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1. Web-Based Medical Information Searching by Chinese Patients With Breast Cancer and its Influence on Survival: Observational Study

Author

Li, Yan, Ye, Shan, Zhou, Yidong, Mao, Feng, Guo, Hailing, Lin, Yan, Zhang, Xiaohui, Shen, Songjie, Shi, Na, Wang, Xiaojie, and Sun, Qiang

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe internet allows patients to easily look for health information. However, how Chinese patients with breast cancer use the internet has rarely been investigated, and there is a scarcity of information about the influence of internet use on survival. ObjectiveThis observational study aimed to investigate the details of online medical information searching by Chinese patients with breast cancer and to determine whether internet use has any survival benefits. MethodsPatients who were diagnosed with invasive breast cancer at Peking Union Medical College Hospital between January 2014 and December 2015 were enrolled. We obtained information on their internet-searching behavior and gathered data from the patients’ medical and follow-up records. The associations between internet use and other clinic-pathological factors were analyzed. A Cox proportional-hazards model and the Kaplan-Meier method were used for disease-free survival (DFS) analyses. ResultsA total of 973 patients with invasive breast cancer who underwent definitive surgery took part in the study. Among them, 477 cases (49.0%) performed web-based breast cancer information searching before the initial treatment. A multivariate logistic regression analysis suggested that web-based breast cancer information searching was significantly associated with younger age (odds ratio [OR] 0.95, 95% CI 0.94-0.97, P

Published
2020
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4. Developing Syllabus for Rare Breast Diseases Using the Integrated Multimodality of Case-/Problem-/Resource-Based Learning

Author

YAO Ru, ZHANG Jiahui, LIAN Jie, QU Yang, ZHANG Xinyue, HUANG Xin, GAO Lu, ZHAO Jun, HUANG Li, JIANG Yingzi, LUO Linzhi, SHEN Songjie, MAO Feng, SUN Qiang, PAN Bo, and ZHOU Yidong

Subjects
breast rare diseases, integrated multimodality in medical teaching, case-based learning, problem-based learning, resource-based learning, bibliometrics analysis, Medicine
Abstract

ObjectiveThis study aims at establishing a teaching catalog and content for breast rare diseases and developing the syllabus for the breast rare disease using integrated multimodality of case-/problem-/resource-based learning (CBL+PBL+RBL).MethodsBy conducting bibliometrics co-occurrence analysis, we collected 6291 articles on breast rare disease published from January, 1975 to June, 2024. Additionally, we retrieved the Textbook on Rare Diseases, the Catalog of Chinese Rare Disease, and Second Batch of Rare Disease Catalog and then decided the teaching content.ResultsFrom 16, 387 keywords, 1000 (6.1%) keywords were identified through co-occurrence analysis, including 50(0.3%) candidate diseases. These were classified into three categories: rare primary breast diseases, rare genetic mutation-related diseases associated with breast cancer, and rare systemic multi-system diseases involving the breast. From the candidate list, 20(0.1%) rare primary breast diseases were further selected for their notable clinical teaching significance, and significant multi-systemic diseases affecting the breast, whether related to gene mutations or not. Teaching plans were drafted using a diversified parallel teaching approaches, taking into account the characteristics of different diseases and the focus of different teaching methods.ConclusionsThis study initiated the development of the teaching content for breast rare diseases and developed the teaching syllabus using the CBL+PBL+RBL integrated multi teaching model and targeting each rare breast disease for the critical point for teaching.

Published
2024
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13. Research Progress of Breast Ultrasound in the Screening of Breast Cancer

Author

WANG Yingjiao, WANG Lihong, LI Ruyin, SHEN Songjie, and SUN Qiang

Subjects
breast cancer, ultrasound, screening, contrast-enhanced ultrasound, automatic breast ultrasound system, Medicine
Abstract

Breast cancer has become the most prevalent malignant tumor worldwide. Screening improves the rate of early detection and is important for the treatment and prognosis of breast cancer. Breast ultrasound is a common method for screening breast cancer, which can be used as a complementary screening tool to mammography to improve the rate of detection, or used for screening breast cancer alone. In recent years, the use of new techniques of ultrasound in screening breast cancer such as shear wave elastography and contrast-enhanced ultrasound, are rapidly developing. This article reviewed the research progress of clinical application of breast ultrasound in screening breast cancer.

