Periodontal disease (PD) is a local inflammatory disease with high morbidity, manifesting tissue destruction results from inflammation of the host immune response to bacterial antigens and irritants. The supportive function of connective tissue and skeletal tissue can be jeopardized without prompt and effective intervention, representing the major cause of tooth loss. However, traditional treatments exhibited great limitations, such as low efficacies, causing serious side effects and recurrent inflammatory episodes. As a major defense mechanism, reactive oxygen species (ROS) play important roles in the pathological progression of PD. Antioxidant therapy is widely believed to be an effective strategy for ROS-triggered diseases, including oxidative stress-induced PD. Most antioxidants can only scavenge one or a few limited kinds of ROS and cannot handle all kinds. In addition, current antioxidant nanomaterials present limitations associated with toxicity, low stability, and poor biocompatibility. To this end, we develop ultra-small molybdenum-based nanodots (MoNDs) with strong ROS in oxidative stress-induced PD. To the best of our knowledge, this is the first time that MoNDs have been used for PD. In the present study, MoNDs have shown extremely good therapeutic effects as ROS scavengers. Spectroscopic and in vitro experiments provided strong evidence for the roles of MoNDs in eliminating multiple ROS and inhibiting ROS-induced inflammatory responses. In addition, the mouse model of PD was established and demonstrated the feasibility of MoNDs as powerful antioxidants. It can alleviate periodontal inflammation by scavenging multiple ROS without obvious side effects and exhibit good biocompatibility. Thus, this newly developed nanomedicine is effective in scavenging ROS and inhibiting M1 phenotypic polarization, which provides promising candidates for the treatment of PD.
Keywords: ROS; anti-inflammatory; gingival fibroblasts; molybdenum-based nanodots; periodontal disease.
Copyright © 2022 Chen, Zhao, Liu, Chen, Yang, Zhang, Wang, Zhu, Zhang, Huang and Ai.