The Physiological Function of Deglutition and Swallowing in Patients With Maxillary Protrusion After Mandibular Advancement.

The objective of this study was to determine the tongue-palatal contact changes in patients with skeletal maxillary protrusion after sagittal split ramus osteotomy (SSRO) during swallowing. In this study, 15 patients with maxillary protrusion and 10 normal subjects participated. Before and 3 months after surgery, tongue-palatal contact patterns during swallowing of patients with maxillary protrusion as well as controls were evaluated by electropalatography. The electrode contact number in the alveolar, palatal, and velar parts was examined. The swallowing duration of each phase was also evaluated. In the lateral area of the velar part, incomplete electrode contact was shown at 0.3 seconds in patients with maxillary protrusion. The electrode contact number in the velar part at 0.3 seconds before tongue-palatal complete contact was significantly less in the preoperative patients compared with the controls ( P < 0.05). A small increase in the electrode contact number of the velar part was shown in the postoperative patients at 0.3 and 0.2 seconds before tongue-palatal complete contact ( P < 0.05). The pharyngeal phase duration was significantly larger in the patients with maxillary protrusion before SSRO compared with the controls ( P < 0.05). After SSRO, the pharyngeal phase duration was significantly shortened. It was shown that the tongue-palatal contact pattern during swallowing in patients with maxillary protrusion improved after orthognathic surgery, and the pharyngeal phase duration was also shortened. It is suggested that the changes in the mesiodistal mandibular position by orthognathic surgery can improve tongue posture and movement during swallowing.

Occlusal Trauma and Bisphosphonate-Related Osteonecrosis of the Jaw in Mice.

Osteonecrosis of the jaw (ONJ) is a serious adverse event that is associated with antiresorptive agents, and it manifests as bone exposure in the maxillofacial region. Previous clinical reports suggest that mechanical trauma would trigger ONJ in a manner that is similar to tooth extractions. To the best of our knowledge, there have been few detailed pathophysiological investigations of the mechanisms by which occlusal/mechanical trauma influences ONJ. Here, we developed a novel mouse model that exhibits ONJ following experimental hyperocclusion and nitrogen-containing bisphosphonate (N-BP) treatment. This in vivo model exhibited ONJ in alveolar bone, particularly in the mandible. Moreover, the experimental hyperocclusion induced remarkable alveolar bone resorption in both mouse mandible and maxilla, whereas N-BP treatment completely prevented alveolar bone resorption. In this study, we also modeled trauma by exposing clumps of mesenchymal stem cells (MSCs)/extracellular matrix complex to hydrostatic pressure in combination with N-BP. Hydrostatic pressure loading induced lactate dehydrogenase (LDH) release by calcified cell clumps that were differentiated from MSCs; this LDH release was enhanced by N-BP priming. These in vivo and in vitro models may contribute further insights into the effect of excessive mechanical loading on ONJ onset in patients with occlusal trauma.

Detecting the presence of supernumerary teeth during the early mixed dentition stage using deep learning algorithms: A pilot study.

BACKGROUND: Supernumerary teeth are a common anomaly and are frequently observed in paediatric patients. To prevent or minimize complications, early diagnosis and treatment is ideal in children with supernumerary teeth. AIM: This study aimed to apply convolutional neural network (CNN)-based deep learning to detect the presence of supernumerary teeth in children during the early mixed dentition stage. DESIGN: Three CNN models, AlexNet, VGG16-TL, and InceptionV3-TL, were employed in this study. A total of 220 panoramic radiographs (from children aged 6 years 0 months to 9 years 6 months) including supernumerary teeth (cases, n = 120) or no anomalies (controls, n = 100) were retrospectively analyzed. The CNN performances were assessed according to accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curves, and area under the ROC curves for a cross-validation test dataset. RESULTS: The VGG16-TL model had the highest performance according to accuracy, sensitivity, specificity, and area under the ROC curve, but the other models had similar performance. CONCLUSION: CNN-based deep learning is a promising approach for detecting the presence of supernumerary teeth during the early mixed dentition stage.

