Background/purpose: Artificial intelligence (AI) is increasingly vital in dentistry, supporting diagnostics, treatment planning, and patient education. However, AI systems face challenges, especially in delivering accurate information within specialized dental fields. This study aimed to evaluate the performance of seven AI-based chatbots (ChatGPT-3.5, ChatGPT-4, Gemini, Gemini Advanced, Claude AI, Microsoft Copilot, and Smodin AI) in correctly answering prosthodontics questions from the Dental Specialty Exam (DUS) in Turkey. The dataset for this study consists of 128 multiple-choice prosthodontics questions from the DUS, a national exam administered in Turkey by the Student Selection and Placement Center (ÖSYM) between 2012 and 2021. Chatbot performance was assessed by categorizing the questions into case-based and knowledge-based. ChatGPT-4 achieved the highest accuracy (75.8 %), while Gemini AI had the lowest (46.1 %). Gemini AI also had more incorrect (69) than correct answers (59). ChatGPT-4 and ChatGPT-3.5 showed significantly higher accuracy in knowledge-based questions compared to case-based ones (p < 0.05). For case-based questions, Gemini and Gemini Advanced had the lowest accuracy (36.4 %), while other chatbots averaged 45.5 %. In knowledge-based questions, ChatGPT-4 performed best (78.6 %) and Gemini AI the worst (47 %). ChatGPT-4 excelled in knowledge-based prosthodontic questions, showing potential to enhance dental education through personalized learning and clinical reasoning support. However, its limitations in case-based scenarios highlight the need for optimization to better address complex clinical situations. These findings suggest that AI models can significantly contribute to dental education and clinical practice.

This study investigated denture care attitudes, dental visit habits, oral mucosal lesions, and hygiene levels in 118 complete denture users treated at a university dentistry faculty. Data on demographics, smoking, denture use duration, dentist visits, and hygiene habits were collected via a questionnaire. A specialist examined mucosal lesions and assessed denture hygiene level using the Budtz-Jorgensen and Bertram method. Categorical data were analyzed with Yates’s correction, Pearson’s chi-square, and Fisher–Freeman–Halton tests; multiple comparisons used the Bonferroni Corrected Z Test. Participants’ mean age was 51.61. Most were non-smokers (55.1%), visited dentists only for complaints (44.9%), cleaned dentures daily (70.3%), and removed them at night (56.8%). Good hygiene was observed in 40.68%. Females cleaned dentures more frequently than males, and 96.3% of those with poor hygiene reported bad denture odor. This study revealed significant deficiencies in denture care habits and inadequate hygiene practices of participants in a university dentistry faculty clinic. Most participants visited dentists only for complaints and had bad habits such as sleeping with their dentures at night and using inappropriate denture hygiene habits. Promoting proper denture hygiene habits and emphasizing the importance of regular dental visits can contribute to better oral health.

Oral Health-Related Quality of Life (OHRQoL) is a term that encompasses conditions such as oral health status, living conditions, and function. OHQoL can change with the varying health conditions of the same individual. Many patients cannot afford implants or have anatomical limitations and therefore use traditional removable dentures. There are comparatively few studies investigating OHRQoL and denture satisfaction that include the patients’ sociodemographic data, denture satisfaction and related questions. This study aimed to investigate OHRQoL and patients’ satisfaction with three types of dentures: upper and lower complete dentures, upper and lower partial dentures, and upper complete lower partial dentures. The study was conducted between January 2022 and June 2023, with 150 patients using removable dentures. Patients’ age, gender, education level, place of residence, smoking status, reasons for tooth loss and visiting the clinic, type of denture and the duration of denture use were recorded. Oral Health Impact Profile (OHIP-14) and patient satisfaction with dentures as measured on a Visual Analog Scale (VAS) were used to assess patients’ satisfactions with OHRQoL and dentures respectively. Descriptive statistics, the Shapiro-Wilk normality test, the Mann-Whitney non‐parametric test and the Kruskal-Wallis test were used. Statistically significant differences were found between gender, prosthetic type, usage duration and OHIP and VAS scores (p < 0.05). Women’s OHIP scores were higher than men’s, patients using complete dentures had higher scores than those using partial dentures in both jaws, those using dentures for less than 1 year had higher scores than those that had used them for more than 1 year. The analysis revealed no statistically significant differences in OHIP and VAS scores based on age, education level, and place of residence (p > 0.05). Patients may find it easier to adapt to removable partial dentures compared to complete dentures. Therefore, in prosthetic planning, dentists should prioritize preserving existing teeth. Regardless of the type of prosthesis, patients adapt to their prostheses over time, leading to increased satisfaction with prolonged use. Since individuals do not have a habit of visiting the dentist when there is no known problem, dentists should encourage patients to attend regular dental check-ups.

The aim of this study was to compare the performance of denture base materials produced by three-dimensional (3D) printing and conventional methods in terms of their mechanical durability and water absorption and solubility properties. Conventional polymethyl methacrylate (PMMA) samples (Meliodent, Heraeus Kulzer, Germany) were prepared using the pressing technique. PowerResins (3BFAB Technology, Inc., Istanbul, Turkey) was used to produce the 3D printed denture base samples. The 3D printed samples were designed using Meshmixer software (Autodesk, Inc.) and printed on a DentaFab Sega 3D Printer (DentaFab, Istanbul, Turkey). Flexural and compressive strength and microhardness tests were conducted to evaluate the mechanical properties of the samples. Water absorption and solubility tests were also performed. The flexural and compressive strength and microhardness values ​​of the 3D printed group were higher than those of the conventional group (p < 0.001). The mean water absorption value was lower in the 3D printed group compared to the conventional group, and the difference between these values ​​was statistically significant (p < 0.001). A statistically significant difference was noted between the groups in terms of water solubility ​​(p = 0.003). Our study shows that 3D printing can produce customized and high-precision prosthetic bases while also improving their physical and mechanical properties.

Background. As polyether ether ketone (PEEK) is a relatively new material in dentistry, its bonding properties with regard to dental acrylic base materials are not fully known. To ensure the long-term success of removable dentures with a PEEK framework, the base materials must be well bonded to each other. Objectives. The study aimed to investigate the effects of different kinds of surface roughening treatment on PEEK and acrylic resin bonding. Material and methods. Eighty PEEK specimens ( N = 80) were randomly divided into 5 groups ( n = 16 per group) and subjected to various surface roughening treatment (control, grinding, sandblasting, tribochemical silica coating (CoJet), and sulfuric acid etching). Heat -polymerized acrylic resin was applied to the treated surfaces of the PEEK specimens. The shear bond strength (SBS) test, environmental scanning electron microscopy (ESEM) analysis and three-dimensional (3D) surface topography analysis were performed. The statistical analysis of the data was conducted using the analysis of variance (ANOVA) and Tukey's multiple comparison test. Results. The one-way ANOVA showed significant differences in the SBS values between the groups ( p = 0.001). Sandblasting, tribochemical silica coating and sulfuric acid etching resulted in high SBS values ( p = 0.001). The highest SBS values were observed in the sulfuric acid etching group (8.83 +/- 3.63 MPa), while the lowest SBS values were observed in the control group (3.33 +/- 2.50 MPa). Conclusions. The additional roughening treatment applied to the PEEK surface increases the bond strength with heat -polymerized acrylic resin.