Published
2022
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14. Interpretation of specification for breast cancer screening, early diagnosis, and treatment management in Chinese women

Author

Ma, Fei, Wu, Jiong, Fu, Li, Li, Anhua, Lan, Bo, Chen, Kexin, Di, Jiangli, Jiang, Yuxin, Li, Jing, Li, Ni, Li, Yexiong, Liu, Peifang, Lu, Jinsong, Niu, Lijuan, Peng, Weijun, Shen, Songjie, Shi, Jufang, Sun, Qiang, Tong, Zhongsheng, Wang, Jing, Wang, Yong, Wang, Shusen, Xie, Yuntao, Ying, Jianming, Zhang, Jin, Zhang, Kai, Zhang, Zhihui, Zheng, Ying, Zhu, Qingli, and Xu, Binghe

Published
2021
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26. Abstract P1-12-03: Antidiarrheal prophylaxis with loperamide for patients with lymph node-negative (N0) or micrometastatic (N1mi), HER2-positive breast cancer who received adjuvant pyrotinib plus nab-paclitaxel: a randomized sub-study of PHAEDRA

Author

Wang, Changjun, primary, Lin, Yan, additional, Zhou, Yidong, additional, Mao, Feng, additional, Guan, Jinghong, additional, Shen, Songjie, additional, Wang, Xuejing, additional, Zhang, Xiaohui, additional, Zhang, Yanna, additional, Pan, Bo, additional, Zhong, Ying, additional, Peng, Li, additional, Li, Yan, additional, Huang, Xin, additional, Xu, Ying, additional, and Sun, Qiang, additional

Published
2023
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35. Comparison of ultrasound and mammography for early diagnosis of breast cancer among Chinese women with suspected breast lesions: A prospective trial

Author

Wang, Yingjiao, primary, Li, Yuechong, additional, Song, Yu, additional, Chen, Chang, additional, Wang, Zhe, additional, Li, Linrong, additional, Liu, Mohan, additional, Liu, Guanmo, additional, Xu, Yali, additional, Zhou, Yidong, additional, Sun, Qiang, additional, and Shen, Songjie, additional

Published
2022
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37. Abstract OT1-12-03: Phase II study of pyrotinib plus nanoparticle albumin-bound (nab)-paclitaxel as adjuvant therapy for lymph node-negative (N0) or micrometastatic (N1mi), HER2-positive early breast cancer (PHAEDRA)

Author

Wang, Changjun, primary, Zhou, Yidong, additional, Lin, Yan, additional, Mao, Feng, additional, Guan, Jinghong, additional, Zhang, Xiaohui, additional, Shen, Songjie, additional, Wang, Xuejing, additional, Zhang, Yanna, additional, Pan, Bo, additional, Zhong, Ying, additional, Peng, Li, additional, Cao, Xi, additional, Yao, Ru, additional, Zhou, Xingtong, additional, Xu, Chi, additional, Xu, Ying, additional, and Sun, Qiang, additional

Published
2022
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38. Additional file 2 of Prognostic significance of different molecular typing methods and immune status based on RNA sequencing in HR-positive and HER2-negative early-stage breast cancer

Author

Ren, Xinyu, Song, Yu, zhang, Yanna, Wu, Huanwen, Chen, Longyun, Pang, Junyi, Zhou, Liangrui, Shen, Songjie, and Liang, Zhiyong

Abstract

Additional file 2: Supplementary table 1. Genes detected in this study. Supplementary table 2. The PAM50 molecular subtype of tumors from patients with local recurrence, distant metastasis, or death.

Published
2022
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39. Additional file 1 of Prognostic significance of different molecular typing methods and immune status based on RNA sequencing in HR-positive and HER2-negative early-stage breast cancer

Author

Ren, Xinyu, Song, Yu, zhang, Yanna, Wu, Huanwen, Chen, Longyun, Pang, Junyi, Zhou, Liangrui, Shen, Songjie, and Liang, Zhiyong

Abstract

Additional file 1: Supplementary Figure S1. ROC curve of immune score. Supplementary Figure S2. Prognosis evaluation of intrinsic subtype of Luminal A, Luminal B and Basal-like subtype of PAM50.

Published
2022
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41. A Stratification-Based Data Collection Scheme in Underwater Acoustic Sensor Networks

Author

Guangjie Han, Tao Yang, Wenbo Zhang, Shen Songjie, and Houbing Song

Subjects
Data collection, Computer Networks and Communications, Water flow, Computer science, Real-time computing, Aerospace Engineering, 020302 automobile design & engineering, 020206 networking & telecommunications, 02 engineering and technology, Propagation delay, Energy consumption, 0203 mechanical engineering, Transmission (telecommunications), Automotive Engineering, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Underwater, Cluster analysis, Wireless sensor network
Abstract

