Background: Rapid palatal expansion (RPE) is the gold standard for maxillary deficiency in growing patients. Conventional soldered expanders often present challenges in adaptation, chairside procedures and bond stability. This study compares traditional RPEs with customized CAD (Computer Aided Design)/CAM (Computer Aided Manufacturing) expanders regarding clinical efficiency and patient experience. Methods: Thirty growing patients (mean age: 9.2 ± 1.1 years) were allocated to two groups: traditional RPEs (n = 15) and customized CAD/CAM RPEs (n = 15). Outcomes included bond failures, chairside time (from initial try into cementation) and short-term patient-reported discomfort via a 10-point Visual Analogue Scale (VAS) 24 h after appliance placement. Significance was set at p < 0.05. Results: The CAD/CAM group showed significantly fewer bond failures (0.2 ± 0.4 vs. 1.1 ± 0.8; p < 0.05) and shorter chairside time (12.4 ± 2.1 min vs. 24.6 ± 3.8 min; p < 0.001). Patient discomfort was also significantly lower in the CAD/CAM group (VAS: 4.1 ± 1.0 vs. 6.3 ± 1.2; p < 0.05). Conclusions: Within the limitations of this pilot exploratory non-randomized study, customized CAD/CAM RPEs were associated with fewer bond failures, shorter chairside application time, and lower short-term discomfort at 24 h compared with traditional appliances. These preliminary findings should be interpreted with caution and confirmed by larger randomized controlled studies.

Temporomandibular joint (TMJ) dysfunction affects a significant portion of the population and can lead to pain and functional limitations, impacting quality of life. The etiology is multifactorial, requiring multifaceted therapeutic approaches. Nanotechnology, such as the Taopatch® device, offers promising support in pain relief and function improvement. This study evaluates the effect of Taopatch® on mouth opening and TMJ pain relief in both adults and children.

Introduction: During the COVID-19 pandemic, the prolonged use of face masks became necessary for infection control. However, this widespread practice may have unintentionally impacted communication, particularly in children at critical stages of speech and language development. Objective: This study aims to examine parental perceptions regarding the effect of prolonged face-mask use on speech and language development in children aged 2–8 years during the COVID-19 pandemic. Methods: A cross-sectional study was conducted using a 14-item online questionnaire completed voluntarily by parents or legal guardians. The survey explored perceived speech and language changes, recovery following discontinuation of mask use, and whether professional intervention (e.g., speech therapy) was sought. Results: A total of 60 participants were recruited. Language delays were more frequently reported in children under 3 years of age (38%) than in older children (22%). Following the end of mask use, 43.1% of parents reported no change in language development, 29.3% perceived no association, and 27.6% observed improvement. Among those who noticed delays, 30.8% consulted a speech therapist, 61.5% reported spontaneous recovery, and 7.7% reported no recovery. Overall, 77.3% of children showed significant language recovery after stopping mask use, 13.6% recovered partially, and 9.1% did not recover. Conclusion: Parental perceptions suggest that prolonged mask use may have interfered with language development in some children, especially the youngest. While many children improved spontaneously, a notable proportion required professional intervention. These findings highlight the importance of early detection and support for children potentially affected by communication while wearing masks during critical developmental periods. Further research using clinician-assessed measures is needed to validate these perceptions.

Background: General-purpose multimodal artificial intelligence (AI) systems can analyze radiographic images, but their numerical consistency for quantitative orthodontic measurements is unknown. Objective: To compare the inter-model agreement of ChatGPT, Claude, and Grok when estimating standardized Italian Board of Orthodontics (IBO) cephalometric measurements on the same lateral cephalograms. Methods: Twenty pre-existing lateral cephalograms from 20 patients aged 10-60 years were analyzed by ChatGPT, Claude, and Grok with the same standardized prompt. Twelve IBO parameters were requested. Three linear measurements were excluded because metric calibration was not validated, leaving nine angular parameters. Model-specific descriptive statistics, pairwise mean absolute differences (MAD), root mean square error, and two-way absolute-agreement single-measure intraclass correlation coefficients (ICC) were calculated. Friedman tests with Holm correction assessed systematic differences between models. Results: Complete-case sample size ranged from 16 to 20 across angular parameters. ICCs were poor for all nine measurements (0.03-0.26). Pooled pairwise MADs were 2.14 degrees for ChatGPT-Claude, 2.71 degrees for ChatGPT-Grok, and 2.59 degrees for Claude-Grok. No angular parameter showed a statistically significant systematic difference among models after Holm correction. Conclusions: ChatGPT, Claude, and Grok produced broadly similar group-level cephalometric estimates but poor case-level numerical agreement. General-purpose multimodal AI systems should not be considered interchangeable cephalometric measurement tools. Validation against an expert human reference standard is required before clinical use.