Zobrazeno 1 - 10
of 725
pro vyhledávání: '"Shaofeng Wang"'
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 16, Iss 1, Pp 1-11 (2024)
Abstract Background Diabetes mellitus (DM) and Helicobacter pylori infection (HPI) pose increasing public health challenges in aging societies, sharing common pathophysiological mechanisms, and linked to significant health risks. Our study examines t
Externí odkaz:
https://doaj.org/article/6b0ee8aa226843c88219ec044b8ac2a1
Autor:
Ningyuan Wen, Dingzhong Peng, Xianze Xiong, Geng Liu, Guilin Nie, Yaoqun Wang, Jianrong Xu, Shaofeng Wang, Sishu Yang, Yuan Tian, Bei Li, Jiong Lu, Nansheng Cheng
Publikováno v:
Signal Transduction and Targeted Therapy, Vol 9, Iss 1, Pp 1-13 (2024)
Abstract Cholangiocarcinoma (CCA) is a highly malignant biliary tract cancer with currently suboptimal diagnostic and prognostic approaches. We present a novel system to monitor CCA using exosomal circular RNA (circRNA) via serum and biliary liquid b
Externí odkaz:
https://doaj.org/article/158590e20d8844dca025e9a0305062ed
Publikováno v:
Case Studies in Thermal Engineering, Vol 62, Iss , Pp 105164- (2024)
Underground coal fires, which are widely distributed and cause serious resource waste and environmental hazards, have become a common concern of the international community. This paper aims to reveal the mechanism of coal spontaneous combustion and t
Externí odkaz:
https://doaj.org/article/50e24af127ec4bbe850ca33a4deff2f7
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-18 (2024)
Abstract Background Colorectal cancer (CRC) is the 3rd most common malignancy with the liver being the most common site of metastases. The recurrence rate of colorectal liver metastases (CRLM) after liver resection (LR) is notably high, with an estim
Externí odkaz:
https://doaj.org/article/6745a4a4cdcd4577b0cf12b3f9a89934
Publikováno v:
International Journal of Coal Science & Technology, Vol 10, Iss 1, Pp 1-17 (2023)
Abstract A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines. The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features
Externí odkaz:
https://doaj.org/article/47f27daf1254448ea6382dd5f9834868
Autor:
Qiang Liu, Jie Zhang, Min Liu, Xiaohui Zhang, Lili Zhao, Yuxin Li, Xiaohui Liu, Yong-hui Yu, Wen-wen Zhang, Shaofeng Wang, Xiaoyu Dong, Zhongliang Li, Fengjuan Zhang, Guo Yao, Guohua Liu, Simmy Reddy
Publikováno v:
BMJ Open, Vol 13, Iss 12 (2023)
Background Recently, with the rapid development of the perinatal medical system and related life-saving techniques, both the short-term and long-term prognoses of extremely preterm infants (EPIs) have improved significantly. In rapidly industrialisin
Externí odkaz:
https://doaj.org/article/ef1c2b05e43b4c19aea0f1ca165cd937
Publikováno v:
BMC Cancer, Vol 23, Iss 1, Pp 1-26 (2023)
Abstract Background Malignant tumors of the biliary system are characterized by a high degree of malignancy and strong invasiveness, and they are usually diagnosed at late stages with poor prognosis. For patients with advanced biliary tract cancer, c
Externí odkaz:
https://doaj.org/article/09b22aecb8714add9f53b974f3d5f1e9
Publikováno v:
International Journal of Coal Science & Technology, Vol 10, Iss 1, Pp 1-25 (2023)
Abstract With the large-scale mining of coal resources, the huge economic losses and environmental problems caused by underground coal fires have become increasingly prominent, and the research on the status quo and response strategies of underground
Externí odkaz:
https://doaj.org/article/c6341997b7d546c588bef9319240fa75
Autor:
Fei Shang, Bo Sun, Shaofeng Wang, Yongquan Han, Wenjing Liu, Ning Kong, Yuwu Ba, Fengchun Miao, Zhendong Liu
Publikováno v:
Lubricants, Vol 12, Iss 4, p 125 (2024)
Rolling mill bearings are prone to wear, erosion, and other damage characteristics due to prolonged exposure to rolling forces. Therefore, regular inspection of rolling mill bearings is necessary. Ultrasonic technology, due to its non-destructive nat
Externí odkaz:
https://doaj.org/article/8105a869de5c489f9eaf6fdf77aba728
Autor:
Shaofeng Wang, Shuang Liang, Qiao Chang, Li Zhang, Beiwen Gong, Yuxing Bai, Feifei Zuo, Yajie Wang, Xianju Xie, Yu Gu
Publikováno v:
Diagnostics, Vol 14, Iss 5, p 497 (2024)
Accurate tooth segmentation and numbering are the cornerstones of efficient automatic dental diagnosis and treatment. In this paper, a multitask learning architecture has been proposed for accurate tooth segmentation and numbering in panoramic X-ray
Externí odkaz:
https://doaj.org/article/3802791aa83441f18d8bd0f57e3ac9d8