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30 results on '"Zhu, Yapei"'

10. Deep Low-Rank and Piecewise-Smooth Constraint Tensor Model for Hyperspectral Anomaly Detection

Author

Feng, Maoyuan, Zhu, Yapei, Yang, Yunxiu, and Shu, Qin

Abstract

Low-rank tensor decomposition and autoencoder (AE) have recently attracted much attention in the hyperspectral anomaly detection field. Although the low-rank tensor decomposition model is self-explainable, a low-rank prior may only partially match real data. In contrast, AE can automatically learn the discriminative features between anomaly and background, whereas AE is not self-explainable. To overcome these problems, a deep low-rank and piecewise-smooth constraint tensor model is proposed for hyperspectral anomaly detection in this article, which makes full use of the low-rank and piecewise-smooth properties of the background tensor in model-driven tensor-based methods and combines the advantage of data-driven AE methods at the same time. Specifically, the background is reconstructed through the AE network, and the tensor nuclear norm (TNN) and total variation (TV) regularization are designed on the network output to make it self-explainable to exploit the low-rank and piecewise-smooth properties of the background in the 3-D. At the same time, an alternating direction method of multipliers (ADMMs)-based approach is given to solve the proposed model, making the low-rank and piecewise-smooth background tensor estimation process and the network training process into two sub-problems. Then, the background can be approximately reconstructed under the constraint of latent priors, while the anomaly is reconstructed with significant reconstruction errors. Finally, the reconstruction errors indicate the anomalous degree. Experimental results validated on several real hyperspectral datasets demonstrate the effectiveness of the proposed algorithm.

Published
2023
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12. Utility Of Plasma circBNC2 As A Diagnostic Biomarker In Epithelial Ovarian Cancer

Author

Hu,Yingchao, Zhu,Yapei, Zhang,Wen, Lang,Jinghe, and Ning,Li

Subjects
endocrine system diseases, OncoTargets and Therapy
Abstract

Yingchao Hu,1 Yapei Zhu,1 Wen Zhang,1 Jinghe Lang,1 Li Ning2 1Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, People’s Republic of China; 2Department of Gynecologic Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People’s Republic of ChinaCorrespondence: Jinghe LangDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, People’s Republic of ChinaFax +86 010 69152893Email langjhpumch@126.comLi NingDepartment of Gynecologic Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People’s Republic of ChinaFax +86 010 69152891Email 18800191533@163.comBackground: Epithelial ovarian cancer (EOC) is the fifth most common cause of cancer death in women. Due to a lacking of early detection method, its five-year survival rate is only 30%. Nevertheless, novel biomarkers for diagnosis remain to be discovered. The potential of microRNA signatures in the diagnosis of EOC has been especially described in recent years. In our previous experiments, we identified that circBNC2 was downregulated in EOC specimens, and was associated with advanced tumor stage and lymph node metastasis (LNM) by performing circRNA-sequencing analysis. The aim of this study was to explore the diagnostic value of circBNC2 in patients with epithelial ovarian cancer (EOC).Methods: Plasma from 249 age and menopause-matched women (83 with EOC; 83 with benign ovarian cyst; 83 were healthy volunteers) was collected prior to surgery. CircBNC2 was analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were analyzed using enzyme-linked immunosorbent assay (ELISA). Receiver operating curve (ROC), the area under the curve (AUC), sensitivity and specificity were estimated.Results: CircBNC2 was downregulated in EOC and had higher ROC AUC in comparing EOC to benign (ROC AUC 0.879, sensitivity 96.4%, specificity 80.7%) or healthy (ROC AUC 0.923, sensitivity 95.2%, specificity 85.5%) cohorts than HE4 (ROC AUC: 0.742, benign cohort; 0.779, healthy cohort) and CA125 (ROC AUC: 0.373, benign cohort; 0.713, healthy cohort). Early stage EOC vs benign (ROC AUC 0.864, sensitivity 92.0%, specificity 80.7%) and healthy (ROC AUC 0.908, sensitivity 92.0%, specificity 85.5%) cohorts could be significantly separated by circBNC2. CircBNC2 performed alike in pre- and postmenopausal women, within EOC compared to the benign or healthy cohort.Conclusion: CircBNC2 is downregulated in EOC (both in tissue and plasma samples) and might present promising novel biomarker for EOC. Further studies are needed to verify our results.Impact: CircBNC2 is downregulated in EOC and warrants investigation in a screening study in females at risk for EOC.Keywords: epithelial ovarian cancer, circular RNA, noncoding RNA, diagnosis, biomarker

