华西口腔医学杂志最新文献

Objectives: The current study aimed to investigate the bonding properties of a novel low-shrinkage resin adhesive containing expanding monomer and epoxy resin monomer after thermal cycling aging treatment.

Methods: Expanding monomer of 3,9-diethyl-3,9-dimethylol-1,5,7,11-tetraoxaspiro-[5,5] undecane (DDTU) as an anti-shrinkage additive and unsaturated epoxy monomer of diallyl bisphenol A diglycidyl ether (DBDE) as a coupling agent were synthesized. A blend of DDTU and DBDE at a mass ratio of 1∶1, referred to as "UE", was added into the resin matrix at the mass fraction of 20% to prepare a novel low-shrinkage resin adhesive.Then, the methacrylate resin adhesive without UE was used as the blank control group, and a commercial resin adhesive system was selected as the commercial control group. Moreover, the resin-dentin bonding and micro-leakage testing specimens were prepared for the thermal cycling aging treatment. The bonding strength was tested, the fracture modes were calculated, the bonding fracture surface was observed by scanning electron microscope (SEM), and the dye penetration was used to evaluate the tooth-restoration marginal interface micro-leakage. All the data were analyzed statistically.

Results: After aging, the dentin bonding strength of the experimental group was (19.20±1.03) MPa without a significant decrease (P>0.05), that of the blank control group was (11.22±1.48) MPa with a significant decrease (P<0.05) and that of the commercial control group was (19.16±1.68) MPa without a significant decrease (P>0.05). The interface fracture was observed as the main fracture mode in each group after thermal cycling by SEM. The fractured bonding surfaces of the experimental group often occurred on the top of the hybrid layer, whereas those of the blank and commercial control groups mostly occurred on the bottom of the hybrid layer. Micro-leakage rating counts of specimens before and after thermal cycling were as follows: the experimental group was primarily 0 grade, thereby indicating that a relatively ideal marginal sealing effect could be achieved (P>0.05); meanwhile, the blank control group was primarily 1 grade, and the penetration depth of dye significantly increased after thermal cycling (P<0.05); the commercial control group was primarily 0 grade without statistical difference before and after thermal cycling (P>0.05), while a significant difference was observed between the commercial control group and experimental group after thermal cycling (P<0.05).

Conclusions: The novel low-shrinkage resin adhesive containing 20%UE exhibited excellent bonding properties even after thermal cycling aging treatment, thereby showing a promising prospect for dental application.

Post-and-core crown is one of the most common forms of restoration of tooth after root canal therapy (RCT). Infection control is the core objective of RCT, which is usually well realized by endodontists. However, many prosthodontists often neglect the infection control of the tooth and the maintenance of the curative effect of RCT during the process of post-and-core crown, which may lead to the failure of the final restoration. The concept of integrated crown-root treatment advocated recently requires clinicians to consider the RCT and final restoration as a whole, rather than simply divided into two parts-endodontic treatment and restorative treatment. As the core content of integrated crown-root treatment, infection control should be taken seriously by clinicians and implemented throughout the whole treatment process, especially in the restorative treatment that is easily overlooked after RCT. Therefore, this article describes the infection control of post-and-core crown restoration, classifies the tooth requiring post-and-core crown restoration, and puts forward the measures of infection control before and during post-and-core crown restoration, in order to provide reference and guidance for clinical practice.

Objectives: This study aimed to investigate the clinical characteristics of congenital deciduous teeth absence and its permanent teeth performance type by using panoramic radiographs.

Methods: A total of 15 749 panora-mic radiographs of 3-6-year-old children with deciduous dentition were collected from January 2020 to December 2021. The incidence of congenital deciduous teeth absence was observed, and the abnormality of permanent teeth was recor-ded. SPSS 24.0 software was used for statistical analysis.

Results: The incidence of congenital deciduous teeth absence was 2.54% (400/15 749), which was found in 217 girls and 183 boys, and the difference between the genders was statistically significant (P=0.003). The absence of one and two deciduous teeth accounted for 99.75% (399/400) of the subjects. In addition, 92.63% (490/529) of mandibular deciduous lateral incisor was congenitally absent, 44.80% (237/529) of deciduous teeth was absent in the left jaw, and less than 55.20% (292/529) was absent in the right; the difference between them was statistically significant (P=0.017). The absence of 96.41% (510/529) deciduous teeth in the mandibular was significantly more than that of 3.59% (19/529) in the maxillary, and the difference between was statistically significant (P=0.000). Furthermore, 68.00% (272/400) and 32.00% (128/400) of deciduous teeth were absent in unilateral and bilateral, respectively, and the difference was statistically significant (P=0.000). Four types of congenital deciduous teeth absence with permanent teeth were observed as follows: 1) 73.91% (391/529) of permanent teeth was absent; 2) 20.60% (109/529) of permanent teeth was not absent; 3) the number of fused permanent teeth accounted for 4.91% (26/529); 4) the number of supernumerary teeth was 0.57% (3/529).

