Gülsüm Ceylan

This study aimed to evaluate the impact of printing orientation on the mechanical and physical properties of three different 3D-printed PMMA denture base r

This in vitro study aimed to evaluate the effects of resin type, layer thickness, and printing orientation on the surface and mechanical properties of 3D-printed occlusal splints fabricated using digital light processing (DLP) technology. Three commercially available splint resins (KeySplint Hard, Freeprint Splint 2.0, and V-Print Splint) were used to fabricate 180 rectangular specimens with two-layer thicknesses (50 µm and 100 µm) and three printing orientations (0°, 45°, 90°). Surface roughness (Ra, Rz), gloss, microhardness, flexural strength, and elastic modulus were measured. Statistical analysis was performed using robust ANOVA with Bonferroni correction. Resin type and printing orientation significantly influenced all surface and mechanical properties (p < 0.001), while layer thickness had a limited effect. Keystone resin exhibited the smoothest surface and highest gloss, whereas Freeprint resin showed the highest microhardness and elastic modulus. Printing at 45° generally enhanced flexural strength and provided more balanced mechanical performance. SEM analysis confirmed that surface morphology varied with orientation, correlating with profilometric and gloss measurements. Resin composition and printing orientation are critical determinants of the mechanical and surface performance of 3D-printed occlusal splints. Optimizing these parameters can improve durability, esthetics, and clinical functionality. All tested materials achieved clinically acceptable surface smoothness, supporting their suitability for intraoral use.

Lenz-Majewski Syndrome (LMS) is a rare multisystem genetic disorder characterized by intellectual disability, cutis laxa, craniofacial abnormalities, and distinct dental features. It is caused by gain-of-function mutations in the Phosphatidylserine Synthase 1 (PTDSS1) gene, which plays a key role in phospholipid biosynthesis. Among the craniofacial and dental manifestations, a progeroid facial appearance with prognathism, midface hypoplasia, large auricles, enamel dysplasia, delayed tooth eruption, and malocclusion are commonly observed. Due to the rarity and phenotypic variability of LMS, individual case reports remain essential for expanding the clinical and molecular understanding of the syndrome. We report a 13-year-old male diagnosed with Lenz-Majewski Syndrome (LMS) through whole exome sequencing, which identified a heterozygous de novo PTDSS1 variant (c.284G > A; p.R95Q), not previously documented in LMS cases. Clinical evaluation revealed moderate intellectual disability, cutis laxa, a progeroid facial appearance, and pronounced prognathism. Intraoral and radiographic examinations demonstrated enamel hypoplasia, taurodontism, delayed eruption of permanent teeth, a horizontally positioned upper lateral incisor, and a large follicular cyst in the maxilla. Orthodontic intervention using Hawley appliances was employed to stimulate the oral mucosa and support the eruption of delayed permanent teeth. This case expands the phenotypic and genotypic understanding of LMS and documents novel dental findings—particularly taurodontism—in association with a previously unreported PTDSS1 variant. It underscores the importance of early dental assessment and multidisciplinary care in managing LMS. Recognizing oral manifestations can facilitate timely diagnosis and personalized treatment strategies, contributing to improved quality of life in affected individuals.

Objective: This in vitro study aimed to evaluate the scan accuracy of 6 intraoral scanners (IOSs) by using a dentate model. Methods: A maxillary dentate reference model was digitized with an industrial-grade blue light optical scanner to generate a reference standard tessellation language (STL) file. The same model was digitized by using 6 IOSs (Trios 4, Trios 3, Primescan, Omnicam, Planmeca Emerald S, and Medit i700) (n=10) to generate test scan STLs. All STL files were imported into a 3-dimensional analysis software program (Geomagic Control X). Test scan STLs were superimposed over the reference STL by using the initial and best-fit alignments of the software program, and the deviations of the scans of IOS from that of the optical scanner were calculated with the root mean square (RMS) method. The average deviation method was used to define the precision of the scans. Kruskal-Wallis and Bonferroni tests were used to statistically evaluate the data (α=0.05). Results: A significant difference was observed between groups in terms of RMS values (p

This study aims to investigate the effects of digital literacy and self-esteem on dental students’ perceptions of professional competence and to provide recommendations for improving educational programs in dental schools. A mixed-methods, descriptive, and relational scanning design was employed, using a questionnaire comprising demographic information, the Rosenberg Self-Esteem Scale (RSES), the Digital Literacy Scale (DLS), and the Professional Competence Scale (PCS). The sample included 427 dental students in Istanbul, Turkey. Statistical analyses included Cronbach Alpha, Confirmatory Factor Analysis, Mann–Whitney U, Kruskal–Wallis, Spearman’s rho correlation, and the Generalized Linear Model (Logit Model). The majority of participants were female (65.6%), aged 21 or older (85.2%), and in their 4th grade of study (35.2%). There were no significant differences in PCS scores concerning gender, age, grade, type of residence, and residence location (p > 0.05). However, PCS scores were significantly higher among those who listed dentistry among their top five preferences, expressed high satisfaction with education, and demonstrated high professional interest (p < 0.05). A significant, positive correlation was observed between PCS and RSES (r = 0.398; p < 0.01), DLS (r = 0.404; p < 0.01), preference (r = 0.120; p < 0.05), education satisfaction (r = 0.298; p < 0.01), and occupational interest (r = 0.502; p < 0.05). Furthermore, the Logit Model analysis revealed that RSES (B = 0.290; p < 0.01), DLS (B = 0.258; p < 0.01), education satisfaction (B = 0.806; p < 0.05), and occupational interest (B = 3.825; p < 0.01) significantly influenced PCS. The findings underscore self-esteem and digital literacy’s integral role in shaping dental students’ perceptions of their professional abilities. Digital literacy is a substantial pillar supporting students’ professional competency. Coupled with a genuine interest in the field and bolstered self-confidence, digital literacy proves instrumental in enhancing students’ academic success in dentistry. By emphasizing and expanding upon digital literacy content within the curriculum, universities can further propel advancements in the dental domain. As such, it is pivotal for dental institutions to weave strategies into their educational fabric to elevate students’ self-esteem and digital proficiency.