Fracture characteristics and translucency of multilayer monolithic zirconia crowns of various thicknesses.

OBJECTIVES: Multilayer monolithic zirconia (M-Zr) crowns can be engineered to achieve gradational translucency and color intensity. However, this modification may compromise the mechanical strength, raising concerns regarding the ability of M-Zr crowns to withstand occlusal stresses. The effects of M-Zr crown thickness on translucency and ability to endure occlusal forces were investigated at different tooth positions (incisors, premolars, and molars). The objective was to determine the minimal thickness of M-Zr crowns used in tooth preparation to meet aesthetic and functional demands. METHODS: M-Zr samples (Vita A1) with four thicknesses (0.5, 1.0, 1.5, and 2.0 mm) were prepared and subjected to translucency testing using a digital colorimeter by 3-third and 9-square division methods. Crown-shaped M-Zr samples with three thicknesses (1.0, 1.5, and 2.0 mm) and three tooth positions (incisor, premolar, and molar) were digitally designed, and 2.0 mm metal abutments were fabricated. The samples were bonded to the abutments; their fracture characteristics were evaluated using a universal testing machine, and their fracture surfaces examined using an optical microscope. Statistical analyses included the Shapiro-Wilk test, Pearson correlation, and one-way and two-way ANOVA with a post hoc Tukey HSD test (α = 0.05). RESULTS: Color analysis results revealed a significant negative correlation between thickness and translucency (r < -0.96, P < 0.01), with the highest values in the incisal region. Cross-sectional profiles confirmed the uniform thickness and morphology of the digitally designed M-Zr crowns. The results of fracture strength analysis showed position-dependent variability, a strong positive correlation with thickness (r > 0.96, P < 0.01), and fracture strengths consistently exceeding 1200 N across all tooth positions. Fracture patterns indicated that thinner crowns at the incisors and molars were more prone to cracking, whereas those at the premolars demonstrated significantly higher strength (4872.51 N, P < 0.05), only with crack or even no fracture occurring at 2.0 mm. CONCLUSIONS: Thickness significantly influenced both the translucency and fracture strength of M-Zr, with the tooth position playing an additional role, albeit to a lesser extent. Although thinner crowns exhibited lower strength at each tooth position, even at a thickness of 1.0 mm, fracture strength exceeding 1200 N was maintained, surpassing the typical occlusal forces. Thus, it can be asserted that M-Zr crowns with a minimum thickness of 1.0 mm can meet both aesthetic and functional requirements.

Image preprocessing with contrast-limited adaptive histogram equalization improves the segmentation performance of deep learning for the articular disk of the temporomandibular joint on magnetic resonance images.

OBJECTIVES: The objective was to evaluate the robustness of deep learning (DL)-based encoder-decoder convolutional neural networks (ED-CNNs) for segmenting temporomandibular joint (TMJ) articular disks using data sets acquired from 2 different 3.0-T magnetic resonance imaging (MRI) scanners using original images and images subjected to contrast-limited adaptive histogram equalization (CLAHE). STUDY DESIGN: In total, 536 MR images from 49 individuals were examined. An expert orthodontist identified and manually segmented the disks in all images, which were then reviewed by another expert orthodontist and 2 expert oral and maxillofacial radiologists. These images were used to evaluate a DL-based semantic segmentation approach using an ED-CNN. Original and preprocessed CLAHE images were used to train and validate the models whose performances were compared. RESULTS: Original and CLAHE images acquired on 1 scanner had pixel values that were significantly darker and with lower contrast. The values of 3 metrics-the Dice similarity coefficient, sensitivity, and positive predictive value-were low when the original MR images were used for model training and validation. However, these metrics significantly improved when images were preprocessed with CLAHE. CONCLUSIONS: The robustness of the ED-CNN model trained on a dataset obtained from a single device is low but can be improved with CLAHE preprocessing. The proposed system provides promising results for a DL-based, fully automated segmentation method for TMJ articular disks on MRI.

