Objectives: Artificial intelligence (AI) is increasingly being utilized across various fields of medicine, presenting significant potential for the future of healthcare. This review is to systematically outline the current applications of AI in the field of oral health management and to provide an in-depth analysis of the associated challenges and future opportunities. Methods: The review was based on a systematic electronic literature search conducted across databases (PubMed, Web of Science, and Scopus) with the keywords including “artificial intelligence,” “AI in dentistry,” “tele-dentistry,” “oral health education,” and “oral health management.” English-language studies relevant to the application of AI across various aspects of oral health management were included based on independent assessments by two reviewers. Results: We concluded that in the realm of oral health management, AI technology has diverse applications, including oral health education and counseling, monitoring, screening, diagnosis, treatment, follow-up care of oral diseases, and the collection and management of oral health data. By enhancing public awareness of oral health and improving self-management capabilities, AI can increase diagnostic accuracy, facilitate personalized treatments, support tele-dentistry, optimize the allocation of dental resources, and provide early warnings for oral diseases. These advancements collectively contribute to the efficiency and quality of oral health management. While AI demonstrates considerable promise in this field, several challenges remain, including inconsistencies in oral health data, limited availability and accessibility of data, the reliability of AI-driven results, and issues of bias and fairness in AI algorithms. Addressing these challenges is essential to fully harness the transformative potential of AI in oral health management. Conclusion: Oral health management encompasses the comprehensive handling of oral health risk factors in individuals, populations, and communities through a series of measures and activities aimed at maintaining and promoting oral health. The ultimate goal is to achieve the greatest societal benefit in oral health at the lowest possible cost. By addressing challenges such as data consistency, availability, and reliability, as well as issues of bias and fairness in AI algorithms, AI may play a significant role in oral health management. Clinical relevance: This paper reviews the role of artificial intelligence in the prevention, diagnosis and treatment of oral diseases, providing an important reference for the later application of artificial intelligence in oral health management.

Bone defects, induced by trauma, infection, tumor resection, osteoporosis, and congenital deformities, severely affect patient health both physiologically and psychologically, imposing substantial burdens on healthcare systems and public resources. Bone defect repair involves a complex biological process that orchestrates events such as immune modulation and osteogenic differentiation. Consequently, ideal materials for bone defect regeneration should possess capabilities in both immune regulation and osteogenesis. In this study, we synthesized a kind of covalent organic framework (COF) nanoparticles at room temperature and modified their surface with polydopamine (PDA), resulting in PDA-functionalized COFs (PCOFs). Utilizing the adhesive properties of PDA, we successfully loaded icariin (ICA) onto the PCOFs nanoparticles, forming ICA@PCOFs. Comprehensive characterization techniques, including visual inspection, scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), confirmed the successful synthesis of ICA@PCOFs nanoparticles. Subsequent optimal concentration determination via the CCK-8 assay, and further experiments including alkaline phosphatase (ALP) activity, alizarin red S (ARS) staining, and immunofluorescent staining for osteocalcin (OCN), runt-related transcription factor 2 (Runx2), inducible nitric oxide synthase (iNOS), and mannose receptor (CD206), assessed their capability to modulate macrophage polarization and promote osteogenesis. The results revealed that ICA-loaded nanoparticles demonstrated significant potential in vitro for immune regulation and promoting stem cell osteogenic differentiation. These findings suggest that ICA@PCOFs nanoparticles could represent a promising therapeutic platform for bone defect regeneration, offering dual functionalities in immune modulation and osteogenesis promotion.

Mitochondrial transfer is defined the process through which specific cell types release their mitochondria and subsequently transfer them to unrelated cell types in response to various physiological or pathological stimuli. This process enhances cellular function and alters disease states. Recent research has begun to explore the potential of intercellular mitochondrial transfer as a therapeutic strategy for human diseases. Mitochondrial dysfunction represents a significant pathological alteration in osteoarthritis, and studies indicate that mitochondrial transfer may serve as an effective modulatory treatment approach for osteoarthritis. Mitochondrial transfer, as an innovative subcellular therapeutic technique, presents the advantages of diverse acquisition methods and multiple transmission pathways. This paper aims to summarize the current understanding of the mechanisms of mitochondrial transfer in relation to osteoarthritis, emphasizing the existing research on mitochondrial transfer in osteoarthritis and its potential as a disease-modifying therapy.

Oral ulcers are common, painful lesions that significantly affect quality of life. Certain medications, especially antimetabolites and mTOR inhibitors, have been implicated in their development. However, drug-induced oral ulcers have not been systematically evaluated using large-scale real-world data. The study employed a dual-validation strategy combining pharmacovigilance signal mining and multivariate logistic regression analysis. By querying specific 'preferred terms' (PTs), adverse event reports in the FAERS database of the Food and Drugs Adminstration of USA, related to oral ulcers were identified. Signal detection was conducted using four disproportionality analysis methods. For the initially screened candidate drugs, a multivariate logistic regression model was constructed, adjusting for potential confounders such as age, gender, weight, reporter type, reporting country and year, to further validate their independent association with oral ulcer reports (P_FDR < .05). Reports of oral ulcerations have shown a significant and sustained increase since 2010, peaking in 2020. The multi-method validation framework identified 289 statistically significant drug-oral ulceration association signals. Drugs with the highest signal strength included cyclizine, mycophenolate sodium and aredia. Other drugs with significant signals included lactulose, acetaminophen codeine phosphate, leflunomide, omalizumab, everolimus and atezolizumab. Integrating signal detection results, logistic regression analysis further confirmed that multiple drugs were significantly associated with the risk of oral ulcer reports. Drugs with extremely high odds ratios (ORs) included estriol and docetaxel sagent. Strongly associated drugs also included immunosuppressants, antihistamines, combination analgesics, bisphosphonates, sartans and antibiotics. This study systematically identified approximately 289 drugs significantly associated with oral ulcer risk, including immunosuppressants, cardiovascular drugs and bronchodilators. Based on pharmacovigilance signal detection and regression analysis, patients on long-term treatment with these drugs should receive enhanced oral monitoring. As this is an observational study, further prospective and experimental research is needed to confirm causality.

Objectives: Connexin43 (Cx43) is involved in the inflammation of many tissue types. Dental caries is infectious disease resulting from mineralized tissue dissolution by a specific bacterial population, causing pulp inflammation. However, Cx43's role in dental pulp remains unclear. Here, we investigated the function of Cx43 during pulp inflammation.Materials and Methods: We constructed a dentin injury model in Sprague–Dawley rats to investigate changes in Cx43 expression during pulp inflammation. Cx43 was inhibited in human dental pulp cells (hDPCs) that had been stimulated with lipopolysaccharide (LPS) to investigate the effect of Cx43 on inflammatory response. Promotion of TLR4‐NF‐κB pathway activity and special Cx43 channel inhibitors were used to clarify the function of Cx43 in hDPCs.Results: Dentin injury led to low‐level inflammation in dental pulp. Following dentin injury, Cx43 expression initially decreased before gradually recovering to normal levels. Cx43 inhibition reduced LPS‐induced expression of inflammatory cytokines and NF‐κB pathway activity. Promotion of NF‐κB pathway activity counteracted the effect of Cx43 in hDPCs. Furthermore, inhibition of Cx43 hemichannels reduced LPS‐induced inflammatory cytokine expression.Conclusions: Cx43 is involved in inflammation of dental pulp, while its inhibition reduced LPS‐induced inflammation in hDPCs through NF‐κB pathway via blockage of hemichannels.