Dalndushe Abdulai

Aims: This study evaluated the quality, accuracy, and readability of responses generated by four Artificial Intelligence (AI) chatbots based on large language models (LLMs): ChatGPT-5.2, Gemini 3, DeepSeek-V3.2, and Grok-4.1, when responding to expert-generated questions in anterior implant dentistry. The aim was to evaluate their potential role as educational and adjunct informational tools in treatment planning and esthetic zone management, while also examining the readability of the generated responses.Methods: Thirty-six standardized questions covering diagnosis, esthetic risk assessment, implant positioning, surgical planning, peri-implant soft tissue management, esthetic complications, and preventive strategies were developed by three prosthodontists experienced in implant dentistry. Responses from ChatGPT, Gemini, DeepSeek, and Grok were independently evaluated by three experts using the modified DISCERN (mDISCERN) score, Global Quality Score (GQS), and a five-point Accuracy Score. Misinformation and Harm scores were also recorded. Repeated-measures comparisons were performed using the Friedman test with Wilcoxon signed-rank post hoc analysis and Bonferroni correction.Results: ChatGPT demonstrated the highest mean scores for informational reliability (mDISCERN: 3.33±0.72) and accuracy (3.56±0.84); however, differences in accuracy were not statistically significant. Gemini showed the highest numerical GQS value (GQS: 3.75±0.77); however, the overall effect size was small, and no GQS pairwise comparison remained statistically significant after adjustment. Grok showed intermediate performance, whereas DeepSeek showed lower numerical reliability scores, with significant pairwise differences identified only in comparison with ChatGPT and Gemini. Significant differences were observed for mDISCERN [χ² (3)=17.52, p0.05). Readability analysis showed a small but statistically significant difference in FRES among the chatbots, with Gemini demonstrating easier readability than Grok after Bonferroni adjustment, whereas FKGL did not differ significantly among the models; overall, the responses required a high-school to early undergraduate reading level.Conclusion: AI chatbots can generate information with potential clinical relevance in anterior implant dentistry; however, variability in informational reliability persists. Although ChatGPT showed slightly higher numerical scores for some outcomes, the observed differences were generally small, and no chatbot demonstrated clear superiority across all evaluated measures. Expert supervision therefore remains essential before integrating such tools into clinical education.

This in vitro study evaluated the effect of post-processing washing duration and printing layer thicknesses on the optical, surface, and mechanical properties of additively manufactured (AM) resins across different resin types. Disc specimens (15-mm diameter × 2-mm thickness) of Saremco Print Crowntec (SC) and VarseoSmile TriniQ (VC) were printed at 50 μm and 100 μm (90° orientation; n = 10/group), ultrasonically washed in 99.9% isopropanol (IPA) for 5, 10, or 15 min, post-cured, and polished. Color coordinates (L*, a*, b*), translucency parameter (TP), surface roughness (Ra), and Vickers hardness (VHN) were measured. The effects of washing duration and layer thickness were analyzed within each resin type using two-way ANOVA and Tukey’s post hoc test (α = 0.05). Washing duration significantly affected the color coordinates of the VC resin at both layer thicknesses ( P < 0.001), and significantly reduced TP values ( P < 0.001). In contrast, the SC resin showed no significant differences in color coordinates or TP across washing durations ( P ≥ 0.178). Surface roughness increased with prolonged washing in VC at 50 μm ( P < 0.001) and in SC at 100 μm ( P < 0.001), while no significant differences were observed in VC at 100 μm ( P = 0.649) or SC at 50 μm ( P = 0.084). Washing duration also reduced Vickers hardness in VC ( P = 0.004), particularly at 50 μm, whereas in SC, hardness was primarily influenced by layer thickness rather than washing duration. These findings indicate that the influence of post-processing washing duration on optical, surface, and mechanical properties is material- and thickness-dependent, highlighting the importance of optimizing washing protocols; however, clinical extrapolation of these results should be interpreted with caution.

Background: This in vitro study evaluated the effect of hydroxyapatite nanoparticle (nano-HAp) incorporation on surface roughness and Vickers hardness of a 3D-printed crown resin after thermocycling. Methods: Disk-shaped specimens (N = 84) were modified and fabricated with 0%, 1%, 2%, and 3% nano-HAp. Surface roughness (Ra) and Vickers hardness (VHN) were measured before and after thermocycling (5000 cycles). Surface morphology was qualitatively assessed using FE-SEM. Data were analyzed using two-way mixed-design ANOVA (α = 0.05). Results: Thermocycling increased surface roughness and reduced hardness in all groups. Ra values were highest in the 3% nano-HAp group after thermocycling (1.16 ± 0.47 µm). Baseline Vickers hardness differed significantly among nano-HAp concentrations, and hardness decreased after thermocycling in all groups; however, the 3% nano-HAp group exhibited the highest post-thermocycling hardness values (24.66 ± 1.51 VHN), which should be interpreted in the context of its higher baseline hardness. FE-SEM observations suggested increased surface irregularities with higher nano-HAp concentrations after thermocycling. Conclusions: Nano-HAp incorporation influenced both surface and mechanical properties, with 3% concentration showing higher hardness after aging but increased roughness.

