Comparison of conventional mathematical model and machine learning model based on recent advances in mathematical models for predicting diabetic kidney disease.

Previous research suggests that mathematical models could serve as valuable tools for diagnosing or predicting diseases like diabetic kidney disease, which often necessitate invasive examinations for conclusive diagnosis. In the big-data era, there are several mathematical modeling methods, but generally, two types are recognized: conventional mathematical model and machine learning model. Each modeling method has its advantages and disadvantages, but a thorough comparison of the two models is lacking. In this article, we describe and briefly compare the conventional mathematical model and machine learning model, and provide research prospects in this field.

Protein kinase C: A potential therapeutic target for endothelial dysfunction in diabetes.

Protein kinase C (PKC) is a family of serine/threonine protein kinases that play an important role in many organs and systems and whose activation contributes significantly to endothelial dysfunction in diabetes. The increase in diacylglycerol (DAG) under high glucose conditions mediates PKC activation and synthesis, which stimulates oxidative stress and inflammation, resulting in impaired endothelial cell function. This article reviews the contribution of PKC to the development of diabetes-related endothelial dysfunction and summarizes the drugs that inhibit PKC activation, with the aim of exploring therapeutic modalities that may alleviate endothelial dysfunction in diabetic patients.

MicroRNA-126 Regulates Thrombosis Through Endothelial Progenitor Cells.

Thrombosis is a common problem with potentially severe consequences. Endothelial progenitor cells (EPCs) show great potential as a thrombosis therapy due to their angiogenesis-promoting, thrombus-relieving, and anticoagulant functions. However, cell therapies present more clinical challenges than small molecule solutions. MicroRNAs (miRNAs) are small noncoding single-stranded RNAs with wide-ranging regulatory activities. miRNA-126 is highly enriched in EPCs and endothelial cells. Although increasing research showed that mircoRNA-126 (miR-126) can regulate EPC functions through various pathways and cytokines, summaries of these interactions are rare. Therefore, this brief review of recent findings on the relationship between miRNA-126 and EPC function will attempt to clarify the role of miR-126 in thrombosis through regulation of EPCs, with the goal of exploring alternative therapies for thrombotic diseases.