Search Results (25)

Background/Objectives: Previous studies on clear aligner therapy (CAT) in mixed dentition primarily focused on the predictability of maxillary arch expansion. However, limited evidence is available regarding mandibular arch changes, particularly in relation to inter-arch coordination. This study aims to evaluate the effectiveness and predictability of dental expansion in both the upper and lower arches using Invisalign First^® aligners. Methods: A retrospective analysis was conducted with 15 participants. Dental expansions were assessed before and after treatment using iTero intraoral scans processed with 3D analysis software. Measurements were compared to the predicted movements planned in ClinCheck^®. Data normality was verified (Shapiro–Wilk test), descriptive statistics were calculated, and paired t-tests were performed to compare clinical and predicted expansions, with significance set at 0.05. Results: Clear aligners achieved effective dento-alveolar expansion in both arches. Predictability was higher at the cusp level than at the gingival level, indicating a tendency toward tipping movements rather than bodily expansion. The study also highlighted mandibular expansion outcomes and gingival-level discrepancies, providing new insights compared to the previous literature. Minor differences between predicted and achieved movements were observed, partly attributable to natural growth and deciduous tooth exfoliation. Conclusions: Clear aligners are effective in achieving maxillary and mandibular arch expansion in mixed dentition, with good predictability at the coronal level. Overengineering buccal root torque may help promote bodily expansion and reduce cuspal–gingival discrepancies. Further studies with larger sample sizes are needed to optimize treatment planning and predictability. Full article

It is well understood that burr size and shape, as well as surface quality attributes like surface roughness in milling parts, vary according to several factors. These include cutting tool orientation, cutting profile, cutting parameters, tool shape and size, coating, and the interaction between the workpiece and the cutting tool. Therefore, burr size cannot be formulated simply as a function of direct parameters. This study proposes an ensemble learning regression model to accurately predict burr size and surface roughness during the slot milling of aluminum alloy (AA) 6061. The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (MAE), mean squared error (MSE), and the coefficient of determination (R²). The model demonstrated strong generalization capability when tested on unseen data. Specifically, it achieved an R² of 0.97 for surface roughness (Ra) and R² values of 0.93 (B5, B8), 0.92 (B2), 0.86 (B1), and 0.65 (B4) for various burr types. These results validate the model’s effectiveness despite the nonlinear and complex nature of burr formation. Additionally, feature importance analysis via the F-test indicated that feed per tooth and depth of cut were the most influential parameters across several burr types and surface roughness outcomes. This work represents a novel and accurate approach for predicting key surface quality indicators, with significant implications for process optimization and cost reduction in precision machining. Full article

Background: Digital planning and the use of a static surgical guide for implant placement provide predictability and safety for patients and practitioners. The aim of this study was to investigate differences in the accuracy and fit of long and short guides. Methods: In patients with at least one missing tooth, long (supported by the entire dental arch) and short templates (supported by two teeth, mesial and distal) were compared via intraoral scans and the superimposition of the STL files of the initial planning and the actual position in the patient’s mouth along the X-, Y- and Z-axes. Furthermore, this study evaluated the conditions (e.g., mouth opening, the implant position) under which fully guided implantation can be realized. Results: The largest deviation was observed in the Z-axis, although this deviation was not as high for the short templates (0.2275 mm) as it was for the long templates (0.4007 mm). With respect to the 3D deviation (dXYZ), the average deviation from the mean value was 0.2953 mm for the short guides and 0.4360 mm for the long guides (p = 0.002). The effect size (Cohen’s d) was 0.709, which was between the medium (0.50) and large effect sizes (0.80). The shorter templates showed a smaller deviation from the actual plan by 80%. With a mouth opening ≥50 mm, fully guided surgery can be performed in the molar region. In the premolar region, the lower limit was 32 mm. Conclusions: The 3D accuracy was significantly higher for the shorter template, which could therefore be favored. Full article

Based on the idea of a surface moving frame in differential geometry, a surface envelopment approximation method is proposed for the integrated design of point-contact tooth surfaces. This method utilizes the envelopment characteristic curve of the first tooth surface as the spline curve and adopts the local structure of the second tooth surface along a predesigned contact path as the surface interpolation condition. Through motion transformation described by the motion invariants of the first tooth surface, a conjugate motion space for the second tooth surface is fully defined by the motion invariants of the first tooth surface. This constitutes the basis of the integrated optimization design space and ensures the global optimization and machinability of the tooth surface design method. Using the experimental data of the point meshing tooth surface loading contact, the gap between the two tooth surfaces during no-load meshing is used as the design target parameter to predict and control the shape and size of the contact area under heavy load and further the symmetry requirements of the tooth surface design. Consequently, a variational inequality model for the global optimal design of the point meshing tooth surface is established. Full article

