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Science China(Life Sciences) 2023年第5期66卷 893-1066页

作者： Aging Biomarker Consortium Hainan Bao Jiani Cao Mengting Chen Min Chen Wei Chen Xiao Chen Yanhao Chen Yu Chen Yutian Chen Zhiyang Chen Jagadish K Chhetri Yingjie Ding Junlin Feng Jun Guo Mengmeng Guo Chuting He Yujuan Jia Haiping Jiang Ying Jing Dingfeng Li Jiaming Li Jingyi Li Qinhao Liang Rui Liang Feng Liu Xiaoqian Liu Zuojun Liu Oscar Junhong Luo Jianwei Lv Jingyi Ma Kehang Mao Jiawei Nie Xinhua Qiao Xinpei Sun Xiaoqiang Tang Jianfang Wang Qiaoran Wang Siyuan Wang Xuan Wang Yaning Wang Yuhan Wang Rimo Wu Kai Xia Fu-Hui Xiao Lingyan Xu Yingying Xu Haoteng Yan Liang Yang Ruici Yang Yuanxin Yang Yilin Ying Le Zhang Weiwei Zhang Wenwan Zhang Xing Zhang Zhuo Zhang Min Zhou Rui Zhou Qingchen Zhu Zhengmao Zhu Feng Cao Zhongwei Cao Piu Chan Chang Chen Guobing Chen Hou-Zao Chen Jun Chen Weimin Ci Bi-Sen Ding Qiurong Ding Feng Gao Jing-Dong JHan Kai Huang Zhenyu Ju Qing-Peng Kong Ji Li Jian Li Xin Li Baohua Liu Feng Liu Lin Liu Qiang Liu Qiang Liu Xingguo Liu Yong Liu Xianghang Luo Shuai Ma Xinran Ma Zhiyong Mao Jing Nie Yaojin Peng Jing Qu Jie Ren Ruibao Ren Moshi Song Zhou Songyang Yi Eve Sun Yu Sun Mei Tian Shusen Wang Si Wang Xia Wang Xiaoning Wang Yan-Jiang Wang Yunfang Wang Catherine CL Wong Andy Peng Xiang Yichuan Xiao Zhengwei Xie Daichao Xu Jing Ye Rui Yue Cuntai Zhang Hongbo Zhang Liang Zhang Weiqi Zhang Yong Zhang Yun-Wu Zhang Zhuohua Zhang Tongbiao Zhao Yuzheng Zhao Dahai Zhu Weiguo Zou Gang Pei Guang-Hui Liu Aging Biomarker Consortium(ABC) Beijing 100101China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing 100101China State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China Department of Dermatology Xiangya HospitalCentral South UniversityChangsha 410008China Hunan Key Laboratory of Aging Biology Xiangya HospitalCentral South UniversityChangsha 410008China National Clinical Research Center for Geriatric Disorders Xiangya HospitalCentral South UniversityChangsha 410008China Clinic Center of Human Gene Research Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Hubei Clinical Research Center of Metabolic and Cardiovascular Disease Huazhong University of Science and TechnologyWuhan 430022China Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging Huazhong University of Science and TechnologyWuhan 430022China Stem Cell Translational Research Center Tongji HospitalTongji University School of MedicineShanghai 200065China Department of Nuclear Medicine Daping HospitalThird Military Medical UniversityChongqing 400042China CAS Key Laboratory of Nutrition Metabolism and Food SafetyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Shanghai Key Laboratory of Maternal Fetal Medicine Clinical and Translational Research Center of Shanghai First Maternity and Infant HospitalFrontier Science Center for Stem Cell ResearchShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China The Department of Endovascular Surgery The First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China Key Laboratory of Regenerative Medicine of Ministry of Education Institute of Ageing and Regenerative MedicineJ

Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological *** a broad spectrum of aging biomarkers has been developed,their potential uses and limitations remain poorly *** immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research:How old are we?Why do we get old?And how can we age slower?This review aims to address this ***,we summarize our current knowledge of biomarkers developed for cellular,organ,and organismal levels of aging,comprising six pillars:physiological characteristics,medical imaging,histological features,cellular alterations,molecular changes,and secretory *** fulfill all these requisites,we propose that aging biomarkers should qualify for being specific,systemic,and clinically relevant.

