Zobrazeno 1 - 10
of 285
pro vyhledávání: '"Jianxiang LI"'
Autor:
Jin Wang, Jianxiang Li
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
Artificial Intelligence (AI) is revolutionizing public health education through its capacity for intricate analysis of large-scale health datasets and the tailored dissemination of health-related information and interventions. This article conducts a
Externí odkaz:
https://doaj.org/article/908b12320df040dc8f54e9e9f2fbd5ff
Autor:
Jin Wang, Kaifan Liu, Jiawen Li, Hailong Zhang, Xian Gong, Xiangrong Song, Meidan Wei, Yaoyu Hu, Jianxiang Li
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
IntroductionLung cancer, with the highest global mortality rate among cancers, presents a grim prognosis, often diagnosed at an advanced stage in nearly 70% of cases. Recent research has unveiled a novel mechanism of cell death termed disulfidptosis,
Externí odkaz:
https://doaj.org/article/e477d78d71ce45f4803f04f788de1ef5
Publikováno v:
Dianxin kexue, Vol 39, Pp 137-144 (2023)
Location service features are enabled in 5G to allow new and innovative location-based services to be developed for kinds of scenarios and the key performance requirements are identified by 3GPP.Firstly, the planning of location service feature in ea
Externí odkaz:
https://doaj.org/article/6b84bddba69e41fca0bece4aec11906a
Autor:
Jin Wang, Xiangrong Song, Meidan Wei, Lexin Qin, Qingyun Zhu, Shujie Wang, Tingting Liang, Wentao Hu, Xinyu Zhu, Jianxiang Li
Publikováno v:
International Journal of Molecular Sciences, Vol 25, Iss 12, p 6690 (2024)
Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive
Externí odkaz:
https://doaj.org/article/610c61c1726e4e1384e3c34f4da86090
Publikováno v:
Materials, Vol 17, Iss 9, p 2126 (2024)
With the rapid development of the new energy vehicle market, the demand for extruded profiles for battery trays, mainly characterized by significant wall thickness differences in multiple chambers, is increasing, posing new challenges to production a
Externí odkaz:
https://doaj.org/article/49fc822ccb3f4e2f803cff9a73c05086
Autor:
Jin Wang, Kaifan Liu, Jiawen Li, Hailong Zhang, Xian Gong, Xiangrong Song, Meidan Wei, Yaoyu Hu, Jianxiang Li
Publikováno v:
Biomolecules, Vol 14, Iss 2, p 228 (2024)
Mitophagy, a conserved cellular mechanism, is crucial for cellular homeostasis through the selective clearance of impaired mitochondria. Its emerging role in cancer development has sparked interest, particularly in lung adenocarcinoma (LUAD). Our stu
Externí odkaz:
https://doaj.org/article/2ce7ede1126e4bfb9710fbc40f142192
Autor:
Yang Zhao, Dan Xu, Jing Wang, Dandan Zhou, Anlan Liu, Yingying Sun, Yuan Yuan, Jianxiang Li, Weifeng Guo
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Aim: Chaihu-jia-Longgu-Muli-tang (CLM) is derived from “Shang Han Lun” and is traditionally prescribed for treating depression. However, there is still a lack of evidence for its antidepressant effects, and the underlying mechanism is also unclea
Externí odkaz:
https://doaj.org/article/8d543f6196884c1b88a3f4157c8db88f
Publikováno v:
Catalysis Communications, Vol 182, Iss , Pp 106751- (2023)
Low-silicon SAPO-34 was rapidly synthesized with the assistance of citric acid using inexpensive triethylamine as a template. The effects of citric acid on the crystal structure, morphology, and acidity were investigated using XRD, SEM, FT-IR as well
Externí odkaz:
https://doaj.org/article/ed58742476f5408693423987e1aec36d
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 4056-4069 (2023)
Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is one of the most prominent housekeeping proteins and is widely used as an internal control in some semi-quantitative assays. In addition to glycolysis, GAPDH is involved in several cancer-related bio
Externí odkaz:
https://doaj.org/article/2fefd380d2e24b8e985ef86434e1cd5a
Publikováno v:
Vehicles, Vol 4, Iss 4, Pp 1365-1390 (2022)
In this work, a machine learning-based energy management system is developed using a long short-term memory (LSTM) network for fuel cell hybrid buses. The neural network implicitly learns the complex relationship between various factors and the optim
Externí odkaz:
https://doaj.org/article/06ec5d2f481149bcb8f31f4ef24d53f4