SUMMARY: The present study assessed the polymerization shrinkage stress kinetics of five low-shrinkage light-cured bulk-fill resin composites: Surefil SDR flow (SF, Dentsply), Tetric EvoCeram Bulkfil (TE, Ivoclar Vivadent), Venus Bulk Fill (VB, Heraeus Kulzer), x-tra fil (XF, Voco), and experimental bulk fill (FB, 3M ESPE). Filtek Z250 (FZ, 3M ESPE) was used as a control. Real-time shrinkage stress of investigated composites was measured using a tensometer; maximum shrinkage stress, stress rate (Rmax), and time to reach maximum stress rate (tmax) were recorded. Flexural strength and modulus were measured using a standard procedure, and curing efficiency of 4-mm long specimens was determined using bottom/top percentage Knoop microhardness. Data were analyzed using one-way analysis of variance and Bonferroni multiple range tests at a significance level of α=0.05. Results of shrinkage stress, Rmax, and tmax of all bulk-fill materials were significantly lower (p<0.05) than those of the control except for XF. All tested bulk-fill materials were able to achieve acceptable curing efficiency (≥80% bottom/top percentage) at 4-mm depth. In conclusion, this study reports a significant reduction in polymerization shrinkage stress while maintaining comparable curing efficiency at 4 mm for some bulk-fill composites and supports their potential use in posterior clinical situations.

SUMMARY: This study assessed marginal leakage and fracture resistance of computer-aided design/computer-aided manufacturing (CAD/CAM) fabricated ceramic crowns with intracoronal extensions into the pulp chambers of endodontically treated teeth (endocrowns) using either feldspathic porcelain (CEREC Blocks [CB], Sirona Dental Systems GmbH, Bensheim, Germany), lithium disilicate (e.max [EX], Ivoclar Vivadent, Schaan, Liechtenstein), or resin nanoceramic (Lava Ultimate [LU], 3M ESPE, St Paul, MN, USA).). Thirty extracted human permanent maxillary molars were endodontically treated. Standardized preparations were done with 2-mm intracoronal extensions of the endocrowns into the pulp chamber. Teeth were divided into three groups (n=10); each group was restored with standardized CAD/CAM fabricated endocrowns using one of the three tested materials. After cementation with resin cement, specimens were stored in distilled water at 37°C for one week, subjected to thermocycling, and immersed in a 5% methylene-blue dye solution for 24 hours. A compressive load was applied at 35 degrees to long axis of the teeth using a universal testing machine until failure. Failure load was recorded, and specimens were examined under a stereomicroscope for modes of failure and microleakage. Results were analyzed using one-way analysis of variance and Bonferroni post hoc multiple comparison tests (α=0.05). LU showed significantly (p<0.05) higher fracture resistance and more favorable fracture mode (ie, fracture of the endocrown without fracture of tooth) as well as higher dye penetration than CB and EX. In conclusion, although using resin nanoceramic blocks for fabrication of endocrowns may result in better fracture resistance and a more favorable fracture mode than other investigated ceramic blocks, more microleakage may be expected with this material.

This study assessed the effect of pretreatment of hybrid and glass ceramics using a self-etching primer on the shear bond strength (SBS) and surface topography, in comparison to pretreatment with hydrofluoric acid and silane. 40 rectangular discs from each ceramic material (IPS e.max CAD;EM, Vita Mark II;VM, Vita Enamic;VE), were equally divided (n=10) and assigned to one of four surface pretreatment methods; etching with 4.8% hydrofluoric acid followed by Monobond plus (HFMP), Monobond etch & prime (Ivoclar Vivadent) (MEP), No treatment (NT) as negative control and Monobond plus (Ivoclar Vivadent) with no etching (MP) as positive control. SBS of resin cement (Multilink-N, Ivoclar Vivadent) to ceramic surfaces was tested following a standard protocol. Surface roughness was evaluated using an Atomic force microscope (AFM). Surface topography and elemental analysis were analyzed using SEM/EDX. Data were analyzed with two-way analysis of variance (ANOVA) and post-hoc Bonferroni test at a significance level of α=0.05. Pretreatment with HFMP resulted in higher SBS and increased surface roughness in comparison to MEP and MP. Regardless the method of surface pretreatment, the mean SBS values of EM ceramic was significantly higher (p<0.05) than those recorded for VM and VE, except when VE was treated with MEP, where the difference was statistically insignificant. Traces of fluoride ion were detected when MEP was used with VE and VM. Under limited conditions, using MEP resulted in comparable SBS results to HFMP; meanwhile HFMP remains the gold standard for pretreatment of glass ceramics for resin-luting cementation.

Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.

SUMMARY: The aim of the study was to evaluate the effect of preparation depth and intraradicular extension on the marginal and internal adaptation of computer-aided design/computer-assisted manufacture (CAD/CAM) endocrown restorations. Standardized preparations were made in resin endodontic tooth models (Nissin Dental), with an intracoronal preparation depth of 2 mm (group H2), with extra 1- (group H3) or 2-mm (group H4) intraradicular extensions in the root canals (n=12). Vita Enamic polymer-infiltrated ceramic-network material endocrowns were fabricated using the CEREC AC CAD/CAM system and were seated on the prepared teeth. Specimens were evaluated by microtomography. Horizontal and vertical tomographic sections were recorded and reconstructed by using the CTSkan software (TView v1.1, Skyscan).The surface/void volume (S/V) in the region of interest was calculated. Marginal gap (MG), absolute marginal discrepancy (MD), and internal marginal gap were measured at various measuring locations and calculated in microscale (μm). Marginal and internal discrepancy data (μm) were analyzed with nonparametric Kruskal-Wallis analysis of variance by ranks with Dunn's post hoc, whereas S/V data were analyzed by one-way analysis of variance and Bonferroni multiple comparisons (α=0.05). Significant differences were found in MG, MD, and internal gap width values between the groups, with H2 showing the lowest values from all groups. S/V calculations presented significant differences between H2 and the other two groups (H3 and H4) tested, with H2 again showing the lowest values. Increasing the intraradicular extension of endocrown restorations increased the marginal and internal gap of endocrown restorations.

SUMMARY: This study evaluated the microtensile bond strength (μ-TBS) of low-shrinkage composites with their corresponding adhesive systems, Filtek Silorane/Silorane adhesive (SIL, 3M ESPE AG, Seefeld, Germany) and Aelite LS/One-Step Plus (AL, BISCO Inc, Schaumburg, IL, USA) in cavities with different C-factors. Filtek Z250/Adper Single Bond Plus (Z, 3M ESPE, St Paul, MN, USA) was used as a control. Method: Standardized Class I cavities were prepared in extracted human molars after removing occlusal enamel. Cavities were assigned into six different C-factors by applying nail polish to four walls, three walls, two walls adjacent to each other, two walls opposite to each other, one wall, or no walls. Resin composites with their corresponding adhesive systems were applied according to manufacturer instructions. Specimens were sectioned to obtain four rectangular beams from the center of the restorations and μ-TBS was measured. Data were analyzed by Weibull survival analysis. Shrinkage stresses of the resin composites were determined after 30 minutes from the start of light-curing using a tensometer testing machine. Flexure elastic modulus was determined using standard procedures, in accordance with ISO 4049. Data for shrinkage stress and elastic modulus were analyzed by one-way analysis of variance followed by a Tukey multiple-comparisons test (p<0.05). Results: μ-TBS of both SIL and AL were not affected by different C-factors; however, the bond strength of Z decreased significantly when the C-factor increased. Shrinkage stress results were 0.94±0.1, 1.79±0.18, and 2.14±0.23 MPa for SIL, AL, and Z, respectively. The flexural modulus of both the SIL and the AL was significantly lower than that of Z. Conclusions: Increasing C-factor did not negatively affect the bond strength of low-shrinkage composites.