关键词： aging senescence biomarker clock

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A Region-Scalable Fitting Model Algorithm Combining Gray Level Difference of Sub-image for AMOLED Defect detection

A Region-Scalable Fitting Model Algorithm Combining Gray Lev...

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IEEE International Conference on Computer and Communication engineering Technology (CCET)

作者： Yufeng Sun Junjun Xiao Shenzhen Engineering Laboratory of Aerospace Detection and Imaging Harbin Institute of Technology (Shenzhen) Shenzhen China

ISBN: (纸本)9781538674383

In this paper, we improve the Region-Scalable Fitting (RSF) model by the gray level difference of sub-image for RSF model's sensitivity to initial contour and slow speed in active matrix organic light emitting diode (AMOLED) defect detection. The gray level difference of sub-image algorithm can only locate the approximate defects area. The Region-Scalable Fitting (RSF) model overcomes the detection difficulty caused by the intensity inhomogeneity, but the local characteristic makes it extremely sensitive to the position of the initial contour curve. To solve this problem, we combine the gray level difference of sub-image algorithm with the RSF model. Firstly, the approximate position of the defects area is found by the gray level difference of sub-image algorithm, and the outline of this approximate defects area is taken as the initial contour curve of the RSF model. Then we implement the RSF model to segment the defects accurately. The experimental results show that the use of gray level difference of sub-image algorithm to locate the initial contour overcomes the disadvantage that the RSF model is sensitive to the initial contour, and improves the detection speed.

关键词： Mathematical model Active matrix organic light emitting diodes Fitting Approximation algorithms Level set Nonhomogeneous media Image segmentation

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Mode coupling in PT-symmetric photonic crystals with a flat band

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Physical Review A 2018年第4期98卷 043844-043844页

作者： Zhenzhen Liu Qiang Zhang Feifei Qin Yuntian Chen Jun Jun Xiao Shenzhen Engineering Laboratory of Aerospace Detection and Imaging College of Electronic and Information Engineering Harbin Institute of Technology (Shenzhen) Shenzhen 518055 China School of Optical and Electronic Information and Wuhan National Laboratory of Optoelectronics Huazhong University of Science and Technology Wuhan China

The exploration of photonic systems embracing the concept of parity-time (PT) symmetry has become highly active in recent years. Studies on this topic potentially have significant technological implications, enabling unidirectional transmission in optical systems with unusual states of light. Here, we investigate the existence of a flat band in a two-dimensional photonic crystal and the consequences in the context of PT symmetry. The flat band is ascribed to a pair of two dipolar states and a monopolar state, which is verified by the proposed coupled mode equations. This flat band is protected by the interactions of these three states; therefore it has tremendous potential to investigate the localized stationary eigenstates, and gives rise to intriguing modulations under the perturbation of gain and loss. Especially, gain-loss configurations predominantly act on the coupling behavior of originally orthogonal states, including thresholdless PT transition, absence, and emergence of PT transition. The gain-loss configurations, together with the flat band, determine the peculiar band structures and the resultant interesting transmission phenomena. By means of coupled mode equations, we disclose the dynamics upon the perturbation of the gain and loss and the wave vector, and show various transmission modulations including unidirectional behavior.

关键词： Photonic crystals Perturbative methods

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High Affinity to Skeleton Rare Earth Doped Nanoparticles for Near-Infrared Ⅱ imaging

High Affinity to Skeleton Rare Earth Doped Nanoparticles for...