Background: Machine learning (ML) has potential to assist dental professionals with diagnosing and predicting outcomes of oral health. Tooth decay in children is the most common chronic childhood disease and it can be prevented by early detection. We aim to provide a map of the current evidence on ML in child oral health and provide insight for future research. Methods: A scoping review used databases like Medline, Web of Science, EBSCO Dentistry & Oral Science Source, Cochrane Library, and Scopus. Included studies assessed ML models for diagnoses, prediction, or management of oral health in children (0–9 years). Data extraction included publication year, location, age, sample size, disease, study type, and ML algorithms. Results: a total of 29 studies were included, mainly in pediatric dentistry and dental public health. Study designs comprised cross-sectional (34.5%), cohort (31.0%), case-control (20.7%), clinical trials (10.3%), and descriptive surveys (3.5%). The majority of studies were from high-income (69.0%) and upper middle-income countries (27.6%), with a small representation from low middle-income countries (3.4%). ML focused on predicting and diagnosing oral health issues such as caries progression and risk, with neural networks predominantly tested alongside emerging techniques like random forest, regression, and gradient boosting. Conclusions: ML algorithms hold promise in improving dental diagnosis and prediction accuracy, benefiting dental professionals, including pediatric and general dentists, in enhancing proficiency and reducing clinical errors. Full article

Spiral bevel gears are extensively employed in mechanical transmissions; however, they are prone to adhesive wear when operating under high-speed and heavy-load conditions. Research indicates that the tooth surface roughness of gears significantly influences the friction and wear of the meshing gears. The present study delves into the origins of tooth surface roughness through the integration of the W-M function and fractal theory. Utilizing an involute helical gear with surface roughness for tooth cutting, a three-dimensional model is established with roughened tooth surfaces. This paper introduces an approach to developing three-dimensional gear models with roughness and applies the finite element method to perform thermodynamic analysis on gears exhibiting diverse levels of surface roughness. The thermal analysis of gears with varying degrees of roughness was conducted using the finite element method. Comparative analysis of the results under specific operating conditions elucidated the impact of roughness on tooth surface temperature rise. In order to validate the simulation model, an experimental test platform for spiral bevel gears of identical size was established. This model integrates tooth surface roughness with thermodynamic analysis, allowing for the rapid assessment of tooth surface temperature rise under different machining conditions, and reducing the cost of validating predicted tooth surface load-carrying capacity. Full article

After tooth extraction, bone levels in the alveoli decrease. Using a bone substitute can help minimize this bone loss. The substitute can be sourced from a human or animal donor or synthetically prepared. In this study, we aimed to address the following PICOS question: In patients needing dental alveolar preservation for implant placement, how does alveolar preservation using a bovine hydroxyapatite bone xenograft with collagen compare to a xenograft without collagen in terms of changes in alveolar height and width, bone density, and the characteristics of the bone tissue observed in biopsies taken at 6 months? We evaluated two xenograft-type bone substitutes for preserving post-extraction dental sockets using tomography and microscopy to answer that question. A total of 18 dental alveoli were studied: 11 preserved with a xenograft composed of apatite (InterOss) and 7 with a xenograft composed of apatite–collagen (InterOss Collagen). Tomographic controls were performed at 1 and 6 months, and microscopic studies were performed on 13 samples. The biopsies were examined with scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). A Multivariate Analysis of Variance (MANOVA) was conducted in the statistical analysis, revealing a significant increase in bone density over time (p = 0.04). Specifically, bone density increased from an average of 526.14 HU at 30 days to 721.96 HU at 60 days in collagen-free samples. However, no statistically significant differences in height or width were found between groups. The MANOVA results indicated that the overall model had a low predictive ability for height, width, and density variables (R-squared values were low), likely due to sample size limitations and the complexity of bone tissue dynamics. On the other hand, FTIR analysis revealed the presence of phosphate groups, carbonates, and amides I, II, and III, indicative of inorganic (hydroxyapatite) and organic (type I collagen) materials in the xenografts. TGA and DSC showed high thermal stability, with minimal mass loss below 150 °C. Finally, both xenografts were influential in alveolar bone regeneration after extraction without significant differences. The trend of increasing collagen density suggests an effect that requires further investigation. However, it is recommended that the sample size be increased to enhance the validity of the results. Full article

