Renal Tissue-Derived Exosomal miRNA-34a in Diabetic Nephropathy Induces Renal Tubular Cell Fibrosis by Promoting the Polarization of M1 Macrophages.

Background: Diabetic nephropathy (DN) is the leading cause of chronic kidney disease, and the activation and infiltration of phagocytes are critical steps of DN. This study aimed to explore the mechanism of exosomes in macrophages and diabetes nephropathy and the role of miRNA-34a, which might provide a new path for treating DN.

Materials And Methods: The DN model was established, and the success of the model establishment was confirmed by detecting general indicators, HE staining, and immunohistochemistry.

Using deep learning-based artificial intelligence electronic images in improving middle school teachers' literacy.

With the rapid development of societal information, electronic educational resources have become an indispensable component of modern education. In response to the increasingly formidable challenges faced by secondary school teachers, this study endeavors to analyze and explore the application of artificial intelligence (AI) methods to enhance their cognitive literacy. Initially, this discourse delves into the application of AI-generated electronic images in the training and instruction of middle school educators, subjecting it to thorough analysis.

The use of deep learning integrating image recognition in language analysis technology in secondary school education.

This work aims to investigate the application of advanced deep learning algorithms and image recognition technologies to enhance language analysis tools in secondary education, with the goal of providing educators with more effective resources and support. Based on artificial intelligence, this work integrates data mining techniques related to deep learning to analyze and study language behavior in secondary school education. Initially, a framework for analyzing language behavior in secondary school education is constructed.