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第十一届全国化学生物学学术会议

作者：和树庆 Changfeng Wu Junle Qu Zhen Cheng 南方科技大学 Academy for Advanced Interdisciplinary Studies and Department of Biomedical Engineering Southern University of Science and Technology(SUSTech) Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Optoelectronic EngineeringShenzhen University Molecular Imaging Program at Stanford(MIPS) Bio-X Programand Department of RadiologyCanary Center at Stanford for Cancer Early DetectionStanford University

As a newly non-invasive emerging modality,NIR-Ⅱ fluorescence imaging(1000-1700 nm) has many advantages over conventional visible and NIR-I imaging(700-900 nm).[1-5] Unfortunately,few NIR-Ⅱ fluorophores are suitable for bone ***,we report an NIR-Ⅱ fluorophore based on DSPE-mPEG encapsulated rare earth doped nanoparticles(RENPs@DSPE-mPEG),which shows inherent affinity to bone without linking any targeting ligands,and thus it provides an alternative non-invasive and non-radiation strategy for skeletal system mapping and bone diseases ***,within NIR-Ⅱ window,imaging at longer wavelength(1345 nm) provides higher resolution and signal-to-noise ratio than that imaging at 1064 nm,even though quantum yield at 1064 nm is 2-fold higher than that at 1345 nm.[2] Besides bone imaging,RENPs@DSPE-mPEG show imaging application in blood vessel and lymph ***,RENPs@DSPE-mPEG can be internalized by circulating white blood *** finding may open a window to increase efficient nanoparticle delivery in the fields such as immunotherapy and improve the diagnostic and therapeutic efficacy of cancer-targeted nanoparticles in clinical applications.

关键词： NIR-Ⅱ imaging NIR-Ⅱa imaging Bone imaging Rare earth doped nanoparticles Thrombus

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Corrigendum to 'Thiophene donor for NIR-II fluorescence imaging guided photothermal/photodynamic/chemo combination therapy' [Acta Biomaterialia 127 (2021) 287-297]

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Acta biomaterialia 2022年 142卷 432页

作者： Qiang Liu Jiangwei Tian Ye Tian Qinchao Sun Dan Sun Dewen Liu Feifei Wang Haijun Xu Guoliang Ying Jigang Wang Ali K Yetisen Nan Jiang Artemisinin Research Center Institute of Chinese Materia Medica China Academy of Chinese Medical Sciences Beijing 100700 China Department of Chemistry Stanford University CA 94305 United States. State Key Laboratory of Natural Medicines Jiangsu Key Laboratory of TCM Evaluation and Translational Research School of Traditional Chinese Pharmacy China Pharmaceutical University Nanjing 21198 China. Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering Biomaterials Research Center School of Biomedical Engineering Southern Medical University Guangzhou 510515 China. Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology & Center for Biomedical Optics and Molecular Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. Jiangsu Co-innovation Center of Efficient Processing and Utilization of Forest Resources College of Chemical Engineering Jiangsu Key Lab of Biomass-based Green Fuels and Chemicals Nanjing Forestry University Nanjing 210037 China. Artemisinin Research Center Institute of Chinese Materia Medica China Academy of Chinese Medical Sciences Beijing 100700 China. Jiangsu Co-innovation Center of Efficient Processing and Utilization of Forest Resources College of Chemical Engineering Jiangsu Key Lab of Biomass-based Green Fuels and Chemicals Nanjing Forestry University Nanjing 210037 China. Electronic address: xuhaijun@***. West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu 610041 China Brigham and Women's Hospital Harvard Medical School Cambridge 02139 MA United States. Electronic address: yingguoliang@***. Department of Urology Shenzhen People's Hospital (The First Affiliated Hospital Southern University of Science and Technology) Shenzhen 518020 China. Electronic address: wangjigang@u.nus.edu. Department of Chemical Engineering Imperial College London London SW7 2AZ United Kingdom. School of Engineering and Applied Sciences