Waste plastic film often contains an abundance of impurities, such as crop stems and soil. To address this issue, a toothed-plate single-roller crushing device for waste plastic film was developed. By analyzing the movement and force pattern of the film, the feeding speed, the number of toothed plates, and the crushing roller rotation speed were used as test factors, and the size qualification rate and the impurity content of the crushed film were used as test indexes. Through a Box–Behnken test design, regression analysis, and ANOVA, a model between factors and indexes was established. The results showed that the size qualification rate and the impurity content of the crushed film were 82.55% and 9.57%, and the errors in the prediction and test values were 6.14% and 8.38%, which proved them to have good reliability. The findings of this study provide essential technical and equipment support for the resource recovery of waste plastic films. Full article

Mechanical seals, such as labyrinth seals, are typically installed at the turbine outlets to prevent oil leakage. However, these seals undergo deformation because of the vibrations of the rotor, even during normal turbine operating conditions, which may cause an increase in oil leakage. In this study, the oil leakage performance of three labyrinth seals with different types of seal teeth, narrow stainless teeth (Type 1), wide aluminum teeth fixed on the body (Type 2), and fixed wide aluminum movable teeth (Type 3), were evaluated using finite element (FE) and computational fluid dynamics (CFD) analyses. Three-dimensional FE models of the rotor and oil deflectors were developed, and the plastic deformation of the teeth of the labyrinth seals was predicted when the rotor impacted the sealing teeth during turbine operation. The oil leakage was predicted using CFD analysis. The results indicated that the Type 3 seal, including movable teeth, is beneficial in preventing leakage and tooth deformation compared with the other types. The Type 2 seal is advantageous because it results in a smaller increase in gap size and greater vena contracta effects than the Type 1 seal. The results of this study could be helpful when designing and selecting the teeth of a labyrinth seal. Full article

Cycloid drives are widely used in various mechanical systems due to their high reduction ratio, compact size, and high efficiency. Tooth surface wear is a major problem that affects the reliability and durability of cycloid drives. However, compared to the research on the wear of involute gears, the prediction of tooth surface wear in cycloid drives is relatively limited and less extensive. To fill this gap, the theoretical wear model of the tooth surface of cycloid-pin gear pairs is proposed based on the Hertz contact theory and Archard’s formula, with consideration of tooth profile modifications. Firstly, the loaded tooth contact analysis model is established to determine the relative sliding velocity and tooth contact stress. Secondly, the calculation steps of single tooth surface wear are presented within one gear mesh cycle. With this, the effects of the tooth profile modifications, the operating conditions such as output torque, input speed, and the assembly eccentricity on the wear depth within one gear mesh cycle are investigated. This study gives a deeper understanding of the tooth surface wear mechanisms of cycloid drives and could be employed to assist gear design and to improve the wear resistance. Full article

Traditional load-to-failure tests fail to recreate clinical failures of all-ceramic restorations. Experimental fabrication, similar to prosthetic laboratory and clinical procedures, best predicts future clinical performance. A hybrid ceramic adherend, mechanically similar to a human tooth, was tested by comparing the shear bond strength (SBS) and fracture mode of four restorative materials adhered with a dual-cure adhesive cement. Surface energy, shear bond strength (SBS), and fracture mode were assessed. Vita Enamic (ENA), Vita Suprinity (SUP), Vita Y-TPZ (Y-ZT), and a nanohybrid composite (RES) (control group) cylinders, adhered with RelyX Ultimate to ENA blocks were assembled in experimental specimens simulating a 3-unit resin-bonded dental bridge. The ENA adherend was ground or treated with 5% hydrofluoric acid for 60 s. Monobond Plus was used as the coupling agent. Mean shear stress (MPa) was calculated for each group. Forest plots by material elaborated after calculating the difference in means and effect size (α = 0.05; 95% CI; Z-value = 1.96) revealed significant differences in the shear force behavior between materials (p < 0.01). RES (69.10 ± 24.58 MPa) > ENA (18.38 ± 8.51 MPa) > SUP (11.44 ± 4.04 MPa) > Y-ZT (18.48 ± 12.12 MPa). Y-ZT and SUP exhibited pre-test failures. SBS was not related to surface energy. The failure mode in the Y-ZT group was material-dependent and exclusively adhesive. ENA is a potential adherend for dental materials SBS tests. In this experimental design, it withstood 103 MPa of adhesive stress before cohesive failure. Full article