An in vitro study of digital impressions and three-dimensional printed models of orbital defects using mobile devices and monoscopic photogrammetry.

PURPOSE: The purpose of this study was to perform an in vitro evaluation of digital impressions using a mobile device and monoscopic photogrammetry in cases of orbital defects with undercuts. METHODS: Three 10-mm-square cubes were attached to a diagnostic cast of a patient with a right orbital defect. Still images acquired with a mobile device were used to generate facial three-dimensional (3D) data. Two types of still images were used: one was a whole face image, and the other was a defect site-focused image. For comparison, an extraoral scanner was used to obtain facial 3D data. Five dental technicians fabricated 3D printed models using additive manufacturing and measured the distances between the measurement points using a digital caliper. The discrepancy between the distances measured on the diagnostic cast of the patient and the 3D printed model was calculated. Friedman test was used to analyze the discrepancy, and the Bonferroni test was used to verify the differences between the pairs. RESULTS: Statistical significance was found with respect to the type of 3D model fabrication method. CONCLUSION: Within the limitations of this in vitro study, the results suggested that the workflow can be applied to digital impressions of the maxillofacial region.

Evaluation of shade correspondence between high-translucency pre-colored zirconia and shade tab by considering the influence of cement shade and substrate materials.

Statement of problem: The relation between cement color and abutment substrate material and the corresponding effect on the color accuracy of high-transparency pre-colored zirconia (HT-Zr) remains unclear. Purpose: This in-vitro study aimed to investigate the difference in color accuracy when the HT-Zr is bonded to different materials-based substrates with differently colored resin cement. Materials and methods: Vita A1 shade HT-Zr with 1 mm thickness was used as the testing sample. The samples were first placed on zirconia (ZR), tooth color resin (CR), and metallic (MT) abutment substrates. Subsequently, four differently colored cements (translucent (TR), bleach, opaque, and A2 shade (A2)) were used for bonding HT-Zr onto the substrate, and the non-bonded group was used as the control group (CG). There were 15 groups in total (n = 10 per group). A digital colorimeter was used to obtain Commission Internationale de l'Eclairage (CIELab) color parameters. The translucency parameter (TP00) of the substrate and sample, as well as color difference (ΔE00) and chroma (C) between the different groups were calculated. Additionally, the ΔE00 and TP00 were compared with the moderately unacceptable match of ΔE00 = 3.6. The statistical analysis was conducted using ANOVA and Tukey HSD post-hoc test (α = 0.05). Results: HT-Zr exhibited high translucency (TP00 = 11.02 ± 0.18), and the mean ΔE00 of the testing samples ranged between 2.18 ± 0.20 and 13.14 ± 0.31. The ZR-CG and MT-A2 groups showed the highest and lowest lightness separately. The CR-CG group exhibited the highest C, and the ΔE00 was lower than that of 3.6. The MT-TR group showed the lowest C and the highest ΔE00. The inter-group comparison revealed that the ΔE00 for different cement is mostly lower than the acceptable color match of 1.0; moreover, the ΔE00 for all the substrates, excluding the CG group, is higher than 3.6. Conclusions: The abutment substrate materials and the cement color should be considered with caution when using HT-Zr, with the effect of abutment substrate materials being more apparent in color accuracy. HT-Zr restorations are not recommended for discolored or bleached abutments but only for natural-colored abutments to achieve the optimal color appearance.

Enhancing Dental Cement Bond Strength with Autofocus-Laser-Cutter-Generated Grooves on Polyetheretherketone Surfaces.