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Deep learning methods for lung cancer segmentation in whole-slide histopathology images - The ACDC@lungHP challenge 2019

arXiv

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arXiv 2020年

作者： Li, Zhang Zhang, Jiehua Tan, Tao Teng, Xichao Sun, Xiaoliang Li, Yang Liu, Lihong Xiao, Yang Lee, Byungjae Li, Yilong Zhang, Qianni Sun, Shujiao Zheng, Yushan Yan, Junyu Li, Ni Hong, Yiyu Ko, Junsu Jung, Hyun Liu, Yanling Chen, Yu-Cheng Wang, Ching-Wei Yurovskiy, Vladimir Maevskikh, Pavel Khanagha, Vahid Jiang, Yi Feng, Xiangjun Liu, Zhihong Li, Daiqiang Schüffler, Peter J. Yu, Qifeng Chen, Hui Tang, Yuling Litjens, Geert College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands and ScreenPoint Medical Eindhoven Nijmegen5600 MB Netherlands Pingan Technology Shenzhen China Lunit Inc. Seoul Korea Republic of School of Electrical Engineering and Computer Science Queen Mary University of London London United Kingdom Image Processing Center School of Astronautics Beihang University Beijing102206 China Beijing Advanced Innovation Center for Biomedical Engineering Beijing100191 China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Image Processing Center School of Astronautics Beihang University Beijing102206 China AstLab School of Automatationm Beihang University Beijing China Department of R&D Center Arontier Co. Ltd. Seoul Korea Republic of Frederick National Laboratory United States Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering Graduate institute of Applied Science and Technology National Taiwan University of Science and Technology AI Explore Taipei Taiwan Research Department Sky-chain Global Yekaterinburg Russia Audio Solutions Team Motorola Solutions Inc. PlantationFL United States Second Xiangya Hospital Central South University Changsha China Hunan Biotechnology Ltd. Changsha China Hunan Cancer Hospital Central South University Changsha China Memorial Sloan Kettering Cancer Center United States First Hospital of Changsha City Changsha China Radboud University Medical Center Nijmegen Netherlands

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated using the false positive rate, false negative rate, and DICE coefficient (DC). The DC ranged from 0.7354±0.1149 to 0.8372±0.0858. The DC of the best method was close to the inter-observer agreement (0.8398±0.0890). All methods were based on deep learning and categorized into two groups: multi-model method and single model method. In general, multi-model methods were significantly better (p Copyright © 2020, The Authors. All rights reserved.

关键词： Biological organs

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A label-free bioluminescent sensor for real-time monitoring polynucleotide kinase activity

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Analytical Chemistry 2014年第16期86卷 8481-8488页

作者： Du, Jiao Xu, Qinfeng Lu, Xiaoquan Zhang, Chun-Yang Key Laboratory of Bioelectrochemistry and Environmental Analysis of Gansu Province College of Chemistry and Chemical Engineering Northwest Normal University Lanzhou 730070 China Single-Molecule Detection and Imaging Laboratory Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong 518055 China

Polynucleotide kinase (PNK) plays a crucial role in maintaining the genomic stability of cells and is becoming a potential target in the radio-therapeutic treatment of cancers. The fluorescent method is usually used to measure the PNK activity, but it is impossible to obtain the real-time monitoring without the employment of the labeled DNA probes. Here, we report a label-free bioluminescent sensor for PNK activity assay through real-time monitoring of the phosphorylation-dependent DNA ligation reaction. In this bioluminescent sensor, two hairpin DNA probes with 5′-protruding terminal are designed as the phosphate acceptor, and the widely used phosphate donor of ATP is substituted by dCTP. In the absence of PNK, the ligation reaction cannot be triggered due to the lack of 5′-phosphoryl groups in the probes, and the background signal is negligible. With the addition of PNK, the phosphorylation-ligation reaction of the probes is initiated with the release of AMP, and the subsequent conversion of AMP to ATP leads to the generation of distinct bioluminescence signal. The PNK activity assay can be performed in real time by continuously monitoring the bioluminescence signal. This bioluminescent sensor is much simpler, label-free, cost-effective, and free from the autofluorescence interference of biological matrix, and can be further used for quantitative, kinetic, and inhibition assay. © 2014 American Chemical Society.

