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Tiehua Zhang,Shuning Zhong,Ligang Hou,Yongjun Wang,XiaoJia Xing,Tianzhu Guan,Jie Zhang,Tiezhu Li 고려인삼학회 2020 Journal of Ginseng Research Vol.44 No.5
Background: As the main metabolites of ginsenosides, 20(S, R)-protopanaxadiol [PPD(S, R)] and 20(S, R)-protopanaxatriol [PPT(S, R)] are the structural basis response to a series of pharmacological effects of their parent components. Although the estrogenicity of several ginsenosides has been confirmed, however, the underlying mechanisms of their estrogenic effects are still largely unclear. In this work, PPD(S, R) and PPT(S, R) were assessed for their ability to bind and activate human estrogen receptor α(hERα) by a combination of in vitro and in silico analysis. Methods: The recombinant hERα ligand-binding domain (hERa-LBD) was expressed in E. coli strain. The direct binding interactions of ginsenosides with hERα-LBD and their ERα agonistic potency were investigated by fluorescence polarization and reporter gene assays, respectively. Then, molecular dynamics simulations were carried out to simulate the binding modes between ginsenosides and hERα-LBD to reveal the structural basis for their agonist activities toward receptor. Results: Fluorescence polarization assay revealed that PPD(S, R) and PPT(S, R) could bind to hERα-LBD with moderate affinities. In the dual luciferase reporter assay using transiently transfected MCF-7 cells, PPD(S, R) and PPT(S, R) acted as agonists of hERα. Molecular docking results showed that these ginsenosides adopted an agonist conformation in the flexible hydrophobic ligand-binding pocket. The stereostructure of C-20 hydroxyl group and the presence of C-6 hydroxyl group exerted significant influence on the hydrogen bond network and steric hindrance, respectively. Conclusion: This work may provide insight into the chemical and pharmacological screening of novel therapeutic agents from ginsenosides.
THE IMPACT OF BIG DATA ON BUSINESS MODEL INNOVATION OF TRADITIONAL INDUSTRY
Shenghui Wang,Yuchen Zhang,Tianzhu Li,Jing Fei Long 글로벌지식마케팅경영학회 2016 Global Marketing Conference Vol.2016 No.7
With the rapid development of science and technology, big data has been applied in many fields and has brought commercial revolution[1]. The scientific community generally regards big data as "massive data + complex types of data". Commercial applications are more concerned about big data as an analytical (prediction) method and focus on the potential commercialization of analysis results. All walks of life will produce large amounts of data every day. The transition of data-scale brings huge commercial value, which will certainly bring the innovation of business model[2]. Particularly in the internet and other emerging industries, because they get data more convenient and fast. Like Amason, Facebook, Google etc, they use analysis of big data to innovate their business model for maximizing their profits[3], actually business model refers to "an enterprise’s profitable operation mode plus ways to make money"[4]. So the effectiveness of business model innovation of big data on emerging industries has been remarkable. But the impact of big data on traditional industries is still in the exploratory stage. Traditional industry mainly refers to the labor intensive, manufacturing oriented industries, including the traditional commerce and service industry[5]. Learning from the experience of big data on business model innovation of emerging industries, traditional industries can use big data to subvert the business model and accelerate the transformation and upgrading.
Poly(2-oxazoline)s: synthesis and biomedical applications
Liuxin Yang,Faming Wang,Pengfei Ren,Tianzhu Zhang,Qianli Zhang 한국고분자학회 2023 Macromolecular Research Vol.31 No.5
With the advancement of medical technology, the previous biomedical material platforms have been unable to meet the increasingly diverse application requirements, and the emergence of poly(2-oxazoline)s provides an opportunity to develop the next generation of biomedical materials. The highly tunable structure and function of poly(2-oxazoline)s, with excellent physical and biological properties, have shown great potential for application in the initial exploratory work. Currently, there are a lot of applied studies related to the water solubility, invisibility, and thermoresponsive of poly(2-oxazoline)s, mainly focused on drug delivery, protein modification, gene carriers, anti-fouling interface, cell sheet engineering, and hydrogel. This paper describes the preparation and physicochemical properties of poly(2-oxazoline)s and reviews the recent applications of poly(2-oxazoline)s in the biomedical field.
A Domain-independent Dual-image based Robust Reversible Watermarking
Xuejing Guo,Yixiang Fang,Junxiang Wang,Wenchao Zeng,Yi Zhao,Tianzhu Zhang,Shi Yun-Qing 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.12
Robust reversible watermarking has attracted widespread attention in the field of information hiding in recent years. It should not only have robustness against attacks in transmission but also meet the reversibility of distortion-free transmission. According to our best knowledge, the most recent robust reversible watermarking methods adopt a single image as the carrier, which might lead to low efficiency in terms of carrier utilization. To address the issue, a novel dual-image robust reversible watermarking framework is proposed in this paper to effectively utilize the correlation between both carriers (namely dual images) and thus improve the efficiency of carrier utilization. In the dual-image robust reversible watermarking framework, a two-layer robust watermarking mechanism is designed to further improve the algorithm performances, i.e., embedding capacity and robustness. In addition, an optimization model is built to determine the parameters. Finally, the proposed framework is applied in different domains (namely domain-independent), i.e., Slantlet Transform and Singular Value Decomposition domain, and Zernike moments, respectively to demonstrate its effectiveness and generality. Experimental results demonstrate the superiority of the proposed dual-image robust reversible watermarking framework.