Published
2019

13. Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer

Author

Si,Manfei, Zhang,Junji, Cao,Jianzhong, Xie,Zhibo, Shu,Shan, Zhu,Yapei, Lang,Jinghe, Si,Manfei, Zhang,Junji, Cao,Jianzhong, Xie,Zhibo, Shu,Shan, Zhu,Yapei, and Lang,Jinghe

Abstract

Manfei Si,1 Junji Zhang,1 Jianzhong Cao,2 Zhibo Xie,3 Shan Shu,1 Yapei Zhu,1 Jinghe Lang1 1Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Department of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 3Department of Vascular Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People’s Republic of ChinaCorrespondence: Jinghe LangDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Dongcheng District, Beijing 100730, People’s Republic of ChinaTel +86 10 6915 6204Email langjh@hotmail.comPurpose: Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC.Methods: Six datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein–protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed

Published
2019

17. Hybrid stopping model-based fast PU and CU decision for 3D-HEVC texture coding.

Author

Li, Yue, Yang, Gaobo, Zhu, Yapei, Ding, Xiangling, Song, Yun, and Zhang, Dengyong

Abstract

As an extension of High-Efficiency Video Coding (HEVC) standard, 3D-HEVC needs to encode multiple texture views and depth maps, which further increases the computational complexity. To reduce the complexity of dependent texture view coding, a fast prediction unit (PU) and coding unit (CU) decision method is proposed for 3D-HEVC based on hybrid stopping model. The inter-view correlation is used as a priori information to roughly predict the possible optimal PU and CU sizes. Then, by exploiting the encoded posterior information, the rate distortion cost correlation and the code block flag, the optimal PU and CU are further examined as being optimal or not. Experimental results show that the proposed fast PU and CU decision method achieves 52.7% encoding time saving on average with negligible loss of coding efficiency for 3D-HEVC-dependent texture view coding. [ABSTRACT FROM AUTHOR]

Published
2020
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30. Polymer nanoparticle delivery of dichloroacetate and DACH-Pt to enhance antitumor efficacy and lower systemic toxicity

Author

YangThese authors contributed equally to this work., Qiang, Cai, Jing, Sun, Si, Kang, Xiang, Guo, Jing, Zhu, Yapei, Yan, Lesan, Jing, Xiabin, and Wang, Zehua

Abstract

Platinum agents can cause DNA damage and thus induce apoptosis of cancer cells, which has made them the backbone of cancer chemotherapy regimens. However, most cancers will develop drug resistance over the course of treatment. Meanwhile, most tumors meet energy needs largely by aerobic glycolysis (glycolysis in the presence of oxygen, called the Warburg effect), which is related to their resistance to apoptosis. Therefore, we have used a biodegradable polymer carrier to conjugate with DACH-Pt and dichloroacetate, a PDK inhibitor that can reverse the Warburg effect and derepress the resistance to apoptosis, thus sensitizing cancer cells to platinum. The as-prepared polymer–drug conjugates can be assembled into nanoparticles for effective delivery and better synergism. In vitroand in vivostudies revealed that the combination of polymer–DCA and polymer–DACH-Pt are much better than the free drugs administered simultaneously, in terms of both safety and antitumor efficacy.

Published
2016
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