Comparison of the Marginal and Internal Fit of Ceramic Laminate Veneers Fabricated with Four Different Computer-Aided Manufacturing Techniques.

Purpose: The improvement of computer-aided design and computer-aided manufacturing (CAD/CAM) has changed the methods of fabricating laminate veneers. The objectives of this study were to evaluate the marginal and internal fit of ceramic veneers manufactured with different CAD/CAM techniques. Materials and methods: A metal die was made by copying a prepared plastic maxillary central right incisor and scanned for designing a laminate veneer. One hundred laminate veneers were made with four different CAD/CAM techniques (n=25), including milled lithium disilicate (MLD), heat-pressed lithium disilicate with 3-dimensional (3D) printed wax patterns (PLD), milled zirconia (MZ), and 3Dprinted zirconia (PZ). The virtual marginal and internal fit of fabricated veneers was evaluated with digital crown fitting software. The actual marginal and internal fit was measured with the silicone replica method under a digital microscope. The measured data were analyzed using the one-way analysis of variance and the Turkey test. Results: There were significant differences in marginal and internal fit (P < 0.001) among manufacturing techniques. Both the virtual and actual marginal and internal gaps were higher in the PLD and PZ groups compared to the MLD and MZ groups. Conclusion: All four CAD/CAM techniques of manufacturing veneers, that is, milled lithium disilicate, heat-pressed lithium disilicate with 3D-printed wax patterns, milled zirconia, and 3D-printed zirconia, have clinically acceptable marginal and internal fit. Milled zirconia and lithium disilicate veneers demonstrated superior marginal and internal fit compared to 3D-printed zirconia and heat-pressed lithium disilicate veneers with 3D-printed wax patterns.

Effectiveness of resin infiltration in the management of anterior teeth affected by molar incisor hypomineralisation (MIH): A systematic review and meta-analysis.

OBJECTIVES: To evaluate the effectiveness of resin infiltration in improving the aesthetic appearance of anterior teeth affected by molar-incisor hypomineralisation (MIH). DATA SOURCES: PubMed, Scopus, EMBASE, Web of Science, ScienceDirect, and Cochrane Central Register of Controlled Trials (CENTRAL) were searched from 2009 to 2024. The protocol was registered in the International Prospective Database of Systematic Reviews (PROSPERO CRD42023461909). STUDY SELECTION: Interventional or comparative studies comparing resin infiltration and other treatments in MIH-affected anterior teeth were included. The risk of bias was evaluated using the Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I tool) and the Risk of Bias 2 (RoB 2.0) tool. Meta-analysis utilized a random-effects model. DATA: Eighteen studies met the inclusion criteria, and twelve were included in the meta-analysis. Resin infiltration showed a higher color difference (ΔE) before and after treatment (mean difference 2.21, 95 % confidence interval [CI] 0.04-4.38, p < 0.001, I2 = 98.61 %, p < 0.001) and better optical improvement (standardised mean difference [SMD] 2.68; 95 %CI 0.30-5.06; p = 0.027, I2 = 97.8 %, p < 0.001) compared to controls. The estimated success rate based on dentist assessment was 92 % (95 %CI 88-95 %, I2 = 17.92 %, p = 0.06). Non-randomised trials showed high (8/14) or moderate (6/14) risk of bias, mainly from confounding and selection issues. Randomised trials had high risk (1/3) or some concerns (2/3) due to missing data. CONCLUSIONS: The findings suggest that resin infiltration significantly improves aesthetic outcomes in MIH-affected anterior teeth, as evidenced by higher colour difference and optical improvement compared to controls. CLINICAL SIGNIFICANCE: While our study shows promising results for resin infiltration, including high success rates and aesthetic improvements, larger-scale studies with longer follow-up periods are necessary to confirm these findings and assess its long-term efficacy.

Hippo pathway-mediated YAP1/TAZ inhibition is essential for proper pancreatic endocrine specification and differentiation.

