Karaokutan I, et al. J Adv Prosthodont. 2015 Feb;7(1):27-31. http://dx.doi.org/10.4047/jap.2015.7.1.27

Ozel GS, et al. J Adv Prosthodont. 2017 Oct;9(5):335-340. https://doi.org/10.4047/jap.2017.9.5.335

This study evaluates the preference rates for smile designs created by professionals or by Artificial Intelligence (AI) among dentists, dentistry students, and laypeople. Four cases with symmetrical and asymmetrical features were selected based on the Facial Flow (FF) concept from the database of the Smile Designer app regarding anatomical facial points. Two smile designs were created for each selected case: one using Artificial Intelligence (AI) and one created manually. An online survey assessed participants’ preferences for the different smile designs. The chi-square test “Pearson’s and Fisher’s exact test (P)” was used to analyze the survey data. A total of 628 people completed the study. Dentists preferred the manually-created smile design for the first three cases. For Case 4, dentists who used the Smile Designer program preferred the manually-created design (55.88%), while those who did not use the program preferred the AI-generated design (55.84%). There was a significant difference in esthetic perception between dentists and dental students (p = 0.001) and between dentists and laypeople (p = 0.001) for Case 1, only between dentists and dental students (p = 0.003) for Case 2, and only between dentists and laypeople (p = 0.001) for Case 3. Furthermore, we found that females (p = 0.007) and orthodontists (p = 0.025) had a higher preference for the AI-generated design in this case compared to males and other dental specialties for Case 3. While age, education level, and clinical experience did not significantly impact dentists’ preference for manually-created or AI-generated smile designs (p > 0.05), our results suggest that there were some differences in preference for Case 3. Overall, our findings suggest that the use of AI-generated smile designs for symmetric faces is acceptable to both dentists and laypeople and can offer time-saving benefits for clinicians.

Background. The surface properties of implants are effective factors for increasing the osseointegration and activity of osteoprogenitor cells. This study compared the stability of dental implants with sandblasted and acid-etched (SLA) and modified surfaces (SLActive) using the resonance frequency analysis (RFA). Methods. In a split-mouth design, 50 dental implants with either SLA surface properties (n=25) or modified (SLActive) surface properties (n=25) were placed in the mandibles of 12 patients with a bilateral posterior edentulous area. Implant stability was measured using RFA (Osstell) at implant placement time and every week for 1, 2, and 3 months before the conventional loading time. Results. One week following the implantation, implant stability increased from 70 to 77.67 for SLA and from 71.67 to 79 for SLActive (P0.05). Conclusions. For both implant surfaces, increased stability was observed over time, with no significant differences between the groups.

Karaokutan I, et al. J Adv Prosthodont. 2022 Apr;14(2):78-87. https://doi.org/10.4047/jap.2022.14.2.78

Objective: This study compared the effects of different surface treatments on the surface roughness ( R _a ), and shear bond strength (SBS) of resin cement to yttria-stabilized tetragonal zirconia (Y-TZP) ceramic and nickel–chromium (Ni–Cr) base metal alloy, respectively. Materials and methods: Thirty disk-shaped specimens (3 mm height and 10 mm diameter) of each material (Y-TZP and Ni–Cr) were prepared. Both zirconia and metal specimens were randomly assigned to three equal groups, according to the surface treatments ( n = 10): sandblasting, sandblasting + Er:YAG laser, and sandblasting + Nd:YAG laser. Resin cement cylinders (4 mm diameter and 3 mm thickness) were placed on each specimen. The SBS tests were performed at a 1 mm per minute crosshead speed through a knife-edge rod after 5000 thermal cycles. The R _a (μm) of the specimens was measured using a profilometer and evaluated topographically by atomic force microscopy and scanning electron microscopy. Analysis of variance, followed by Tukey's honestly significant difference, in addition to the Kruskal–Wallis test, followed by the Mann–Whitney U test, were used for statistical analysis (α = 0.05). Results: Combined sandblasting and laser treatment of the metal groups led to statistically higher R _a values than sandblasting alone ( p < 0.05). For Y-TZP, there were no significant differences between the R _a values of the subgroups ( p > 0.05). The SBS of the sandblasted metal group was significantly higher than the other two laser-irradiated groups, whereas the SBS of sandblasted zirconia was only significantly higher than the Nd:YAG laser-irradiated group ( p < 0.05). Conclusions: Combined laser and sandblasting surface treatments resulted in rougher surfaces than sandblasting alone, especially for the metal specimens. Sandblasting, alone, improved the SBS of resin cement in both metal and zirconia, compared with the laser and sandblasting treatments, combined.