Oral cancer (OC), characterized by malignant tumors in the mouth, is one of the most prevalent malignancies worldwide. Chemotherapy is a commonly used treatment for OC; however, it often leads to severe side effects on human bodies. In recent years, nanotechnology has emerged as a promising solution for managing OC using nanomaterials and nanoparticles (NPs). Nano-drug delivery systems (nano-DDSs) that employ various NPs as nanocarriers have been extensively developed to enhance current OC therapies by achieving controlled drug release and targeted drug delivery. Through searching and analyzing relevant research literature, it was found that certain nano-DDSs can improve the therapeutic effect of drugs by enhancing drug accumulation in tumor tissues. Furthermore, they can achieve targeted delivery and controlled release of drugs through adjustments in particle size, surface functionalization, and drug encapsulation technology of nano-DDSs. The application of nano-DDSs provides a new tool and strategy for OC therapy, offering personalized treatment options for OC patients by enhancing drug delivery, reducing toxic side effects, and improving therapeutic outcomes. However, the use of nano-DDSs in OC therapy still faces challenges such as toxicity, precise targeting, biodegradability, and satisfying drug-release kinetics. Overall, this review evaluates the potential and limitations of different nano-DDSs in OC therapy, focusing on their components, mechanisms of action, and laboratory therapeutic effects, aiming to provide insights into understanding, designing, and developing more effective and safer nano-DDSs. Future studies should focus on addressing these issues to further advance the application and development of nano-DDSs in OC therapy.

Objective: Poor conditions in the intraoral environment often lead to low-quality photos and videos, hindering further clinical diagnosis. To restore these digital records, this study proposes a real-time interactive restoration system using segment anything model. Methods: Intraoral digital videos, obtained from the vident-lab dataset through an intraoral camera, serve as the input for interactive restoration system. The initial phase employs an interactive segmentation module leveraging segment anything model. Subsequently, a real-time intraframe restoration module and a video enhancement module were designed. A series of ablation studies were systematically conducted to illustrate the superior design of interactive restoration system. Our quantitative evaluation criteria contain restoration quality, segmentation accuracy, and processing speed. Furthermore, the clinical applicability of the processed videos was evaluated by experts. Results: Extensive experiments demonstrated its performance on segmentation with a mean intersection-over-union of 0.977. On video restoration, it leads to reliable performances with peak signal-to-noise ratio of 37.09 and structural similarity index measure of 0.961, respectively. More visualization results are shown on the https://yogurtsam.github.io/iveproject page . Conclusion: Interactive restoration system demonstrates its potential to serve patients and dentists with reliable and controllable intraoral video restoration.