Search

Background: JianPiYiFei (JPYF) II granules are a Chinese medicine for the treatment of chronic obstructive pulmonary disease (COPD). However, the main components and underlying mechanisms of JPYF II granules are not well understood. This study aimed to elucidate the potential mechanism of JPYF II granules in the treatment of COPD using network pharmacology, molecular docking, and molecular dynamics simulation techniques. Methods: The active compounds and corresponding protein targets of the JPYF II granules were found using the TCMSP, ETCM, and Uniport databases, and a compound–target network was constructed using Cytoscape3.9.1. The COPD targets were searched for in GEO datasets and the OMIM and GeneCards databases. The intersection between the effective compound-related targets and disease-related targets was obtained, PPI networks were constructed, and GO and KEGG enrichment analyses were performed. Then, molecular docking analysis verified the results obtained using network pharmacology. Finally, the protein–compound complexes obtained from the molecular docking analysis were simulated using molecular dynamics (MD) simulations. Results: The network pharmacological results showed that quercetin, kaempferol, and stigmasterol are the main active compounds in JPYF II granules, and AKT1, IL-6, and TNF are key target proteins. The PI3K/AKT signaling pathway is a potential pathway through which the JPYF II granules affect COPD. The results of the molecular docking analysis suggested that quercetin, kaempferol, and stigmasterol have a good binding affinity with AKT1, IL-6, and TNF. The MD simulation results showed that TNF has a good binding affinity with the compounds. Conclusions: This study identified the effective compounds, targets, and related underlying molecular mechanisms of JPYF II granules in the treatment of COPD through network pharmacology, molecular docking, and MD simulation techniques, which provides a reference for subsequent research on the treatment of COPD.

Based on the data of China’s new energy listed companies, this paper empirically studies the impact of the patent signal on the financing constraints of new energy enterprises and its mechanism. The results show that: (i) Both the invention patent application and the non-invention patent application can play a signaling role to alleviate the financing constraints of new energy enterprises; (ii) Analyst attention plays an intermediary role between the patent signal and the financing constraints of new energy enterprises. Compared with non-invention patents, analyst attention plays a more vital intermediary role on invention patents; (iii) Patent signal can alleviate the financing constraints of new energy enterprises in the growth and maturity stages by increasing analyst attention but has no apparent effect on the recession period; (iv) Compared with non-main board listed and small-scale new energy enterprises, patent signal has a more substantial effect on alleviating the financing constraints of main board listed and large-scale new energy enterprises.

In recent years, bounded distributions have attracted extensive attention. At the same time, various areas involve bounded interval data, such as proportion and ratio. In this paper, we propose a new bounded model, named logistic Truncated exponential skew logistic distribution. Some basic statistical properties of the proposed distribution are studied, including moments, mean residual life function, Renyi entropy, mean deviation, order statistics, exponential family, and quantile function. The maximum likelihood method is used to estimate the unknown parameters of the proposed distribution. More importantly, the applications to three real data sets mainly from the field of engineering science prove that the logistic Truncated exponential skew logistic distribution fits better than other bounded distributions.

The Kumaraswamy distribution is a common type of bounded distribution, which is widely used in agriculture, hydrology, and other fields. In this paper, we use the methods of the likelihood ratio test, modified information criterion, and Schwarz information criterion to analyze the change point of the Kumaraswamy distribution. Simulation experiments give the performance of the three methods. The application section illustrates the feasibility of the proposed method by applying it to a real dataset.