Conclusions: Although the absence of congenital deciduous teeth is less common than that of permanent teeth, it affects deciduous and permanent teeth to some extent. Dentists should pay attention to trace and observe whether abnormalities are present in the permanent teeth and take timely measures to maintain children's oral health.

Objectives: This study aimed to observe the color rebound and rebound rates of non-pulp discolored teeth within 1 year after routine internal bleaching to guide clinical practice and prompt prognosis.

Methods: In this work, the efficacy of bleaching was observed in 20 patients. The color of discolored teeth was measured by using a computerized colorimeter before bleaching; immediately after bleaching; and at the 1st, 3rd, 6th, 9th, and 12th months after bleaching. The L*, a*, and b* values of the color of cervical, mesial, and incisal parts of the teeth were obtained, and the color change amounts ΔE*, ΔL*, Δa*, and Δb* were calculated. The overall rebound rate (P*) and the color rebound velocity (V*) were also analyzed over time.

Results: In 20 patients following treatment, the average ΔE* of tooth color change was 14.99. After bleaching, the neck and middle of the teeth ΔE* and ΔL* decreased in the 1st, 3rd, 6th, 9th, and 12th months, and the differences were statistically significant. Meanwhile, from the 9th month after bleaching, the rebound speed was lower than that in the 1st month, and the difference was statistically significant. The incisal end of the tooth ΔE* and ΔL* decreased in the 6th, 9th, and 12th months after bleaching, and the differences were statistically significant. No significant difference was found in the rebound speed between time points. However, this rate settled after the 9th month, with an average color rebound rate of 30.11% in 20 patients.

Conclusions: The results indicated that internal bleaching could cause a noticeable color change on pulpless teeth. The color rebound after bleaching was mainly caused by lightness (L*), which gradually decreased with time, and it was slightly related to a* and b*. The color of the teeth after internal bleaching rebounded to a certain extent with time, but the color rebound speed became stable from the 9th month. Clinically, secondary internal bleaching can be considered at this time according to whether the colors of the affected tooth and the adjacent tooth are coordinated and depending on the patient's needs.

Objectives: This study aims to predict the risk of deep caries exposure in radiographic images based on the convolutional neural network model, compare the prediction results of the network model with those of senior dentists, evaluate the performance of the model for teaching and training stomatological students and young dentists, and assist dentists to clarify treatment plans and conduct good doctor-patient communication before surgery.

Methods: A total of 206 cases of pulpitis caused by deep caries were selected from the Department of Stomatological Hospital of Tianjin Medical University from 2019 to 2022. According to the inclusion and exclusion criteria, 104 cases of pulpitis were exposed during the decaying preparation period and 102 cases of pulpitis were not exposed. The 206 radiographic images collected were randomly divided into three groups according to the proportion: 126 radiographic images in the training set, 40 radiographic images in the validation set, and 40 radiographic images in the test set. Three convolutional neural networks, visual geometry group network (VGG), residual network (ResNet), and dense convolutional network (DenseNet) were selected to analyze the rules of the radiographic images in the training set. The radiographic images of the validation set were used to adjust the super parameters of the network. Finally, 40 radiographic images of the test set were used to evaluate the performance of the three network models. A senior dentist specializing in dental pulp was selected to predict whether the deep caries of 40 radiographic images in the test set were exposed. The gold standard is whether the pulp is exposed after decaying the prepared hole during the clinical operation. The prediction effect of the three network models (VGG, ResNet, and DenseNet) and the senior dentist on the pulp exposure of 40 radiographic images in the test set were compared using receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score to select the best network model.

Results: The best network model was DenseNet model, with AUC of 0.97. The AUC values of the ResNet model, VGG model, and the senior dentist were 0.89, 0.78, and 0.87, respectively. Accuracy was not statistically different between the senior dentist (0.850) and the DenseNet model (0.850)(P>0.05). Kappa consistency test showed moderate reliability (Kappa=0.6>0.4, P<0.05).

Conclusions: Among the three convolutional neural network models, the DenseNet model has the best predictive effect on whether deep caries are exposed in imaging. The predictive effect of this model is equivalent to the level of senior dentists specializing in dental pulp.

Jaw defects caused by various reasons often seriously affect appearance and function. The goal of the treatment of oral and maxillofacial tumors should include the cure of the tumor and the restoration of premorbid function. The development of microsurgery and digital surgery technology has promoted the development of jaw reconstruction with vascularized free bone flap. Good appearance and improved predictability could be obtained with the help of preope-rative visual design. How to rehabilitate occlusal function on the reconstructed jaw and improve the quality of life of patients has become an important research direction. This article discusses the challenge of jaw reconstruction, the selection of vascularized bone flap, the choice of implant timing, the treatment of peri-implant soft tissue, and the influence of radiotherapy on implants after jaw reconstruction.

Dental erosion is characterized by progressively destroyed teeth, which has no relation to bacteria but to chemicals. Some internal factors, such as gastroesophageal reflux induced by bulimia, anorexia, gastrointestinal diseases, or drugs, and external factors, such as diet, drugs, and occupational acid exposure, are considered promotive factors for this disease. This article presents a patient suffering from severe dental erosion in the whole dentition, especially in the maxillary teeth, due to gastroesophageal reflux induced by glucocorticoid therapy for optic neuritis. This article discusses the mechanism between optic neuritis glucocorticoid therapy and dental erosion.

