This study aimed to compare the surface roughness, hardness, and flexure strength of interim indirect resin restorations fabricated with CAD-CAM (CC), 3D printing (3D), and conventional techniques (CV). Twenty disk (3 mm × Ø10 mm) and ten bar specimens (25 × 2 × 2 mm) were fabricated for the CC, 3D, and CV groups, to be used for surface roughness, micro-hardness, and flexural strength testing using standardized protocol. Three indentations for Vickers micro-hardness (VHN) were performed on each disk and an average was identified for each specimen. Surface micro-roughness (Ra) was calculated in micrometers (μm) using a 3D optical non-contact surface microscope. A three-point bending test with a universal testing machine was utilized for assessing flexural strength. The load was applied at a crosshead speed of 3 mm/min over a distance of 25 mm until fracture. Means and standard deviations were compared using ANOVA and post hoc Tukey–Kramer tests, and a p-value of ≤0.05 was considered statistically significant. Ra was significantly different among the study groups (p < 0.05). Surface roughness among the CC and CV groups was statistically comparable (p > 0.05). However, 3D showed significantly higher Ra compared to CC and CV samples (p < 0.05). Micro-hardness was significantly higher in 3D samples (p < 0.05) compared to CC and CV specimens. In addition, CC and CV showed comparable micro-hardness (p > 0.05). A significant difference in flexural strength was observed among the study groups (p < 0.05). CC and 3D showed comparable strength outcomes (p > 0.05), although CV specimens showed significantly lower (p < 0.05) strength compared to CC and 3D samples. The 3D-printed provisional restorative resins showed flexural strength and micro-hardness comparable to CAD-CAM fabricated specimens, and surface micro-roughness for printed specimens was considerably higher compared to CAD-CAM and conventional fabrication techniques.

The aim is to assess the influence of fabrication techniques—conventional (CN), CAD-CAM (CC), and 3D printing (3D)—on the marginal fit, adaptation, surface roughness, and wear of interim restorations of crowns. Thirty interim crowns were fabricated using CN, CC, and 3D techniques. Sixty discs were fabricated to evaluate surface wear and surface roughness properties, with 10 disc samples in each group (n = 10). Internal adaptation and marginal integrity of interim crowns were analyzed with micro CT to detect microgaps at selected points. Average surface micro-roughness (Ra) was calculated in micrometers (μm) using an optical non-contact surface microscope under cyclic loading. Surface wear was evaluated by surface area measurements (mm3) using a micro CT. Analysis of variance (ANOVA) and Tukey’s post hoc comparison tests with Pearson correlation were performed for data analysis. The highest adaptation means were for CN (269.94 ± 64 μm), and the lowest mean value was observed for 3D (197.82 ± 11.72 μm) crowns. CN and CC specimens showed comparable adaptation (p > 0.05), which were significantly higher (p < 0.05) than 3D crowns. CN crowns showed significantly higher marginal misfit compared to 3D (p < 0.05) and CC (p < 0.05) crowns. The highest mean surface roughness was observed in the 3D crowns (5.61 ± 0.33 µm), whereas the lowest was found in CC crowns (3.28 ± 0.34 µm). Better restoration Ra was observed using the CC method followed by CN. CN had the highest wear (17.79 ± 2.78 mm3), and the lowest wear was observed in the 3D (10.81 ± 2.00 mm3) specimen. Low surface wear was observed using 3D printing, followed by CN and CC techniques. The printed specimen showed comparable outcomes to CAD-CAM restoration; however, they were better than CN restoration. A positive correlation between adaptation and surface roughness was observed, indicating an effect of the fabrication technique on material physical property.

Purpose The aim of this 60 months follow‐up investigation was to investigate the impact of jaw location on clinical and radiological status of dental‐implant therapy in cigarette‐smokers and never‐smokers. Materials and Methods Twenty‐nine self‐reported cigarette‐smokers and 27 nonsmokers were assessed. All implants were categorized into three regions with reference to their location in the maxilla or mandible: (a) Anterior zone: implants located in anterior teeth; (b) Middle zone: Implants located in the premolar region; and (c) posterior zone: implants located in the molar region. Peri‐implant crestal bone loss (CBL), bleeding‐on‐probing (BOP) and probing‐depth (PD) ≥ 4 mm and were assessed. Level of statistical significance was set at P < .05. Results Mean age of cigarette‐smokers (n = 29) and never‐smokers (n = 27) was 44.5 years (39‐51 years) and 43.6 years (35‐49 years), respectively. The average duration of cigarette‐smoking was 20.3 years (17‐26 years). The mean periimplant PD (P < .05) and CBL (P < .05) were significantly higher in cigarette‐smokers in contrast to never‐smokers in all zones. No statistically significant differences in CBL, PD, and BOP were observed in the three zones of implant location among cigarette‐smokers and never‐smokers. Conclusion Smoking enhanced PD and CBL around dental implants and this relationship was independent of site of implant placement and jaw location.

The aim of this study was to assess the impact of smoking on the whole salivary flow rate (SFR), IgA levels and clinical oral dryness (COD) among active and passive smokers. Material and Methods: The participants were categorized as active smokers (N = 54) or passive smokers (N = 163). Saliva was collected in tubes and placed in ice storage at -70°C. Salivary IgA levels were assessed in duplication using the enzyme linked immunosorbent assay (ELISA) method. Following the saliva sample collection, the subjects were assessed for COD using the COD score, SFR and caries. Chi-square test, the t-test and ANOVA were employed to compare the clinical impact of the smoking status associated with specific variables (smoking status, number of cigarettes, active caries, gender, age, COD score, IgA level and SFR). A p-value of <0.05 was considered significant. Results: Two hundred and seventeen subjects with the mean age of 32.86±6.30 years, with 145 males (66.8%) and 72 females (33.2%), were included in the study. Among the active smokers, 88.8% were males compared to 11.2% females. The active smokers had the mean age of 32.52 years,