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199 results on '"Xu, Ruixue"'

2. Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

Author

Zeng, Dewen, Li, Mingqi, Ding, Yukun, Xu, Xiaowei, Xie, Qiu, Xu, Ruixue, Fei, Hongwen, Huang, Meiping, Zhuang, Jian, and Shi, Yiyu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Most existing deep learning-based frameworks for image segmentation assume that a unique ground truth is known and can be used for performance evaluation. This is true for many applications, but not all. Myocardial segmentation of Myocardial Contrast Echocardiography (MCE), a critical task in automatic myocardial perfusion analysis, is an example. Due to the low resolution and serious artifacts in MCE data, annotations from different cardiologists can vary significantly, and it is hard to tell which one is the best. In this case, how can we find a good way to evaluate segmentation performance and how do we train the neural network? In this paper, we address the first problem by proposing a new extended Dice to effectively evaluate the segmentation performance when multiple accepted ground truth is available. Then based on our proposed metric, we solve the second problem by further incorporating the new metric into a loss function that enables neural networks to flexibly learn general features of myocardium. Experiment results on our clinical MCE data set demonstrate that the neural network trained with the proposed loss function outperforms those existing ones that try to obtain a unique ground truth from multiple annotations, both quantitatively and qualitatively. Finally, our grading study shows that using extended Dice as an evaluation metric can better identify segmentation results that need manual correction compared with using Dice., Comment: 12 pages

Published
2021

6. Structural dynamics in the evolution of a bilobed protein scaffold

Author

Gouridis, Giorgos, Muthahari, Yusran A., de Boer, Marijn, Griffith, Douglas A., Tsirigotaki, Alexandra, Tassis, Konstantinos, Zijlstra, Niels, Xu, Ruixue, Eleftheriadis, Nikolaos, Sugijo, Yovin, Zacharias, Martin, Dömling, Alexander, Karamanou, Spyridoula, Pozidis, Charalambos, Economou, Anastassios, and Cordes, Thorben

Published
2021

11. Experience and Enlightenment: 'Customer-Oriented' Nine-Stage Major Gifts Management Model of World-Class U.S. Universities

Author

Lin, Chenghua, Xie, Yanjie, and Xu, Ruixue

Abstract

Since the 1990s, "customer orientation" marketing has been widely applied to major gifts management of world-class U.S. universities, forming a donorcentered model for major gifts management. It focuses on donor demands management, relationship cultivation and value creation, which has a major effect on university fundraising and development. Through literature review and case study of the University of Pittsburgh, this study analyzes the major gifts management model of world-class U.S. universities in terms of theory, structure, operation model, and development characteristics. The findings show that there are two important characteristics of the organizational structure of major gifts management in the United States: one is the donation market segmentation and the donor classification management; the other is the refinement of donation management functions. And this paper proposes a nine-stage major gifts management model of world-class U.S. universities, which contains "Definition-Identification- Qualification-Development of Strategy-Cultivation-Solicitation-Negotiation-Acknowledgment -Stewardship." Finally, this paper summarizes the development trend of major gifts management: emphasizing donor's value creation, donor internalization and capitalization, cultivating prospective donors from national to international, moving towards integration of leading capacity building and donor orientation.

Published
2019
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12. Deaggregation of mutant Plasmodium yoelii de-ubiquitinase UBP1 alters MDR1 localization to confer multidrug resistance

Author

Xu, Ruixue, primary, Lin, Lirong, additional, Jiao, Zhiwei, additional, Liang, Rui, additional, Guo, Yazhen, additional, Zhang, Yixin, additional, Shang, Xiaoxu, additional, Wang, Yuezhou, additional, Wang, Xu, additional, Yao, Luming, additional, Liu, Shengfa, additional, Deng, Xianming, additional, Yuan, Jing, additional, Su, Xin-zhuan, additional, and Li, Jian, additional

Published
2024
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13. Influence of PCDH9 (rs9540720) and narcissistic personality traits on the incidence of major depressive disorder in Chinese first-year university students: findings from a 2-year cohort study

Author

Xu, Ruixue, primary, Liu, Zhaorui, additional, Li, Hanyun, additional, Luo, Linlin, additional, Zheng, Yi, additional, Mu, Fuqin, additional, Liu, Yujia, additional, Zhang, Weixin, additional, Zhang, Ying, additional, Wang, Jianli, additional, and Liu, Yan, additional