Polyetheretherketone (PEEK) is widely used in dentistry owing to its exceptional properties, including its natural appearance; however, existing surface treatment methods for bonding PEEK have limitations. Autofocus laser cutters, known for their precise engraving and cutting capabilities, offer potential for surface treatment of PEEK; thus, the objective of this study was to investigate the creation of laser groove structures on PEEK to enhance its bonding capability with dental resin cement. A dental computer-aided design and manufacturing system was used to fabricate PEEK samples, and three groove patterns (circle, line, and grid) were generated on PEEK surfaces, with air-abrasion used as the control group. The surface characteristics, cell viability, and bond strength were evaluated, and the data were statistically analyzed using one-way analysis of variance and post hoc Tukey's tests (α = 0.05). Laser-treated PEEK exhibited a uniform texture with a groove depth of approximately 39.4 µm, hydrophobic properties with a contact angle exceeding 90°, a surface roughness of 7.3-12.4 µm, consistent topography, and comparable cell viability compared with untreated PEEK. Despite a decrease in bond strength after thermal cycling, no significant intergroup differences were observed, except for the line-shaped laser pattern. These findings indicate that the autofocus laser cutter effectively enhances the surface characteristics of PEEK by creating a uniform texture and grooves, showing promise in improving bonding properties, even considering the impact of thermal cycling effects.

Effect of Various Airborne Particle Abrasion Conditions on Bonding between Polyether-Ether-Ketone (PEEK) and Dental Resin Cement.

The effects of alumina particle size and jet pressure on the bond strength of polyetheretherketone (PEEK) were examined to determine the airborne particle abrasion parameters with minimal effects on PEEK and to achieve optimal bond strength, as a reference for future clinical use. An alumina particle with four particle sizes and three jet pressures was used to air-abrade PEEK. Surface roughness (Ra), morphology, chemical structure, and wettability were analyzed using a stylus profilometer, scanning electron microscope, X-ray diffractometer, and contact angle analyzer, respectively. The shear bond strength (SBS) of PEEK and dental resin cement was analyzed using a universal testing machine (n = 10). The failure modes and debonded fracture surfaces were observed using optical microscopy. Airborne particle abrasion increased the Ra and hydrophobicity of PEEK and deposited alumina residues. The SBS generally decreased after thermal cycling. A large particle size damaged the PEEK surface. The effects of different particle sizes and jet pressures on the SBS were only significant in certain groups. Adhesive failure was the main mode for all groups. Within the limitations of this study, 110 µm grain-sized alumina particles combined with a jet pressure of 2 bar prevented damage to PEEK, providing sufficient SBS and bonding durability between PEEK and dental resin cement.

Optimizing Dental Bond Strength: Insights from Comprehensive Literature Review and Future Implications for Clinical Practice.

This review examines the modifying factors affecting bond strength in various bonding scenarios, particularly their relevance to the longevity of dental restorations. Understanding these factors is crucial for improving clinical outcomes in dentistry. Data were gathered from the PubMed database, ResearchGate, and Google Scholar resources, covering studies from 1992 to 2022. The findings suggest that for dentin-resin bonds, minimizing smear layers and utilizing MMP inhibitors to prevent hybrid layer degradation are essential. In the case of resin-resin bonds, reversing blood contamination is possible, but preventing saliva contamination is more challenging, underscoring its critical importance during clinical procedures. Additionally, while pretreatment on ceramics has minimal impact on bond strength, the influence of specific colorings should be carefully considered in treatment planning. This comprehensive review highlights that although established practices recognize significant bond strength factors, ongoing research provides valuable insights to enhance the clinical experience for patients. Once confirmed through rigorous experimentation, these emerging findings should be swiftly integrated into dental practice to improve patient outcomes.

Lansoprazole and zoledronate delays hard tissue healing of tooth extraction sockets in dexamethasone-treated mice.

