Oral diseases such as dental caries, periodontitis, and oral cancer are prevalent and present significant challenges to global public health. Although these diseases are typically treated through procedures like dental preparation and resin filling, scaling and root planning, or surgical excision, these interventions are often not entirely effective, and postoperative drug therapy is usually required. Traditional drug treatments, however, are limited by factors such as poor drug penetration, significant side effects, and the development of drug resistance. As a result, there is a growing need for novel drug delivery systems that can enhance therapeutic efficacy, reduce side effects, and improve treatment outcomes. In recent years, drug-loaded vesicles, such as liposomes, polymersomes, and extracellular vesicles (EVs), have emerged as promising drug delivery platforms due to their high drug encapsulation efficiency, controlled release properties, and excellent biocompatibility. This review provides an in-depth examination of the characteristics, advantages, and limitations of liposomes, polymersomes, and extracellular vesicles in the context of oral disease treatment. It further explores the reasons for their advantages and limitations and discusses the specific applications, development prospects, and strategies for optimizing these vesicle-based systems for improved clinical outcomes.

Aim: To identify osteoclastogenic macrophage subsets and their regulatory mechanisms in periodontitis. Methods: We integrated single-cell RNA sequencing datasets from human and murine periodontitis to construct a comprehensive macrophage and monocyte atlas. Employing functional enrichment, cell-cell communication, pseudotime, transcription factor, and machine learning analyses, we characterized and selected the specific macrophage subset involved in cell interactions. In vitro and in vivo experiments, including enzyme-linked immunosorbent assay, TRAP staining, micro-CT, qPCR, flow cytometry, and immunofluorescence staining, were performed to dissect the osteoclastogenic potential of specific macrophage subsets and to identify the key pathways. Results: We discovered that the IL7R⁺ macrophage subset possesses significant osteoclast differentiation potential. Our findings indicate that the IL7/IL7R signaling axis facilitates osteoclast differentiation. Genes highly expressed in IL7R⁺ macrophages were identified as strong predictors for periodontitis by machine learning models. In vivo and in vitro experimental validation confirmed an increase in IL7R⁺ macrophages, along with their enhanced osteoclastogenic capacity. confirmed an increase in IL7R⁺ macrophages, along with their osteoclastogenic capacity. The inhibition of the IL7/IL7R signaling pathway was found to mitigate periodontitis progression by impeding osteoclast differentiation. Furthermore, fibroblasts were found to secret IL7 interacting with IL7 receptors on macrophages. Conclusion: Our study identifies IL7R⁺ macrophages as potential osteoclast precursors in periodontitis. We demonstrate that the IL7/IL7R signaling pathway is a critical driver of osteoclast differentiation. Moreover, targeting IL7R is a potential therapeutic strategy to curb periodontitis bone resorption.