties. Furthermore, the model reduces dependence on experimental and CFD data. Efficacy of the model is validated using experimental data from four distinct types of centrifugal compressors. Correlation analysis reveals that the model's coefficients can be expressed as functions of the ratio of the Reynolds number to the impeller tip speed. This ratio serves as a characteristic parameter for the design and optimization of centrifugal compressors. Consequently, the proposed method offers an efficient and accurate means for the quick computation of centrifugal compressor characteristics. This is of great significance for improving the efficiency of centrifugal compressors and reducing energy consumption.

关键词： Centrifugal compressor Positive problem Characteristic prediction Aerodynamic characteristic Axisymmetric model