Hydrolytic degradation and changes in surface roughness may compromise the long-term clinical performance of contemporary restorative resin materials, particularly when different manufacturing techniques are used. This study aimed to evaluate the hydrolytic stability and surface roughness of restorative resin materials manufactured using additive and subtractive techniques by assessing their behavior after water immersion. Disc-shaped specimens (10 mm × 1.5 mm) were prepared for the evaluation of water sorption (Wsp) and water solubility (Wsl) using the same specimens (n = 15 per group), and for surface roughness (Ra) analysis using separate specimens (n = 15 per group). Specimens were fabricated from one nanohybrid resin CAD/CAM block (Lava Ultimate, LU), two indirect laboratory composites (Signum, SI; SR Nexco, NX), and two 3D-printed permanent resins (Formlabs Permanent Crown, FL; Saremco print CROWNTEC, SC), according to the manufacturers’ instructions. All specimens were immersed in distilled water for 24 h, 7 days, 28 days, and 60 days. Water sorption and solubility values (µg/mm³) were calculated after recording mass changes to constant mass. Surface roughness was assessed at baseline and after 60 days of water storage using a white-light interferometric optical profilometer. Two-way ANOVA was used to analyze Wsp and Wsl according to material and storage time, Ra was analyzed using one-way ANOVA for baseline comparisons among materials or two-way robust ANOVA for material- and time-dependent analyses when assumptions of normality and homogeneity of variances were not met (α = 0.05). For water sorption, significant main effects of resin composite material and storage time were observed (p < 0.001), with the highest values recorded for the FL and the lowest values for the LU compared with the other materials. For water solubility, both resin composite material (p = 0.005) and storage time (p < 0.001) showed significant main effects, with the NX differing significantly from the LU and SI. Surface roughness differed significantly among resin composite materials (p < 0.001), whereas storage time did not significantly influence Ra (p = 0.145). The hydrolytic behavior of the investigated resin composite materials was material-dependent. Differences in filler system, resin matrix composition, and manufacturing method significantly affected water sorption and solubility, whereas surface roughness was primarily determined by the material and was not significantly influenced by water storage time under the conditions of this study. The selection of indirect restorative materials has a direct impact on hydrolytic stability. Therefore, for long-term restorations, materials and manufacturing methods associated with lower water sorption and solubility should be prioritized to enhance durability and maintain surface quality in the oral environment.

Aim This study aimed to evaluate the knowledge and awareness of dental students regarding digital dentistry including CAD/CAM systems, 3D-printing technologies, and intraoral scanning. Material and method A descriptive cross-sectional survey was conducted among undergraduate dental students at Biruni University Faculty of Dentistry. The questionnaire consisted of three main sections: demographics, knowledge and awareness of digital dentistry applications. Data were analyzed using descriptive statistics and chi-square tests to determine associations between student’s study level and their level of digital dentistry awareness. Results Of the 307 respondents, 63.8% were female and 36.2% male, mostly aged 20–24 years. Preclinical students represented 74.9% and clinical students 25.1% of participants. General awareness of digital technology in dentistry was 58.5%, while knowledge of CAD/CAM applications (32.7%) and virtual articulators (30.7%) remained limited. Over 70% of students could not identify materials or file formats used in 3D printing or CAD/CAM workflows. A significant relationship was observed between the year of study and digital awareness (χ² = 29.651, p < 0.001), indicating that clinical students were significantly more familiar with digital systems than preclinical students. Conclusion Dental students demonstrated moderate awareness but limited practical knowledge of digital dentistry. Clinical exposure enhanced familiarity with CAD/CAM and 3D-printing technologies. These findings highlight the need for integrating structured digital dentistry education earlier in the dental curriculum to improve technological competence and readiness for modern clinical practice.

This study evaluated the effect of incorporating boric acid (BA) at different concentrations on the flexural strength, color stability, and microhardness of 3D-printed permanent crown resins. Disk-shaped specimens (15 × 2 mm) were fabricated for color stability and Vickers microhardness testing, and bar-shaped specimens (25 × 2 × 2 mm) were prepared for flexural strength evaluation using a masked stereolithography (MSLA) printer. BA was incorporated into the resin at 0% (control), 1%, 2%, and 3% (w/w). Flexural strength (n = 7 per group) was measured using a three-point bending test, microhardness (n = 7 per group) was assessed with the Vickers method, and color stability (n = 22 per group) was evaluated using ΔE₀₀ values at 3 time points: immediately after post-curing (T0), 30 min after post-curing (T1), and 60 min after post-curing (T2). Surface morphology was examined using field-emission scanning electron microscopy (FE-SEM). Data were analyzed using one-way and two-way ANOVA followed by Tukey’s HSD post hoc tests (α = 0.05). BA incorporation significantly affected flexural strength (p < 0.05), with the 3% BA group showing the highest mean value (177.92 ± 38.58 MPa), significantly higher than the control (p = 0.001), 1% (p = 0.002), and 2% (p = 0.011) groups. Microhardness showed an increasing trend with higher BA concentrations but did not reach statistical significance (p > 0.05). Color stability was adversely affected by BA addition (p < 0.001), as ΔE₀₀ values increased progressively from T0 to T2, with the 3% BA group consistently exceeding both perceptibility (ΔE₀₀ > 0.8) and clinical acceptability thresholds (ΔE₀₀ > 1.8) at all time points. BA incorporation enhanced flexural strength in a concentration-dependent manner, while microhardness improvements were not statistically significant, and color stability was compromised at higher concentrations. BA-modified resins may be suitable for posterior restorations where mechanical performance is prioritized.