Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.

Introduction: Stroke patients are at high risk of developing cerebral edema, which can have severe consequences. However, there are currently few effective tools for early identification or prediction of this risk. As machine learning (ML) is increasingly used in clinical practice, its effectiveness in predicting cerebral edema risk in stroke patients has been explored.

Periodontal ligament cells-derived exosomes promote osteoclast differentiation via modulating macrophage polarization.

Several studies have demonstrated that exosomes (Exos) are involved in the regulation of macrophage polarization and osteoclast differentiation. However, the characteristics as well as roles of exosomes from human periodontal ligament cells (hPDLCs-Exos) in M1/M2 macrophage polarization and osteoclast differentiation remain unclear. Here, periodontal ligament cells were successfully extracted by method of improved Type-I collagen enzyme digestion.