Published
2024
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19. Human ApoE2 protects mice against Plasmodium berghei ANKA experimental cerebral malaria

Author

Liang, Rui, primary, Rao, Hengjun, additional, Pang, Qin, additional, Xu, Ruixue, additional, Jiao, Zhiwei, additional, Lin, Lirong, additional, Li, Li, additional, Zhong, Li, additional, Zhang, Yixin, additional, Guo, Yazhen, additional, Xiao, Nengming, additional, Liu, Shengfa, additional, Chen, Xiao-Fen, additional, Su, Xin-zhuan, additional, and Li, Jian, additional

Published
2023
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24. Intrinsically stretchable porous liquid–metal conductor for multifunctional electronics applications.

Author

Sun, Xin, Yin, Minghui, Xu, Ruixue, Fu, Zhiwei, Zhu, He, Guo, Qikai, Li, Yang, Li, Chao, Li, Yan, and Qian, Kai

Abstract

As intrinsically stretchable materials for flexible electronics construction, liquid metal (LM) based composite conductors face challenges to achieve a high conductivity with minimum resistance increase due to the large dimensional change and poor wettability under a large tensile strain. To address this issue, a super-stretchable eutectic gallium indium (EGaIn) foamed elastomer composite is prepared with the assistance of a sugar template and O2 plasma treatment, and displays a marginal resistance change of only ∼31.3% under a large strain of 500% due to the reorientation and elongation of the conductive network. The EGaIn conductor exhibits superior properties of a high uptake of LM and conductivity enhancement from ∼2.38 × 104 (0% strain) to ∼2.97 × 105 S m−1 (500% strain) due to the strong capillary force during stretching. This work is a significant step toward high-performance stretchable conductors, demonstrating great potential in multifunctional device development including self-powered nanogenerators, electromagnetic interface (EMI) shielding, and thermal regulators. [ABSTRACT FROM AUTHOR]

Published
2023
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25. The colonic interleukin-19 aggravates the dextran sodium sulfate/stress-induced comorbidities due to colitis and anxiety

Author

Li, Qiongyu, primary, Meng, Fantao, additional, Ma, Xiangxian, additional, Sun, Zhe, additional, Dai, Juanjuan, additional, Liu, Jing, additional, Li, Dan, additional, Cong, Peijia, additional, Xu, Ruixue, additional, Zhao, Di, additional, Wang, Wentao, additional, Wang, Dan, additional, Liu, Cuilan, additional, Wang, Faxiang, additional, Li, Chen, additional, and Lian, Haifeng, additional

Published
2023
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33. Detection Range Enhancement of Stretchable Ultrasensitive Crack‐Based Strain Sensor with Ordered Ag Nanowire Micromeshes for Human Epidermis Monitoring

Author

Xu, Jing, primary, Liu, Jiaxin, additional, Sun, Bowen, additional, Guo, Yihan, additional, Xu, Ruixue, additional, Han, Xu, additional, Hong, Wang, additional, Xu, Yimeng, additional, Zhu, He, additional, Sun, Xin, additional, Fu, Zhiwei, additional, Xiong, Jiaqing, additional, Tao, Jifang, additional, and Qian, Kai, additional

Published
2022
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37. Diverse Substrate Scaffolds by Multicomponent Reactions and Protein Structural Dynamics by Single-molecule FRET

Author

Xu, Ruixue, Dömling, Alex, Economou, Anastassios, Groves, Matthew, and Drug Design

Abstract

This dissertation is scientifically divided into two main parts; Part Ⅰ describes the assessment of diverse substrate scaffolds using multicomponent reaction chemistry. The excellent maneuverability and efficiency of multicomponent reactions combined with high-throughput synthesis allow generating big synthesis data. This enables the deeper exploration of the chemical space in a fast, low-cost, and environment-friendly manner. Further coupling with high-throughput screening methods can lead to an acceleration in the early stage of drug discovery. Part Ⅱ demonstrates that bilobed proteins bearing a common primordial structural core diversified into transcription factors, enzymes, and extra-cytoplasmic transport-related proteins. The reason is that evolutionary modifications primarily at its termini enabled distinct structural dynamics. Substrate-binding domain 2, one of those bilobed proteins, undergoes a large conformational change upon ligand binding. The allosteric coupling of substrate-binding domain 2 is specific to L-glutamine, whereas altering structural dynamics can adapt protein for additional ligands. Understanding the molecular determinants of this specificity and/or intramolecular allosteric communication is critical to understanding protein evolution and the development of therapeutics. Drug design benefits not only from generating extensive compounds libraries but also from a better understanding of drug targets, especially very dynamic ones, since the visible pocket from a PDB structure may not exist.