Proton pump inhibitors (PPIs) are among the most commonly prescribed medicines for the management of acid-related gastrointestinal diseases. Osteonecrosis of the jaw (ONJ) is a serious adverse event that is associated with the use of antiresorptive and antiangiogenic agents. According to previous clinical reports, the use of PPIs contributes to the pathogenesis of severe ONJ that requires surgery. Here, we investigated the effects of lansoprazole (LP) or LP in combination with zoledronate (ZOL) on ONJ development in mice. C57BL/6J mice were administered ZOL (125 µg/kg intravenously, twice weekly) and/or LP (10 mg/kg intraperitoneally; 3 weeks of 3 consecutive days followed by 1 day off). One week after initiation of the study, the first molar was atraumatically extracted. Concurrently with ZOL administration, dexamethasone (Dex) was administered (5 mg/kg intraperitoneally, twice weekly). Micro-computed tomography and histological evaluation were performed to characterize femoral structures, tooth extraction sockets, and osteonecrosis areas. The results showed that ZOL/Dex significantly increased bone mass compared to saline/Dex, while the simultaneous administration of LP and ZOL/Dex diminished the ZOL-induced enhancement of bone mass. In the alveolar bone around the tooth extraction socket, necrotic bone was significantly increased in the LP/Dex group compared to the saline/Dex group. However, no signs of more severe ONJ-like lesions were observed following combined administration of LP and ZOL/Dex, other than an increase in the number of non-attached TRAP-positive cells. Our findings in a mouse model suggest that LP use can be a risk factor for the development of ONJ.

Influence of dental abrasives on surface roughness, gloss, and color of titanium.

PURPOSE: The influence of three dental abrasives on the surface roughness, glossiness, and color of titanium (Ti) after mechanical polishing was investigated. METHODS: The specimens were divided into groups, referred to as SM, SR, and TP, to distinguish the different polishing processes. SM: rubber polishing using a rubber point containing SiC abrasive particles at 20,000 rpm, followed by gloss polishing; SR: rubber polishing using a rubber point containing Al2O3 abrasive particles at 20,000 rpm, followed by gloss polishing; TP: rubber polishing using a rubber point containing TiO2 abrasive particles at 6,000 rpm, followed by gloss polishing. Gloss polishing was carried out at 10,000 rpm using a leather buffing wheel. Measurements to evaluate the surface conditions of Ti were performed after each polishing process. RESULTS: There were no significant differences in the Ra and glossiness values between the SM and TP groups; these specimens were not as smooth and glossy as the SR group. The SM group showed relatively high values of lightness and chroma after gloss polishing. CONCLUSION: Rubber polishing with abrasives containing SiC or TiO2 particles before gloss polishing did not achieve appropriate surface conditions on Ti.

Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs.

The aim of the feasibility study was to construct deep learning models for the classification of multiple dental anomalies in panoramic radiographs. Panoramic radiographs with single supernumerary teeth and/or odontomas were considered the "case" group; panoramic radiographs with no dental anomalies were considered the "control" group. The dataset comprised 150 panoramic radiographs: 50 each of no dental anomalies, single supernumerary teeth, and odontomas. To classify the panoramic radiographs into case and control categories, we employed AlexNet, which is a convolutional neural network model. AlexNet was able to classify whole panoramic radiographs into two or three classes, according to the presence or absence of supernumerary teeth or odontomas. The performance metrics of the three-class classification were 70%, 70.8%, 70%, and 69.7% for accuracy, precision, sensitivity, and F1 score, respectively, in the macro average. These results support the feasibility of using deep learning to detect multiple dental anomalies in panoramic radiographs.

Evaluation of trabecular bone formation in a canine model surrounding a dental implant fixture immobilized with an antimicrobial peptide derived from histatin.

JH8194 induces osteoblast differentiation, although it was originally designed to improve antifungal activity. This suggests that JH8194 is useful for implant treatment. Therefore, the aim of this study was to evaluate the osseointegration capacity of JH8194-modified titanium dental implant fixtures (JH8194-Fi). The implants were randomly implanted into the edentulous ridge of dog mandibles. Healing abutments were inserted immediately after implant placement. Three weeks later, peri-implant bone levels, the first bone-to-implant contact points, and trabecular bone formation surrounding the implants were assessed by histological and digital image analyses based on microcomputed tomography (microCT). The histological analysis revealed an enhancement of mature trabecular bone around the JH8194-Fi compared with untreated fixtures (control-Fi). Similarly, microCT combined with analysis by Zed View™ also showed increased trabecular bone formation surrounding the JH8194-Fi compared with the control-Fi (Student's t-test, P < 0.05). JH8194 may offer an alternative biological modification of titanium surfaces to enhance trabecular bone formation around dental implants, which may contribute to the transient acquirement of osseointegration and the long-term success of implant therapy.

