#AI reads Urine# Exploratory Research on the Urine Proteome in Patients With Diabetic Peripheral Neuropathy

This study is the first to adopt urinary proteomics technology to analyze urine samples from 9 patients with Diabetic Peripheral Neuropathy (DPN) and 11 healthy individuals. A total of 2611 proteins were identified, among which 312 showed significant differences (239 decreased and 73 increased), with a verified reliability exceeding 90%. These differential proteins are enriched in biological processes such as cytoplasmic translation and immune response, as well as signaling pathways including ribosome and metabolic pathways. Some of them are related to the pathogenesis of diabetes and nerve damage, and 22 high-confidence differential proteins (e.g., triokinase/FMN cyclase and bifunctional coenzyme A synthase) can serve as potential diagnostic and therapeutic biomarkers. The study confirms that urinary proteomics can effectively distinguish DPN patients from healthy individuals, featuring advantages of non-invasiveness and convenient sampling, thus providing a new idea for the early screening and monitoring of DPN. However, it has limitations such as a relatively small sample size and lack of independent validation of key biomarkers. Future research needs to expand the sample size and refine disease grouping for further investigation.

International Journal of Endocrinology https://doi.org/10.1155/ije/6652078

Youhe Gao

Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

For earlier AI Reads Urine articles：

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/