Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Wen Hao Xu"'
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-5 (2021)
Abstract Sentinel lymph node biopsy (SLNB) for axillary lymph node staging in early breast cancer has been widely recognized. The combination of radio-colloids and dye method is the best method recognized. The reagents and equipment required in the p
Externí odkaz:
https://doaj.org/article/7e6414c4690a47f5bbe99138c9ecf369
Autor:
Wen-Hao Xu, Hai-Yan Jin, Hua Jin, Xiao-Wei Wang, Fa-Li Jia, Li-Lan Jiang, Xin-Rui Zhao, Zheng-Ri Li
Publikováno v:
Guoji Yanke Zazhi, Vol 23, Iss 8, Pp 1413-1416 (2023)
AIM: To study the correlation between meibomian gland dysfunction(MGD)patients and their sleep quality.METHODS: Retrospective case-control study. A total of 150 MGD patients treated in our hospital from January 2021 to October 2022 were selected and
Externí odkaz:
https://doaj.org/article/8a18ae26b48842a88b5d4ee021e25bd3
Autor:
Yue Wang, Xi Tian, Shu-Xuan Zhu, Wen-Hao Xu, Aihetaimujiang Anwaier, Jia-Qi Su, Hua-Lei Gan, Yuan-Yuan Qu, Jian-Yuan Zhao, Hai-Liang Zhang, Ding-Wei Ye
Publikováno v:
World Journal of Surgical Oncology, Vol 21, Iss 1, Pp 1-16 (2023)
Abstract Background Papillary renal cell carcinoma (PRCC) can be divided into type 1 (PRCC1) and type 2 (PRCC2) and PRCC2 share a more invasive phenotype and worse prognosis. This study aims to identify potential prognostic and therapeutic biomarkers
Externí odkaz:
https://doaj.org/article/f228ab93ead649508c9a11b0d5a11b73
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
Externí odkaz:
https://doaj.org/article/7c705e62c505496c869156d473a53bcd
Autor:
Er-yong Zhang, Dong-guang Wen, Gui-ling Wang, Wei-de Yan, Wen-shi Wang, Cheng-ming Ye, Xu-feng Li, Huang Wang, Xian-chun Tang, Wei Weng, Kuan Li, Chong-yuan Zhang, Ming-xing Liang, Hong-bao Luo, Han-yue Hu, Wei Zhang, Sen-qi Zhang, Xian-peng Jin, Hai-dong Wu, Lin-you Zhang, Qing-da Feng, Jing-yu Xie, Dan Wang, Yun-chao He, Yue-wei Wang, Zu-bin Chen, Zheng-pu Cheng, Wei-feng Luo, Yi Yang, Hao Zhang, En-lai Zha, Yu-lie Gong, Yu Zheng, Chang-sheng Jiang, Sheng-sheng Zhang, Xue Niu, Hui Zhang, Li-sha Hu, Gui-lin Zhu, Wen-hao Xu, Zhao-xuan Niu, Li Yang
Publikováno v:
China Geology, Vol 5, Iss 3, Pp 372-382 (2022)
Hot dry rock (HDR) is a kind of clean energy with significant potential. Since the 1970s, the United States, Japan, France, Australia, and other countries have attempted to conduct several HDR development research projects to extract thermal energy b
Externí odkaz:
https://doaj.org/article/df214afd0c874717b1a08a514a7a09ca
Autor:
Wen-Hao Xu, Shen-Nan Shi, Yue Xu, Jun Wang, Hong-Kai Wang, Da-Long Cao, Guo-Hai Shi, Yuan-Yuan Qu, Hai-Liang Zhang, Ding-Wei Ye
Publikováno v:
Journal of Translational Medicine, Vol 17, Iss 1, Pp 1-14 (2019)
Abstract Background Growing evidence has demonstrated immune reactivity as a confirmed important carcinogenesis and therapy efficacy for clear cell renal cell carcinoma (ccRCC). Aquaporin 9 (AQP9) is involved in many immune-related signals; however,
Externí odkaz:
https://doaj.org/article/44ce66beada0415598bdf1e3e6a5832e
Publikováno v:
Green Chemistry. 25:245-255
New insights into amide-esterification during urethane alcoholysis are presented, and they enable chemical-full-recycling of blended fabric waste.
Autor:
Aihetaimujiang Anwaier, Shu-Xuan Zhu, Xi Tian, Wen-Hao Xu, Yue Wang, Maierdan Palihati, Wei-Yue Wang, Guo-Hai Shi, Yuan-Yuan Qu, Hai-Liang Zhang, Ding-Wei Ye
Publikováno v:
Phenomics. 2:404-418
Autor:
Wen-Hao Xu, Junlong Wu, Jun Wang, Fang-Ning Wan, Hong-Kai Wang, Da-Long Cao, Yuan-Yuan Qu, Hai-Liang Zhang, Ding-Wei Ye
Publikováno v:
Frontiers in Genetics, Vol 10 (2019)
Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify po
Externí odkaz:
https://doaj.org/article/896b01e19672472287dd9d2708ac3fdd
Publikováno v:
Quant Imaging Med Surg
BACKGROUND: To use adversarial training to increase the generalizability and diagnostic accuracy of deep learning models for prostate cancer diagnosis. METHODS: This multicenter study retrospectively included 396 prostate cancer patients who underwen