Landmark annotation and mandibular lateral deviation analysis of posteroanterior cephalograms using a convolutional neural network.

BACKGROUND/PURPOSE: Facial asymmetry is relatively common in the general population. Here, we propose a fully automated annotation system that supports analysis of mandibular deviation and detection of facial asymmetry in posteroanterior (PA) cephalograms by means of a deep learning-based convolutional neural network (CNN) algorithm. MATERIALS AND METHODS: In this retrospective study, 400 PA cephalograms were collected from the medical records of patients aged 4 years 2 months-80 years 3 months (mean age, 17 years 10 months; 255 female patients and 145 male patients). A deep CNN with two optimizers and a random forest algorithm were trained using 320 PA cephalograms; in these images, four PA landmarks were independently identified and manually annotated by two orthodontists. RESULTS: The CNN algorithms had a high coefficient of determination (R 2 ), compared with the random forest algorithm (CNN-stochastic gradient descent, R 2  = 0.715; CNN-Adam, R 2  = 0.700; random forest, R 2  = 0.486). Analysis of the best and worst performances of the algorithms for each landmark demonstrated that the right latero-orbital landmark was most difficult to detect accurately by using the CNN. Based on the annotated landmarks, reference lines were defined using an algorithm coded in Python. The CNN and random forest algorithms exhibited similar accuracy for the distance between the menton and vertical reference line. CONCLUSION: Our findings imply that the proposed deep CNN algorithm for detection of facial asymmetry may enable prompt assessment and reduce the effort involved in orthodontic diagnosis.

Alterations to Titanium Surface Depending on the Fluorides and Abrasives in Toothpaste.

Fluoride and abrasives in toothpastes may cause corrosion and deterioration of the titanium used for implants and other prostheses. The purpose of this study was to investigate how the presence or absence and types of fluoride and abrasives affected the titanium surface texture. Brushing with toothpastes was performed on pure-titanium discs using an abrasive testing machine. Unprocessed titanium discs without brushing were used as control samples. Surface roughness, color, and gloss of titanium were measured and the differences compared with the control were analyzed. Additionally, titanium surfaces and abrasives in toothpastes were observed using a scanning electron microscope to compare the surface texture of each sample. Some toothpastes (abrasive+) significantly increased the difference in surface roughness, color, and gloss, compared with ultrapure water. Toothpaste (fluoride+/abrasive+) that had many polygonal abrasive particles led to the largest color differences and exhibited notable scratches and a larger number of contaminant- or corrosion-like black spots. In contrast, brushing with toothpaste without fluoride or abrasives (fluoride-/abrasive-) caused little change to the titanium surface. These results suggest that both fluoride and abrasives in toothpaste used for brushing may be factors that affect surface texture and corrosion resistance of titanium.

Biofilm Formation on the Surface of (Poly)Ether-Ether-Ketone and In Vitro Antimicrobial Efficacy of Photodynamic Therapy on Peri-Implant Mucositis.

Poly-ether-ether-ketone (PEEK) is an aesthetically pleasing natural material with good biocompatibility and shock absorption characteristics. The application of PEEK as a dental implant or abutment is expected to reduce the risk of failure and enhance aesthetics. Given that approximately one in 15 patients have allergic reactions to antibiotics, photodynamic therapy (PDT) has been gaining attention as an alternative treatment. Herein, the applicability of PEEK dental implants or abutments was investigated using material analyses, biofilm formation assay, and cell viability tests. The possible use of PDT for peri-implant mucositis was evaluated with the biofilm removal assay. The obtained data were analyzed based on the multivariate analysis of variance, paired t-tests, and the Pearson correlation coefficient (α = 0.05). The results revealed that PEEK was significantly less conducive to the formation of biofilms with S. mutans and A. actinomycetemcomitan (p < 0.001) but exhibited comparable MG-63 (human osteoblast-like) osteoblast cell viability (p > 0.05) to the other materials. PDT had similar antimicrobial efficacy and yielded similar biofilm removal effects to antibiotics. Altogether, these findings suggest that PEEK has attractive features and can serve as an alternative material for dental implants or abutments. In cases where peri-implant mucositis occurs, PDT can be used as an accessible therapeutic approach.