Objectives: This study aims to investigate the effects of tumor-stromal fibroblasts (TSFs) on the proliferation, invasion, and migration of salivary gland pleomorphic adenoma (SPA) cells in vitro.

Methods: Salivary gland pleomorphic adenoma cells (SPACs), TSFs, and peri-tumorous normal fibroblasts (NFs) were obtained by tissue primary culture and identified by immunocytochemical staining. The conditioned medium was obtained from TSF and NF in logarithmic phase. SPACs were cultured by conditioned medium and treated by TSF (group TSF-SPAC) and NF (group NF-SPAC). SPACs were used as the control group. The proliferation, invasion, and migration of the three groups of cells were detected by MTT, transwell, and scratch assays, respectively. The expression of vascular endothelial growth factor (VEGF) in the three groups was tested by enzyme linked immunosorbent assay (ELISA).

Results: Immunocytochemical staining showed positive vimentin expression in NF and TSF. Results also indicated the weak positive expression of α-smooth muscle actin (SMA) and fibroblast activation protein (FAP) in TSFs and the negative expression of α-SMA and FAP in NFs. MTT assay showed that cell proliferation in the TSF-SPAC group was significantly different from that in the NF-SPAC and SPAC groups (P<0.05). Cell proliferation was not different between the NF-SPAC and SPAC groups (P>0.05). Transwell and scratch assays showed no difference in cell invasion and migration among the groups (P>0.05). ELISA showed that no significant difference in VEGF expression among the three groups (P>0.05).

Conclusions: TSFs may be involved in SPA biological behavior by promoting the proliferation of SPACs but has no effect on the invasion and migration of SPACs in vitro. Hence, TSF may be a new therapeutic target in SPA treatment.

Objectives: This study aimed to investigate how naringenin (Nar) affected the anti-inflammatory, vascula-rization, and osteogenesis differentiation of human periodontal ligament stem cells (hPDLSCs) stimulated by lipopolysaccharide (LPS) and to preliminarily explore the underlying mechanism.

Methods: Cell-counting kit-8 (CCK8), cell scratch test, and Transwell assay were used to investigate the proliferation and migratory capabilities of hPDLSCs. Alkaline phosphatase (ALP) staining, alizarin red staining, lumen-formation assay, enzyme-linked immunosorbent assay, quantitative timed polymerase chain reaction, and Western blot were used to measure the expression of osteopontin (OPN), Runt-related transcription factor 2 (RUNX2), vascular endothlial growth factor (VEGF), basic fibroblast growth factor (bFGF), von Willebrand factor (vWF), tumor necrosis factor-α (TNF-α), and interleukin (IL)-6.

Results: We observed that 10 μmol/L Nar could attenuate the inflammatory response of hPDLSCs stimulated by 10 μg/mL LPS and promoted their proliferation, migration, and vascularization differentiation. Furthermore, 0.1 μmol/L Nar could effectively restore the osteogenic differentiation of inflammatory hPDLSCs. The effects of Nar's anti-inflammatory and promotion of osteogenic differentiation significantly decreased and inflammatory vascularization differentiation increased after adding AMD3100 (a specific CXCR4 inhibitor).

Conclusions: Nar demonstrated the ability to promote the anti-inflammatory, vascularization, and osteogenic effects of hPDLSCs stimulated by LPS, and the ability was associated with the stromal cell-derived factor/C-X-C motif chemokine receptor 4 signaling axis.

Objectives: This study aimed to analyze the bacteria in dental caries and establish an optimized dental-ca-ries diagnosis model based on 16S ribosomal RNA (rRNA) data of oral flora.

Methods: We searched the public databa-ses of microbiomes including NCBI, MG-RAST, EMBL-EBI, and QIITA and collected data involved in the relevant research on human oral microbiomes worldwide. The samples in the caries dataset (1 703) were compared with healthy ones (20 540) by using the microbial search engine (MSE) to obtain the microbiome novelty score (MNS) and construct a caries diagnosis model based on this index. Nonparametric multivariate ANOVA was used to analyze and compare the impact of different host factors on the oral flora MNS, and the model was optimized by controlling related factors. Finally, the effect of the model was evaluated by receiver operating characteristic (ROC) curve analysis.

Results: 1) The oral microbiota distribution obviously differed among people with various oral-health statuses, and the species richness and species diversity index decreased. 2) ROC curve was used to evaluate the caries data set, and the area under ROC curve was AUC=0.67. 3) Among the five hosts' factors including caries status, country, age, decayed missing filled tooth (DMFT) indices, and sampling site displayed the strongest effect on MNS of samples (P=0.001). 4) The AUC of the model was 0.87, 0.74, 0.74, and 0.75 in high caries, medium caries, low caries samples in Chinese children, and mixed dental plaque samples after controlling host factors, respectively.

Conclusions: The model based on the analysis of 16S rRNA data of oral flora had good diagnostic efficiency.