Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface.

Nifedipine (NIF) is a dihydropyridine calcium channel blocker primarily used to treat conditions such as hypertension and angina. However, its low solubility and low bioavailability limit its effectiveness in clinical practice. Here, we developed a cocrystal prediction model based on Graph Neural Networks (CocrystalGNN) for the screening of cocrystals with NIF. And scoring 50 coformers using CocrystalGNN. To validate the reliability of the model, we used another prediction method, Molecular Electrostatic Potential Surface (MEPS), to verify the prediction results. Subsequently, we performed a second validation using experiments. The results indicate that our model achieved high performance. Ultimately, cocrystals of NIF were successfully obtained and all cocrystals exhibited better solubility and dissolution characteristics compared to the parent drug. This study lays a solid foundation for combining virtual prediction with experimental screening to discover novel water-insoluble drug cocrystals.

Mining the sustainability of takeaway businesses in online food delivery service supply chain.

The online food delivery service supply chain constitutes a crucial element in achieving sustainable development goals. With its prosperity, an increasing number of takeaway businesses are drawn to this sector. As their numbers rise, issues such as profitability resilience, environmental friendliness, and fulfillment of social responsibility emerge, posing potential disruptions to the service supply chain. Against this backdrop, our endeavor is to mine the sustainability of takeaway businesses using the triple bottom line. We propose a two-stage approach involving the Bayesian best-worst method and a data mining technique to derive the weights of sustainability criteria and the clusters of takeaway businesses. Subsequently, a case study is conducted focusing on takeaway businesses on the Ele.me platform in China. The results highlight economic sustainability as the most valued criterion, followed by social and environmental sustainability. Clustering outcomes reveal four distinct levels of sustainability, with a stronger performance in social sustainability compared to environmental and economic dimensions. Further discussions explore the relationship between sustainability levels, cuisine categories, and business size. Consequently, this study suggests an effective approach for advancing sustainability initiatives within the online food delivery service supply chain.

Establishment and comparison of different procedures for modeling intrauterine adhesion in rats: A preliminary study.

The establishment of a stable animal model for intrauterine adhesion (IUA) can significantly enhance research on the pathogenesis and pathological changes of this disease, as well as on the development of innovative therapeutic approaches. In this study, three different modeling methods, including phenol mucilage combined mechanical scraping, ethanol combined mechanical scraping and ethanol modeling alone were designed. The morphological characteristics of the models were evaluated. The underlying mechanisms and fertility capacity of the ethanol modeling group were analyzed and compared to those of the sham surgery group. All three methods resulted in severe intrauterine adhesions, with ethanol being identified as a reliable modeling agent and was subsequently subjected to further evaluation. Immunohistochemistry and RT-PCR results indicated that the ethanol modeling group exhibited an increase in the degree of fibrosis and inflammation, as well as a significant reduction in endometrial thickness, gland number, vascularization, and endometrial receptivity, ultimately resulting in the loss of fertility capacity. The aforementioned findings indicate that the intrauterine perfusion of 95 % ethanol is efficacious in inducing the development of intrauterine adhesions in rats. Given its cost-effectiveness, efficacy, and stability in IUA formation, the use of 95 % ethanol intrauterine perfusion may serve as a novel platform for evaluating innovative anti-adhesion materials and bioengineered therapies.

How does China's big data policy affect the digital economy of cities? Evidence from national big data comprehensive pilot zones.

Based on the panel data of 280 cities in China from 2011 to 2019, this paper examines the effects of big data policies on the digital economy development by using the national big data comprehensive pilot zones as a quasi-natural experiment. The findings of this paper are as follows. First, the big data policy significantly promotes China's digital economy development. Second, cities at a higher administrative level receive higher policy benefits than cities at a lower administrative level. Third, technological innovation and human capital are important ways for the big data policy to improve the development of the digital economy. The conclusions of this paper not only help to assess the effectiveness of big data policies and ensure the efficacy of policy implementation, but also provide policy support for local governments to fully explore the value of data elements and grasp the new opportunities for the digital economy development with the help of the pilot zones.