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935 results on '"H. Luan"'

1. Cardioprotection against experimental myocardial ischemic injury using cornin

Author

Y. Xu, H. Luan, Y. Jiang, X. Tian, and S. Zhang

Subjects
Cornin, Myocardial ischemia and reperfusion, CREB, Akt, Hypoxia, Medicine (General), R5-920, Biology (General), QH301-705.5
Abstract

Phosphorylated-cyclic adenosine monophosphate response element-binding protein (Phospho-CREB) has an important role in the pathogenesis of myocardial ischemia. We isolated the iridoid glycoside cornin from the fruit of Verbena officinalis L, investigated its effects against myocardial ischemia and reperfusion (I/R) injury in vivo, and elucidated its potential mechanism in vitro. Effects of cornin on cell viability, as well as expression of phospho-CREB and phospho-Akt in hypoxic H9c2 cells in vitro, and myocardial I/R injury in vivo, were investigated. Cornin attenuated hypoxia-induced cytotoxicity significantly in H9c2 cells in a concentration-dependent manner. Treatment of H9c2 cells with cornin (10 µM) blocked the reduction of expression of phospho-CREB and phospho-Akt in a hypoxic condition. Treatment of rats with cornin (30 mg/kg, iv) protected them from myocardial I/R injury as indicated by a decrease in infarct volume, improvement in hemodynamics, and reduction of severity of myocardial damage. Cornin treatment also attenuated the reduction of expression of phospho-CREB and phospho-Akt in ischemic myocardial tissue. These data suggest that cornin exerts protective effects due to an increase in expression of phospho-CREB and phospho-Akt.

Published
2016
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27. A Survey on ChatGPT: AI–Generated Contents, Challenges, and Solutions

Author

Yuntao Wang, Yanghe Pan, Miao Yan, Zhou Su, and Tom H. Luan

Subjects
AIGC, generative AI, ChatGPT, security, and privacy, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64
Abstract

With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.

Published
2023
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38. High-entropy induced a glass-to-glass transition in a metallic glass

Author

Hengwei Luan, Xin Zhang, Hongyu Ding, Fei Zhang, J. H. Luan, Z. B. Jiao, Yi-Chieh Yang, Hengtong Bu, Ranbin Wang, Jialun Gu, Chunlin Shao, Qing Yu, Yang Shao, Qiaoshi Zeng, Na Chen, C. T. Liu, and Ke-Fu Yao

Subjects
Science
Abstract

Glass-to-glass transitions can help understanding the glass nature, but it remains difficult to tune metallic glasses into significantly different glass states. Here the authors demonstrate the high-entropy effects in glass-to-glass transitions of high-entropy metallic glasses.

Published
2022
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