Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Zhenzhen Ji"'
Publikováno v:
Shipin gongye ke-ji, Vol 45, Iss 16, Pp 102-113 (2024)
To improve the solubility and stability of lutein (LUT), this study utilized the electrostatic self-assembly method to encapsulate LUT within food-grade protein nanoparticles and composite nanoparticles derived from soybean protein isolates (SPI) and
Externí odkaz:
https://doaj.org/article/74512a0ca9564cdb940b72aa63b0fd0e
Autor:
Xinhao Chen, Jian Xing, Chunfa Wu, Chaotuan Zhang, Zhenzhen Ji, Xinjian Liu, Xianju Zhou, Wei Tang
Neuronal intranuclear inclusion disease (NIID) is a slowly progressive neurodegenerative disorder characterized by the presence of eosinophilic intranuclear inclusions in the nervous system and multiple visceral organs. Clinical manifestations of NII
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d5aab705bf1af635d3c55130719e8ef
https://doi.org/10.21203/rs.3.rs-1517964/v1
https://doi.org/10.21203/rs.3.rs-1517964/v1
Publikováno v:
Ann Transl Med
BACKGROUND: Triptolide (PG490), as a triterpene dicyclic oxide has been reported to increase the generation of reactive oxygen species (ROS) and nitric oxide (NO) and induce apoptosis of RAW 264.7 cells in a dose-dependent manner. The activity of dea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f716c38ce5b81ab5cb06c07d3db335cf
https://europepmc.org/articles/PMC8506553/
https://europepmc.org/articles/PMC8506553/
Autor:
Zhenzhen Jiang, Guangqing Cai, Haiting Liu, Leping Liu, Rong Huang, Xinmin Nie, Rong Gui, Jian Li, Jinqi Ma, Ke Cao, Yanwei Luo
Publikováno v:
Journal of Nanobiotechnology, Vol 22, Iss 1, Pp 1-21 (2024)
Abstract Background Combination therapy involving immune checkpoint blockade (ICB) and other drugs is a potential strategy for converting immune-cold tumors into immune-hot tumors to benefit from immunotherapy. To achieve drug synergy, we developed a
Externí odkaz:
https://doaj.org/article/a85048a859814ff5baf461bad2ecc150
Autor:
Tongshuai Liu, Ning Kong, Zhilong Liu, Lei Xi, Xue Hui, Wei Ma, Xuanyang Li, Pu Cheng, Zhenzhen Ji, Zhixiao Yang, Xiao Yang
Publikováno v:
Livestock Science. 265:105080
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa10fe585c0de08673e09656dc6164fa
https://doi.org/10.1016/j.livsci.2022.105080
https://doi.org/10.1016/j.livsci.2022.105080
Publikováno v:
Annals of Noninvasive Electrocardiology, Vol 29, Iss 4, Pp n/a-n/a (2024)
Abstract Background The aim was to evaluate the effect of beta‐blockers (BB) on the response of heart rate (HR) to 6‐min walk test (6MWT) in atrial fibrillation (AF) and whether the AF patients treated with BB have a similar HR response to 6MWT a
Externí odkaz:
https://doaj.org/article/9ce5e9c197d941ebbe81a2538127800d
Publikováno v:
BMC Plant Biology, Vol 24, Iss 1, Pp 1-17 (2024)
Abstract NAC transcription factors are widely distributed in the plant kingdom and play an important role in the response to various abiotic stresses in plant species. Tritipyrum, an octoploid derived from hybridization of Triticum aestivum (AABBDD)
Externí odkaz:
https://doaj.org/article/71f4ff93984f49988a2bc3c184013746
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-7 (2023)
Abstract The question of whether community nucleic acid testing contributes to an increase in infections within residential compounds has not been definitively answered. Shanghai, one of the largest cities in China, conducted city-wide community test
Externí odkaz:
https://doaj.org/article/07f1bdf506614d50ab9dfba7a99fa68b
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 52, Iss , Pp 101691- (2024)
Study region: Dongjiang River Network (DJRN), a complex urbanized river network in the Pearl River Basin, China. Study focus: Low-oxygen conditions have been expanding in urbanized river systems, whereas a clear and quantitative understanding on the
Externí odkaz:
https://doaj.org/article/7283c02da2ab41c89da8cbba3c2ef550
Autor:
Zhenzhen Jiang, Leping Liu, Lin Du, Shanshan Lv, Fang Liang, Yanwei Luo, Chunjiang Wang, Qin Shen
Publikováno v:
Heliyon, Vol 10, Iss 6, Pp e28143- (2024)
Background: Acute respiratory distress syndrome (ARDS) is a fatal outcome of severe sepsis. Machine learning models are helpful for accurately predicting ARDS in patients with sepsis at an early stage. Objective: We aim to develop a machine-learning
Externí odkaz:
https://doaj.org/article/457eaad4a9074242903e0ca9fa088154