Background and purpose: Accurate instance segmentation of teeth in panoramic dental X-rays is a challenging task due to variations in tooth morphology and overlapping regions. In this study, we propose a new algorithm, for instance, segmentation of the different teeth in panoramic dental X-rays. Methods: An instance segmentation model was trained using the architecture of a Mask Region-based Convolutional Neural Network (Mask-RCNN). The data for the training, validation, and testing were taken from the Tuft dental database (1000 panoramic dental radiographs). The number of the predicted label was 52 (20 deciduous and 32 permanent). The size of the training, validation, and test sets were 760, 190, and 70 images, respectively, and the split was performed randomly. The model was trained for 300 epochs, using a batch size of 10, a base learning rate of 0.001, and a warm-up multistep learning rate scheduler (gamma = 0.1). Data augmentation was performed by changing the brightness, contrast, crop, and image size. The percentage of correctly detected teeth and Dice in the test set were used as the quality metrics for the model. Results: In the test set, the percentage of correctly classified teeth was 98.4%, while the Dice score was 0.87. For both the left mandibular central and lateral incisor permanent teeth, the Dice index result was 0.91 and the accuracy was 100%. For the permanent teeth right mandibular first molar, mandibular second molar, and third molar, the Dice indexes were 0.92, 0.93, and 0.78, respectively, with an accuracy of 100% for all three different teeth. For deciduous teeth, the Dice indexes for the right mandibular lateral incisor, right mandibular canine, and right mandibular first molar were 0.89, 0.91, and 0.85, respectively, with an accuracy of 100%. Conclusions: A successful instance segmentation model for teeth identification in panoramic dental X-ray was developed and validated. This model may help speed up and automate tasks like teeth counting and identifying specific missing teeth, improving the current clinical practice. Full article

Automatic age estimation using panoramic dental radiographic images is an important procedure for forensics and personal oral healthcare. The accuracies of the age estimation have increased recently with the advances in deep neural networks (DNN), but DNN requires large sizes of the labeled dataset which is not always available. This study examined whether a deep neural network is able to estimate tooth ages when precise age information is not given. A deep neural network model was developed and applied to age estimation using an image augmentation technique. A total of 10,023 original images were classified according to age groups (in decades, from the 10s to the 70s). The proposed model was validated using a 10-fold cross-validation technique for precise evaluation, and the accuracies of the predicted tooth ages were calculated by varying the tolerance. The accuracies were 53.846% with a tolerance of ±5 years, 95.121% with ±15 years, and 99.581% with ±25 years, which means the probability for the estimation error to be larger than one age group is 0.419%. The results indicate that artificial intelligence has potential not only in the forensic aspect but also in the clinical aspect of oral care. Full article

Cell counting and sorting is a vital step in the purification process within the area of biomedical research. It has been widely reported and accepted that the use of hydrodynamic focusing in conjunction with the application of a dielectrophoretic (DEP) force allows efficient separation of biological entities such as platelets from red blood cell (RBC) samples due to their size difference. This paper presents computational results of a multiphysics simulation modelling study on evaluating continuous separation of RBCs and platelets in a microfluidic device design with saw-tooth profile electrodes via DEP. The theoretical cell particle trajectory, particle cell counting, and particle separation distance study results reported in this work were predicted using COMSOL v6.0 Multiphysics simulation software. To validate the numerical model used in this work for the reported device design, we first developed a simple y-channel microfluidic device with square “in fluid” electrodes similar to the design reported previously in other works. We then compared the obtained simulation results for the simple y-channel device with the square in fluid electrodes to the reported experimental work done on this simple design which resulted in 98% agreement. The design reported in this work is an improvement over existing designs in that it can perform rapid separation of RBCs (estimated 99% purification) and platelets in a total time of 6–7 s at a minimum voltage setting of 1 V and at a minimum frequency of 1 Hz. The threshold for efficient separation of cells ends at 1000 kHz for a 1 V setting. The saw-tooth electrode profile appears to be an improvement over existing designs in that the sharp corners reduced the required horizontal distance needed for separation to occur and contributed to a non-uniform DEP electric field. The results of this simulation study further suggest that this DEP separation technique may potentially be applied to improve the efficiency of separation processes of biological sample scenarios and simultaneously increase the accuracy of diagnostic processes via cell counting and sorting. Full article

Evolutionary changes in vertebrates are linked to genetic alterations that often affect tooth crown shape, which is a criterion of speciation events. The Notch pathway is highly conserved between species and controls morphogenetic processes in most developing organs, including teeth. Epithelial loss of the Notch-ligand Jagged1 in developing mouse molars affects the location, size and interconnections of their cusps that lead to minor tooth crown shape modifications convergent to those observed along Muridae evolution. RNA sequencing analysis revealed that these alterations are due to the modulation of more than 2000 genes and that Notch signaling is a hub for significant morphogenetic networks, such as Wnts and Fibroblast Growth Factors. The modeling of these tooth crown changes in mutant mice, via a three-dimensional metamorphosis approach, allowed prediction of how Jagged1-associated mutations in humans could affect the morphology of their teeth. These results shed new light on Notch/Jagged1-mediated signaling as one of the crucial components for dental variations in evolution. Full article