Underwater acoustic sensor networks (UASNs) are widely used in a variety of ocean applications, such as exploring ocean resources or monitoring abnormal ocean environments. However, data collection schemes in UASNs are significantly different from those in wireless sensor networks due to high power consumption, severe propagation delay, and so on. Furthermore, previous research has overlooked practical conditions, such as characteristics of water delamination and energy constraint on autonomous underwater vehicles (AUVs). In this paper, a stratification-based data collection scheme for three-dimensional UASNs is proposed to solve these problems. In this scheme, the network is divided into two layers on the basis of the Ekman drift current model. The upper layer, called the Ekman layer, suffers large water velocity. Thus, nodes in the upper layer will follow the water flow. In this case, we employ a forward set-based multihop forwarding algorithm for data collection. The lower layer suffers small water velocity so that nodes in this layer are considered as relatively static. A neighbor density clustering-based AUV data gathering algorithm is applied in this layer for data collection. By employing different data collection algorithms in different layers, we can integrate the advantages of a multihop transmission scheme and AUV-aided data collection scheme to reduce network consumption and improve network lifetime. The simulation results also confirm the proposed method has good performance.

Published
2018

44. miR-452 Reverses Abnormal Glycosylation Modification of ERα and Estrogen Resistance in TNBC (Triple-Negative Breast Cancer) Through Targeting UGT1A1

Author

Li, Yan, primary, Zhou, Yidong, additional, Mao, Feng, additional, Shen, Songjie, additional, Zhao, Bin, additional, Xu, Yali, additional, Lin, Yan, additional, Zhang, Xiaohui, additional, Cao, Xi, additional, Xu, Ying, additional, Chen, Chang, additional, Zhang, Jinqian, additional, and Sun, Qiang, additional

Published
2020
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47. The impact of pre-existed and SERM-induced non-alcoholic fatty liver disease on breast cancer survival: a meta-analysis

Author

Wang, Changjun, primary, Zhou, Yidong, additional, Huang, Wei, additional, Chen, Ziyuan, additional, Zhu, Hanjiang, additional, Mao, Feng, additional, Lin, Yan, additional, Zhang, Xiaohui, additional, Shen, Songjie, additional, Zhong, Ying, additional, Huang, Xin, additional, Chen, Chang, additional, and Sun, Qiang, additional

Published
2020
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49. Prediction-based delay optimization data collection algorithm for underwater acoustic sensor networks

Author

Mohsen Guizani, Hao Wang, Guangjie Han, Shen Songjie, and Jinfang Jiang

Subjects
data collection delay, Traverse, Data collection, Computer Networks and Communications, Computer science, AUV-aided, Aerospace Engineering, 020302 automobile design & engineering, 02 engineering and technology, Energy consumption, prediction, Cluster (spacecraft), 0203 mechanical engineering, Face (geometry), Kernel (statistics), Automotive Engineering, UASNs, Electrical and Electronic Engineering, Underwater, Cluster analysis, Algorithm
Abstract

The past years have seen a rapid development of autonomous underwater vehicle-aided (AUV-aided) data-gathering schemes in underwater acoustic sensor networks (UASNs). The use of AUVs efficiently reduces energy consumption of sensor nodes. However, all AUV-aided solutions face severe problems in data collection delay, especially in a large-scale network. In this paper, to reduce data collection delay, we propose a prediction-based delay optimization data collection algorithm (PDO-DC). On the contrary to the traditional delay optimization algorithms, Kernel Ridge Regression (KRR) is utilized via cluster member nodes to obtain the corresponding prediction models. Then, the AUV can obtain all cluster data by traversing less cluster head nodes, which can effectively reduce the collection delay of the AUV. The experimental results demonstrate that the proposed method is both feasible and effective. - 2019 IEEE. Manuscript received December 10, 2018; revised March 19, 2019; accepted April 27, 2019. Date of publication May 2, 2019; date of current version July 16, 2019. The work was supported in part by the National Key Research and Development Program, 2018YFC0407900 and in part by the National Natural Science Foundation of China under Grants 61572172, 61602152, and 61872124, and in part by the Open Fund of State Key Laboratory of Acoustics under Grant SKLA201901. The review of this paper was coordinated by Dr. P. Lin. (Corresponding author: Guangjie Han.) G. Han and S. Shen are with the Department of Information and Communication Systems, Hohai University, Changzhou 213022, China (e-mail: hanguangjie@gmail.com; shensongjiehhuc@outlook.com). Scopus

Published
2019

50. Phosphatidylinositol-3,4,5-Trisphosphate Dependent Rac Exchange Factor 1 (PREX1) is a Novel Predictor of Prognosis for Breast Cancer Patients: A Retrospective Case Series

Author

Zhong, Ying, primary, Zhang, Jing, additional, Zhou, Yidong, additional, Mao, Feng, additional, Lin, Yan, additional, Xu, Yali, additional, Guan, Jinghong, additional, Shen, Songjie, additional, Pan, Bo, additional, Wang, Changjun, additional, Peng, Li, additional, Huang, Xin, additional, Li, Yan, additional, Cao, Xi, additional, and Sun, Qiang, additional

Published
2019
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