Published
2022

42. A deep learning approach with temporal consistency for automatic myocardial segmentation of quantitative myocardial contrast echocardiography

Author

Mingqi Li, Xiaowei Xu, Hongwen Fei, Meiping Huang, Qiu Xie, Yu Wang, Yiyu Shi, Dewen Zeng, Xu Ruixue, and Dunliang Ma

Subjects
business.industry, Deep learning, Pattern recognition, Image segmentation, 030204 cardiovascular system & hematology, Convolutional neural network, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Recurrent neural network, Sørensen–Dice coefficient, Test set, Medicine, Radiology, Nuclear Medicine and imaging, Segmentation, Artificial intelligence, Cardiology and Cardiovascular Medicine, business, Cardiac imaging
Abstract

Quantitative myocardial contrast echocardiography (MCE) has been proved to be valuable in detecting myocardial ischemia. During quantitative MCE analysis, myocardial segmentation is a critical step in determining accurate region of interests (ROIs). However, traditional myocardial segmentation mainly relies on manual tracing of myocardial contours, which is time-consuming and laborious. To solve this problem, we propose a fully automatic myocardial segmentation framework that can segment myocardial regions in MCE accurately without human intervention. A total of 100 patients’ MCE sequences were divided into a training set and a test set according to a 7: 3 proportion for analysis. We proposed a bi-directional training schema, which incorporated temporal information of forward and backward direction among frames in MCE sequences to ensure temporal consistency by combining convolutional neural network with recurrent neural network. Experiment results demonstrated that compared with a traditional segmentation model (U-net) and the model considering only forward temporal information (U-net + forward), our framework achieved the highest segmentation precision in Dice coefficient (U-net vs U-net + forward vs our framework: 0.78 ± 0.07 vs 0.79 ± 0.07 vs 0.81 ± 0.07, p

Published
2021

43. Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

Author

Hongwen Fei, Dewen Zeng, Yiyu Shi, Yukun Ding, Jian Zhuang, Mingqi Li, Xu Ruixue, Qiu Xie, Xiaowei Xu, and Meiping Huang

Subjects
Data set, Ground truth, Artificial neural network, Computer science, business.industry, Deep learning, Metric (mathematics), Dice, Segmentation, Pattern recognition, Image segmentation, Artificial intelligence, business
Abstract

Most existing deep learning-based frameworks for image segmentation assume that a unique ground truth is known and can be used for performance evaluation. This is true for many applications, but not all. Myocardial segmentation of Myocardial Contrast Echocardiography (MCE), a critical task in automatic myocardial perfusion analysis, is an example. Due to the low resolution and serious artifacts in MCE data, annotations from different cardiologists can vary significantly, and it is hard to tell which one is the best. In this case, how can we find a good way to evaluate segmentation performance and how do we train the neural network? In this paper, we address the first problem by proposing a new extended Dice to effectively evaluate the segmentation performance when multiple accepted ground truth is available. Then based on our proposed metric, we solve the second problem by further incorporating the new metric into a loss function that enables neural networks to flexibly learn general features of myocardium. Experiment results on our clinical MCE data set demonstrate that the neural network trained with the proposed loss function outperforms those existing ones that try to obtain a unique ground truth from multiple annotations, both quantitatively and qualitatively. Finally, our grading study shows that using extended Dice as an evaluation metric can better identify segmentation results that need manual correction compared with using Dice.

Published
2021

50. Annexin A1 is responsible for ursolic acid mediated anticancer effects on breast cancer stem cells by wnt/β-catenin pathway

Author

fan, shujun, primary, Xu, Ruixue, additional, Zhang, Han, additional, Mao, Jun, additional, Zhang, Qingqing, additional, Lu, Ying, additional, Wang, Mei, additional, Wang, Huaxin, additional, Yu, Xiaotang, additional, Hou, Zhenhuan, additional, Sun, Xu, additional, Wei, Yuanyi, additional, Huang, Yuhong, additional, Wang, Bo, additional, Song, Bo, additional, and Li, Lianhong, additional

Published
2020
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