Zobrazeno 1 - 10
of 516
pro vyhledávání: '"Yifan, Cheng"'
Autor:
Yifan Cheng, Yuan Lu
Publikováno v:
Bioactive Materials, Vol 43, Iss , Pp 342-375 (2025)
Many chronic diseases have become severe public health problems with the development of society. A safe and efficient healthcare method is to utilize physical stimulus-responsive polymer patches, which may respond to physical stimuli, including light
Externí odkaz:
https://doaj.org/article/4aaaba07b7a64f5896aea17472ac0e3e
Publikováno v:
Journal of Materials Research and Technology, Vol 33, Iss , Pp 683-697 (2024)
This study investigates the effects of cold rolling and annealing on the microstructure, texture, and mechanical properties of FeCoCrNiMn high-entropy alloys. Utilizing vacuum induction melting, the alloy was initially cast into ingots and hot-rolled
Externí odkaz:
https://doaj.org/article/a6f9ccaee8724bc79251048b45a3b8eb
Autor:
Jie Wang, Jiajie Zhou, Yifan Cheng, Shuai Zhao, Ruiqi Li, Chenkai Zhang, Yayan Fu, Longhe Sun, Jun Ren, Daorong Wang
Publikováno v:
World Journal of Surgical Oncology, Vol 22, Iss 1, Pp 1-9 (2024)
Abstract Background The cranial-caudal-medial approach (CCMA) has been proposed for laparoscopic right hemicolectomy nowadays. This study aimed to investigate the safety and oncological efficacy of CCMA in the treatment of right-sided colon cancer co
Externí odkaz:
https://doaj.org/article/7a768cf7807b4d3d84c960b0d6cce8a1
Exploring genetic association of systemic iron status and risk with incidence of diabetic neuropathy
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 16, Iss 1, Pp 1-8 (2024)
Abstract Background Diabetic neuropathy (DN), a frequent complication in individuals with diabetes mellitus (DM), is hypothesized to have a correlation with systemic iron status, though the nature of this relationship remains unclear. This study empl
Externí odkaz:
https://doaj.org/article/99ad84d9b4184f489ee24a1b4741c673
Publikováno v:
BMC Pregnancy and Childbirth, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background The experiences and challenges associated with breastfeeding multiple births can be considerably more complex than those of singletons. Multiple births refer to the delivery of more than one offspring in a single birth event. Emph
Externí odkaz:
https://doaj.org/article/9d5644e9b2b347c990dc986c9d1cfd53
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Results regarding whether it is essential to incorporate genetic variants into risk prediction models for esophageal cancer (EC) are inconsistent due to the different genetic backgrounds of the populations studied. We aimed to ide
Externí odkaz:
https://doaj.org/article/34e0862679814900b7f3bbf75c9b64fd
Autor:
Li-Wen Zhu, Zihao Li, Xiaohong Dong, Huadong Wu, Yifan Cheng, Shengnan Xia, Xinyu Bao, Yun Xu, Runjing Cao
Publikováno v:
Cell Communication and Signaling, Vol 22, Iss 1, Pp 1-17 (2024)
Abstract Background Macrophages are key inflammatory immune cells that orchestrate the initiation and progression of autoimmune diseases. The characters of macrophage in diseases are determined by its phenotype in response to the local microenvironme
Externí odkaz:
https://doaj.org/article/4e9206efbb914d8fb326943ca790ced7
Publikováno v:
AIP Advances, Vol 14, Iss 9, Pp 095305-095305-7 (2024)
We have theoretically and experimentally demonstrated the feasibility of achieving ultra-low dark current in CpBnn type detectors based on a double-barrier InAs/GaSb/AlSb type-II superlattice. By employing a structure that separates the absorption re
Externí odkaz:
https://doaj.org/article/e029f1363b2d4e83abb10ed1b16cd948
Autor:
Yifan Cheng, Qing Li, Guiying Sun, Tiandong Li, Yuanlin Zou, Hua Ye, Keyan Wang, Jianxiang Shi, Peng Wang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-
Externí odkaz:
https://doaj.org/article/c20ce9aca0b44a569c1445451da4792d
Publikováno v:
Cancer Imaging, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of meta
Externí odkaz:
https://doaj.org/article/d2af5ea38c4145c88a2c2f3b7e9f98be