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1,611 results on '"Zhu, Yanan"'

2. Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One

Author

Zhang, Hongyuan, Zhu, Yanan, and Li, Xuelong

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Graph neural networks (GNN) suffer from severe inefficiency. It is mainly caused by the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multiple simple modules for more efficient training, which is comprised of classical forward training (FT)and designed backward training (BT). Under the proposed framework, each module can be trained efficiently in FT by stochastic algorithms without distortion of graph information owing to its simplicity. To avoid the only unidirectional information delivery of FT and sufficiently train shallow modules with the deeper ones, we develop a backward training mechanism that makes the former modules perceive the latter modules. The backward training introduces the reversed information delivery into the decoupled modules as well as the forward information delivery. To investigate how the decoupling and greedy training affect the representational capacity, we theoretically prove that the error produced by linear modules will not accumulate on unsupervised tasks in most cases. The theoretical and experimental results show that the proposed framework is highly efficient with reasonable performance., Comment: Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence

Published
2023

3. Molecular mechanism for activation of the 26S proteasome by ZFAND5.

Author

Lee, Donghoon, Zhu, Yanan, Colson, Louis, Wang, Xiaorong, Chen, Siyi, Tkacik, Emre, Huang, Lan, Ouyang, Qi, Goldberg, Alfred, and Lu, Ying

Subjects
ZFAND5, muscle atrophy, proteasome activation, proteasomes, protein degradation, ubiquitin, Animals, Mice, Adenosine Triphosphatases, Cryoelectron Microscopy, Cytoplasm, Proteasome Endopeptidase Complex, DNA-Binding Proteins
Abstract

Various hormones, kinases, and stressors (fasting, heat shock) stimulate 26S proteasome activity. To understand how its capacity to degrade ubiquitylated proteins can increase, we studied mouse ZFAND5, which promotes protein degradation during muscle atrophy. Cryo-electron microscopy showed that ZFAND5 induces large conformational changes in the 19S regulatory particle. ZFAND5s AN1 Zn-finger domain interacts with the Rpt5 ATPase and its C terminus with Rpt1 ATPase and Rpn1, a ubiquitin-binding subunit. Upon proteasome binding, ZFAND5 widens the entrance of the substrate translocation channel, yet it associates only transiently with the proteasome. Dissociation of ZFAND5 then stimulates opening of the 20S proteasome gate. Using single-molecule microscopy, we showed that ZFAND5 binds ubiquitylated substrates, prolongs their association with proteasomes, and increases the likelihood that bound substrates undergo degradation, even though ZFAND5 dissociates before substrate deubiquitylation. These changes in proteasome conformation and reaction cycle can explain the accelerated degradation and suggest how other proteasome activators may stimulate proteolysis.

Published
2023

13. Efficacy and safety of generic pomalidomide plus low-dose dexamethasone in relapsed or refractory multiple myeloma: a multicenter, open-label, single-arm trial

Author

Zhou, Huixing, Wang, Yafei, Chen, Jiao, He, Aili, Jin, Jie, Lu, Quanyi, Zhao, Ying, Li, Junjun, Hou, Ming, Su, Liping, Lai, Xun, Wang, Wei, Liu, Lihong, Ma, Yanping, Gao, Da, Lai, Wenhong, Zhou, Xin, Jing, Hongmei, Zhang, Jinqiao, Yang, Wei, Ran, Xuehong, Lin, Congmeng, Hao, Jianping, Xiao, Taiwu, Huang, Zhenqian, Zhu, Zhigang, Wang, Qing, Fang, Baijun, Wang, Binghua, Song, Yanping, Cai, Zhen, Liu, Bo, Zhu, Yanan, Yang, Xinai, Kang, Xiaoyan, Li, Juan, and Chen, Wenming

Published
2024
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22. Diagnosis and treatment strategies for patients with refractory recurrent aphthous ulcer and systemic diseases

Author

WANG Wenmei, PENG Qiao, WANG Xiang, and ZHU Yanan

Subjects
refractory recurrent aphthous ulcer, systemic diseases, inflammatory bowel disease, iron deficiency anemia, diabetes mellitus, behcer’s disease, reiter’s syndrome, sprue syndrome, sutton syndrome, aids, Medicine
Abstract

Recurrent aphthous ulcer (RAU) is one of the most common diseases of the oral mucosa. At present, no effective method is available for RAU treatment, especially for refractory RAU, which significantly affects patients’ oral health and quality of life. Research shows that combination with systemic diseases greatly increases the difficulty of curing refractory RAU, making conventional oral ulcer treatment harder to perform effectively. This is probably because dentists commonly only focus on handling oral ulcers but neglect to think about the etiology of oral ulcers from a holistic perspective. Thus, we summarized some conditions of refractory RAU accompanied by systemic diseases, including inflammatory bowel disease, iron deficiency anemia, diabetes mellitus, Behçet’s disease, Reiter’s syndrome, sprue syndrome, Sutton syndrome, and acquired immunodeficiency syndrome. We also outlined the treatment principles of these patients. To be specific, on the one hand, dentists should cooperate with the relevant specialists to treat the systemic diseases, while on the other hand they should take measures including topical/general use of medicine, local physical therapy, Traditional Chinese medicine treatment, and psychotherapy for RAU management. This paper aims to provide clinicians with a more comprehensive understanding of the diagnosis and treatment of refractory RAU, in order to make personalized treatment plans for patients and improve the clinical efficacy of refractory RAU.

Published
2023
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37. A Multicenter Study on the Clinical Characteristics and Outcomes Among Children With Moderate to Severe Abusive Head Trauma

Author

Lee, Jan Hau, Liu, Jun, Chor, Yek Kee, Gan, Chin Seng, Ong, Jacqueline, Anantasit, Nattachai, Samransamruajkit, Rujipat, Kurosawa, Hiroshi, Ming, Mei Xiu, Dang, Hongxing, Abbas, Qalab, Lee, Pei-Chuen, Liu, Chunfeng, Kazzaz, Yasser M., González-Dambrauskas, Sebastián, Roa G, Juan D., Fernández-Sarmiento, Jaime, Gómez Arriola, Natalia Elizabeth, Ardila Gómez, Ivan Jose, Jaramillo Bustamante, Juan Camilo, Caporal, Paula, Aparicio, Gabriela, Pantoja Chamorro, Freddy Israel, Terán Miranda, Thelma Elvira, Flores, Marisol Fonseca, Torre Gómez, Rosa Elena de la, Pilar Orive, Francisco Javier, Lasso Palomino, Rubén Eduardo, Watzlawik, Natalia Zita, Yock-Corrales, Adriana, Guier-Bonilla, Luisana, Turina, Deborah M., Rodríguez, María Miñambres, Domínguez Rojas, Jesús Ángel, Domínguez-Rojas, Jesús Ángel, Roa, Juan D., Fernandez-Sarmiento, Jaime, Zhu, Yanan, Kazzaz, Yasser, Dewi, Dianna Sri, and Chong, Shu-Ling

Published
2024
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41. Unsupervised Domain Adaptation Through Transferring both the Source-Knowledge and Target-Relatedness Simultaneously

Author

Tian, Qing, Zhu, Yanan, Ma, Chuang, and Cao, Meng

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Unsupervised domain adaptation (UDA) is an emerging research topic in the field of machine learning and pattern recognition, which aims to help the learning of unlabeled target domain by transferring knowledge from the source domain.

Published
2020

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