Immobilized-OPG-Fc on a titanium surface inhibits RANKL-dependent osteoclast differentiation in vitro.

The purpose of the present study was to examine the effect of osteoprotegerin (OPG)-Fc fusion protein immobilized on a titanium surface on the initial differentiation of osteoclast precursor RAW264.7 cells. These cells were cultured on titanium specimens over which OPG-Fc was immobilized. The enhancement of tartrate-resistant acid phosphatase (TRAP) and cathepsin K mRNA expression in RAW264.7 cells exposed to receptor activator of NF-kappaB ligand (RANKL) stimulation on OPG-Fc-coated titanium was significantly lower than that in RAW264.7 cells exposed to RANKL on titanium specimens without immobilized OPG-Fc (ANOVA, P < 0.01). Preincubation of OPG-Fc-coated titanium, in a medium supplemented with 10% fetal bovine serum at 37 degrees C for two days before the cells were seeded, had no significant effect on the decrease in mRNA expression (ANOVA, P < 0.01). Taken together, these results indicate that OPG-Fc immobilized on a titanium surface blocks the differentiation of RAW264.7 cells induced by RANKL stimulation.

Titanium immobilized with an antimicrobial peptide derived from histatin accelerates the differentiation of osteoblastic cell line, MC3T3-E1.

The objective of this study was to evaluate the effect of titanium immobilized with a cationic antimicrobial peptide (JH8194) derived from histatin on the biofilm formation of Porphyromonas gingivalis and differentiation of osteoblastic cells (MC3T3-E1). The titanium specimens (Ti) were immobilized with JH8194, according to the method previously described. The colonization of P. gingivalis on JH8194-Ti was significantly lower than that on control- and blocking-Ti. JH8194-Ti enhanced the mRNA expressions of Runx2 and OPN, and ALPase activity in the MC3T3-E1, as compared with those of control- and blocking-Ti. These results, taken together, suggested the possibility that JH8194-Ti may be a potential aid to shorten the period of acquiring osseointegration.

Applying deep artificial neural network approach to maxillofacial prostheses coloration.

PURPOSE: Maxillofacial prosthetic rehabilitation replaces missing structures to recover the function and aesthetics relating to facial defects or injuries. Deep learning is rapidly expanding with respect to applications in medical fields. In this study, we apply the artificial neural network (ANN)-based deep learning approach to coloration support for fabricating maxillofacial prostheses. METHODS: We compared two machine learning algorithms, ANN-based deep learning and the random forest algorithm, to determine the compounding amount of pigment. We prepared 52 silicone elastomer specimens of varying colors and measured the CIE 1976 L* a* b* color space information using a spectrophotometer on the input dataset. The output of these algorithms indicated the compounding amount of four pigments. According to the algorithms' pigment compounding predictions, we prepared the specimens for validation analysis and measured the CIE 1976 L* a* b* values. We determined the color differences between the real skin color of five research participants (22.3 ± 1.7 years) and that of the silicone elastomer specimens fabricated based on the algorithm predictions using the CIEDE00 ΔE00 color system. RESULTS: The color differences (ΔE00 value) between the real skin color and silicone elastomer validation specimens were 3.45 ± 0.87 (ANN) and 5.54 ± 1.41 (random forest), which indicates that the deep ANN approach produced superior results with respect to the ΔE00 value compared with the random forest algorithm. CONCLUSIONS: These results suggest that applying deep ANN is a promising technique for the coloration of maxillofacial prostheses.