关键词： Bioluminescence

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Coded Excitation System for Stationary Target detection Using Multi Segment Coding

Coded Excitation System for Stationary Target Detection Usin...

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2014 International Conference on Industrial engineering and Information Technology

作者： Jie LI Kai ZHAN Pan-pan LIU Xiao-nian HE Zheng-di QIN National-Regional Key Technology Engineering Laboratory of China for Medical Ultrasound Guangdong Province Key Laboratory for Biomedical Information Detection and Ultrasound Imaging Department of Biomedical Engineering Health Science CenterShenzhen University

In ultrasound systems,the analysis of inherent signal-to-noise(SNR) is one of the eternal *** signal improvements of approximately 10 times are theoretically possible for ultrasonic testing(UT) using coded *** applying the coded excitation into the ultrasound pulse-echo system,codes selection is important as the limited time duration of the transmission *** selected code sequences can hardly get a good auto-correlation *** earlier reports,a technique called Truncated Long Code(TLC) was proposed for dynamic signal detection [1][2][3].Good auto-correlation property has been acquired as the parameter estimation time window can be much longer than the single pulse *** this report,we use the same approach to form a multi-segment coding scheme to detect the stationary objects in ultrasound pulse-echo *** importance of this study are to confirm the efficacy of this new scheme and try to find possible uses in biomedical and industrial applications as well.

关键词： Coded excitation,multi-segment coding,pulse-echo,ultrasound system

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The mechanical effects of microbubble oscillation on elastic vessel wall under ultrasonic excitation with different frequencies using finite element method

The mechanical effects of microbubble oscillation on elastic...

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World Congress on Medical Physics and Biomedical engineering

作者： Shen, Y.Y. Wang, T.F. Chen, S.P. Department of Biomedical Engineering Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Biomedical Information Detection and Ultrasound Imaging Nanhai Road No. 3688 Shenzhen China

ISBN: (纸本)9783642293047

It was proposed that the bubble-vessel interaction played important role in the blood brain barrier opening associated with microbubble cavitations. The mechanical effects of microbubble oscillation on elastic vessel wall under ultrasonic excitation with different frequencies are studied by numerical simulation using fluid solid interaction. The natural frequency of microbubble oscillation is larger than that in the infinite liquid surroundings. The compressive circumferential stress with magnitude 300 kPa is not likely to induce brain microvessel endothelial lining disruption. © 2013 Springer-Verlag.

关键词： Finite element method

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Simulation on detection of tissue harmonic motion using pulse-echo ultrasound and adaptive digital sinusoidal filter

Simulation on detection of tissue harmonic motion using puls...

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World Congress on Medical Physics and Biomedical engineering

作者： Diao, X.F. Qin, Z.D. Chen, S.P. Wang, T.F. Shen, Y.Y. Zhang, X.Y. Guangdong Provincial Key Laboratory of Biomedical Information Detection and Ultrasound Imaging Shenzhen 518060 China Department of Biomedical Engineering School of Medicine Shenzhen University Nanhai Ave 3688 Shenzhen China

ISBN: (纸本)9783642293047

The shear wave propagation speed is related to the elasticity and viscosity of the tissue, and can be estimated from phase changes over a short distance traveled. A novel method is proposed to estimate the shear wave velocity using pulse echo ultrasound and adaptive sinusoidal filter. In this work, we deduced the phase information representation of the harmonic motion of the tissue from the ultrasound echoes, the new method was studied using Field-II simulations and the experiment results agree well with the theory. © 2013 Springer-Verlag.

关键词： Tissue

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