Amaç: Bu in vitro çalışmanın amacı intraoral tarayıcıların dental implantlar üzerinden alınan ölçülerin hassasiyetine olan etkisini kapsamlı bir şekilde değerlendirmektir. Gereç ve Yöntem: Bu çalışma, altı intraoral tarayıcıyı (AİT); Trios 4, Trios 3, Primescan, Omnicam, Planmeca ve Medit i700 karşılaştırmak üzerine tasarlandı. 3D yazıcı (Formlabs 3) ile üretilen master modelden herbir AİT ile ölçü alındı. AİT’lerin doğruluk (trueness) ve kesinlik (precision) değerleri belirlendi ve analiz edildi. İstatistiksel analizlerde, Shapiro-Wilks testi ve Kruskal-Wallis non-parametrik testleri (α=0.05) ayrıca çoklu karşılaştırmalarda Tamhane testi kullanıldı. Bulgular: Gruplara ait doğruluk değerleri arasında anlamlı farklar bulundu (p 0.05) diğer AİT’ler ile arasında anlamlı fark bulundu (p 0.05). Ancak, Primescan ve Medit i700'ün doğruluk değerleri ile diğer AİT'ler arasında istatistiksel olarak anlamlı fark bulundu (p 0.05). Sonuç: En yüksek doğruluk değeri Primescan'de, en yüksek kesinlik değeri ise Medit i700'de bulundu. Bu sonuçlar, AİT’lerin seçiminde hekimler tarafından dikkate alınmalıdır.

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.

Cross-linking agents are incorporated into denture base materials to improve their mechanical properties. This study investigated the effects of various cross-linking agents, with different cross-linking chain lengths and flexibilities, on the flexural strength, impact strength, and surface hardness of polymethyl methacrylate (PMMA). The cross-linking agents used were ethylene glycol dimethacrylate (EGDMA), tetraethylene glycol dimethacrylate (TEGDMA), tetraethylene glycol diacrylate (TEGDA), and polyethylene glycol dimethacrylate (PEGDMA). These agents were added to the methyl methacrylate (MMA) monomer component in concentrations of 5%, 10%, 15%, and 20% by volume and 10% by molecular weight. A total of 630 specimens, comprising 21 groups, were fabricated. Flexural strength and elastic modulus were assessed using a 3-point bending test, impact strength was measured via the Charpy type test, and surface Vickers hardness was determined. Statistical analyses were performed using the Kolmogorov–Smirnov Test, Kruskal–Wallis Test, Mann–Whitney U Test, and ANOVA with post hoc Tamhane test (p ≤ 0.05). No significant increase in flexural strength, elastic modulus, or impact strength was observed in the cross-linking groups compared to conventional PMMA. However, surface hardness values notably decreased with the addition of 5% to 20% PEGDMA. The incorporation of cross-linking agents in concentrations ranging from 5% to 15% led to an improvement in the mechanical properties of PMMA.

This study compared the accuracy (trueness and precision) of stone models fabricated using two brands of CAD/CAM optimized stones Cerec Stone (BC) and Elite Master (EM), and a conventional type IV stone Elite Rock Fast (ERF). 30 conventional Type IV and scannable stone complete-arch models were scanned with a blue LED extraoral scanner, and root mean square values were obtained. 6 abutments were used in complete-arch models. The digital models were compared with the master model to evaluate their trueness using model superimposition with Geomagic software. Precision was determined for each case by superimposing combinations of the 10 datasets in each group. The point cloud density of each model was calculated with MeshLab software. Kruskal-Wallis and Mann-Whitney non-parametric tests were used for the statistical analysis. The trueness of the stone models was 96 μm for the BC, 88.2 μm for the EM, and 87.6 μm for the ERF. There were no significant differences between the tested dental stones (p = .768). However, the EM models (35.6 μm) were more precise than the BC (46.9 μm) and ERF (56.4 μm) models (p = .001, p < .001). EM models also showed the highest point cloud density. There were significant differences in point cloud density (p = .003). The EM models showed significant differences in precision but no significant differences in terms of trueness. Although EM was more precise and had the highest point cloud density, all models were within the clinically acceptable limit.