The Hippo pathway plays a central role in tissue development and homeostasis. However, the function of Hippo in pancreatic endocrine development remains obscure. Here, we generated novel conditional genetically engineered mouse models to examine the roles of Hippo pathway-mediated YAP1/TAZ inhibition in the development stages of endocrine specification and differentiation. While YAP1 protein was localized to the nuclei in bipotent progenitor cells, Neurogenin 3 expressing endocrine progenitors completely lost YAP1 expression. Using genetically engineered mouse models, we found that inactivation of YAP1 requires both an intact Hippo pathway and Neurogenin 3 protein. Gene deletion of Lats1 and 2 kinases (Lats1&2) in endocrine progenitor cells of developing mouse pancreas using Neurog3Cre blocked endocrine progenitor cell differentiation and specification, resulting in reduced islets size and a disorganized pancreas at birth. Loss of Lats1&2 in Neurogenin 3 expressing cells activated YAP1/TAZ transcriptional activity and recruited macrophages to the developing pancreas. These defects were rescued by deletion of Yap1/Wwtr1 genes, suggesting that tight regulation of YAP1/TAZ by Hippo signaling is crucial for pancreatic endocrine specification. In contrast, deletion of Lats1&2 using ß-cell-specific Ins1CreER resulted in a phenotypically normal pancreas, indicating that Lats1&2 are indispensable for differentiation of endocrine progenitors but not for that of ß-cells. Our results demonstrate that loss of YAP1/TAZ expression in the pancreatic endocrine compartment is not a passive consequence of endocrine specification. Rather, Hippo pathway-mediated inhibition of YAP1/TAZ in endocrine progenitors is a prerequisite for endocrine specification and differentiation.

Engineering high-valence metal-enriched cobalt oxyhydroxide catalysts for an enhanced OER under near-neutral pH conditions.

Understanding water splitting in pH-neutral media has important implications for hydrogen production from seawater. Despite their significance, electrochemical water oxidation and reduction in neutral electrolytes still face great challenges. This study focuses on designing efficient electrocatalysts capable of promoting the oxygen evolution reaction (OER) in neutral media by incorporating high-valence elements into transition-metal hydroxides. The as-prepared and optimized two-dimensional Mo-Co(OH)2 nanosheets, which undergo operando transformation into oxyhydroxide active species, demonstrated an overpotential of 550 mV at 10 mA cm-2 with a Tafel slope of 110.1 mV dec-1 in 0.5 M KHCO3. In situ X-ray absorption spectroscopy revealed that the incorporation of high-valence elements facilitates the generation of CoOOH active sites at low potential and enhances electron transfer kinetics by altering the electronic environment of the Co center. This study offers new insights for developing more efficient OER electrocatalysts and provides fresh ideas for seawater utilization through the study of the reaction mechanism of the near-neutral-pH OER.

Comparing the accuracy of two machine learning models in detection and classification of periapical lesions using periapical radiographs.

BACKGROUND: Previous deep learning-based studies were mainly conducted on detecting periapical lesions; limited information in classification, such as the periapical index (PAI) scoring system, is available. The study aimed to apply two deep learning models, Faster R-CNN and YOLOv4, in detecting and classifying periapical lesions using the PAI score from periapical radiographs (PR) in three different regions of the dental arch: anterior teeth, premolars, and molars. METHODS: Out of 2658 PR selected for the study, 2122 PR were used for training, 268 PR were used for validation and 268 PR were used for testing. The diagnosis made by experienced dentists was used as the reference diagnosis. RESULTS: The Faster R-CNN and YOLOv4 models obtained great sensitivity, specificity, accuracy, and precision for detecting periapical lesions. No clear difference in the performance of both models among these three regions was found. The true prediction of Faster R-CNN was 89%, 83.01% and 91.84% for PAI 3, PAI 4 and PAI 5 lesions, respectively. The corresponding values of YOLOv4 were 68.06%, 50.94%, and 65.31%. CONCLUSIONS: Our study demonstrated the potential of YOLOv4 and Faster R-CNN models for detecting and classifying periapical lesions based on the PAI scoring system using periapical radiographs.

A Dataset of apical periodontitis lesions in panoramic radiographs for deep-learning-based classification and detection.

Deep learning has been studied in recent years to identify periapical lesions- a significant indicator of periapical periodontitis in radiographs. An accurate dataset is essential for constructing an efficient learning model for detecting periapical lesions. In order to achieve this goal, we gathered and created a database of panoramic radiographs containing periapical lesions from the High-quality Dental Treatment Centre, School of Dentistry, Hanoi Medical University, between January 2016 and March 2021. Out of 16,519 radiographs, three experienced dentists identified 3,926 images of periapical lesions and annotated those lesions based on the Periapical Lesions Classification. By applying well-known data processing techniques (e.g. scaling, mirroring, and flipping), the amount of data is increased to 17,004 images through generating additional images for machine learning. The dataset has three folders: one for the original photos, one for the post-augmentation images, and the rest for the annotation of periapical lesions. The information could assist researchers in developing a predictive machine model for detecting periapical lesions in radiographs.