Direct interaction in digital interactive media and stock performance: Evidence from Panorama.

Media information plays an essential role in the stock market. Recent financial research has verified that media information could shock stock price by influencing investors' expectation. Now, a new type of interactive media, called Digital Interactive Media (DIM), is popular in Chinese stock market and becomes the main channel for investors to understand listed companies. Unlike general news media or investor forums, DIM enables direct interaction between listed companies and investors. In the modern society where digital economy is booming, media information would largely affect investors' decisions. Therefore, it is urgent to use natural language processing (NLP) technology to deconstruct the massive questions and answers (Q&A) interactive information in DIM and extract valuable factors that affect stock prices and stock performances to explore the influence mechanism of digital interactive information on stock performances. This paper firstly uses web crawling technology to obtain approximately 110000 Q&A text information from the digital interactive platform ('Panoramic Network') from 2015 to 2021. Then we use big data text analysis technology and emotional quantification technology to extract valuable influencing factors from the massive text. A Multiple Linear Regression (MLR) model was created to explore specific influence mechanism of digital interactive information on stock price performance. The empirical results show that the emotions implicit in investors' questions do not significantly impact stock performance. However, the emotions and attitudes of the answers by listed companies can significantly affect corresponding stock prices, which indirectly confirms the Proximate Cause Effect of behavioral finance. This effect is particularly evident in the stock prices on the current trading day and the next trading day. In the Robustness Test, this paper replaces dependent variable and adds relevant control variables, and the conclusion remains valid. In the Endogeneity Test, this paper selects sample data before the launch of Panorama Network in 2014 as a comparison, and uses a Difference-in-Difference (DID) model to prove the significant impact of the launch of Panorama Network on Chinese stock market. In the Heterogeneity Test, the paper classifies the market value, region, and industry of listed companies and regressed the sub samples, once again confirming the reliability of the empirical conclusions. The results of Robustness Test, Endogeneity Test, and Heterogeneity Test conducted in this paper all support empirical conclusions.

Protective effects of ginsenoside F2 on isoproterenol-induced myocardial infarction by activating the Nrf2/HO-1 and PI3K/Akt signaling pathways.

BACKGROUND: Ginsenoside F2 (GF2) serves as the principal intestinal metabolite resulting from the oral intake of Panax ginseng and Panax quinquefolius, exhibiting antioxidative, hypolipidemic, antitumor, and anti-inflammatory properties. Nevertheless, its effect on myocardial infarction (MI) is still unknown. PURPOSE: The purpose of this study is to investigate the protective effect and the underlying mechanisms of GF2 against isoproterenol (ISO)-induced MI. METHODS: ISO-induced H9c2 cardiomyocytes and MI rat models were utilized as in vitro and in vivo models to evaluate the impact of anti-MI of GF2. The underlying mechanisms were investigated using a variety of methodologies, including electrocardiography, Western blot analysis, histopathological examination, immunofluorescence, immunohistochemistry, and ELISA techniques. RESULTS: In vivo experiments, our results indicated that GF2 significantly ameliorated ISO-induced electrocardiographic (ECG) abnormalities, myocardial fiber necrosis, rupture, fibrosis of myocardial tissues, and suppressed cardiac enzyme activities. Meanwhile, GF2 notably raised the activity of antioxidant enzymes like CAT, GSH, and SOD. Furthermore, it downregulated Keap1 expression level while upregulating NQO1, Nrf2, and HO-1 expression levels. Additionally, GF2 suppressed the expression of the cleaved caspase-3 and pro-apoptotic protein Bax while promoting the expression of anti-apoptotic proteins Bcl-2, p-PI3K, and p-Akt. TUNEL fluorescence results also demonstrated that GF2 effectively inhibited cardiomyocyte apoptosis. Furthermore, consistent with the results of animal experiments, GF2 considerably attenuated ROS generation, changed apoptosis and mitochondrial function, and reduced oxidative stress in ISO-induced H9c2 cardiomyocytes through activating Nrf2/HO-1 and PI3K/Akt signaling pathways. CONCLUSION: Taken together, GF2 ameliorated MI by preventing cardiocyte apoptosis, oxidative stress, and mitochondrial dysfunction via modulating the Nrf2/HO-1 and PI3K/Akt signaling pathways, showing potential as a treatment strategy for treating MI.