Background and Objectives: Bromelain is a mixture of protease obtained from pineapple fruits or stems. Even though the biological mechanism of action of bromelain has not been completely understood, it is well known that bromelain possesses anticancer, anti-inflammatory and immunomodulatory effects. This study investigated the anti-inflammatory effects of bromelain on lipopolysaccharide (LPS)-induced human dental pulp cells (hDPCs). Materials and Methods: Cell viability after bromelain treatment was measured using WST-1 assay. We exposed hDPCs to 5 µg/mL of LPS with 2.5 or 5 µg/mL of bromelain. We performed reverse-transcription polymerase chain reaction and enzyme-linked immunosorbent assay to detect interleukin-1β, interleukin-6, and interleukin-8 levels. Western blots were used to detect intercellular adhesion molecules-1 (ICAM-1) and vascular cell adhesion molecules-1 (VCAM-1) levels. Immunofluorescence staining and Western blots were used to determine bromelain’s anti-inflammatory mechanism. We also performed alkaline phosphatase and Alizarin red staining to verify mineralization nodule formation. Results: Bromelain at 2.5, 5, 10, or 20 µg/mL did not affect the viability of hDPCs significantly. LPS increased interleukin-1β, interleukin-6, interleukin-8, ICAM-1 and VCAM-1 expression in hDPCs. Bromelain significantly decreased interleukin-1β, interleukin-6, interleukin-8, ICAM-1, and VCAM-1 levels in hDPCs, which were stimulated by LPS. Bromelain treatment significantly reduced p65 phosphorylation in the cytoplasm and the nucleus. It also significantly decreased phosphorylation levels of extracellular signal-related kinases (ERK) and p38 mitogen-activated protein kinases (p38). Bromelain also promoted ALP activity and mineralized nodule formation. Conclusions: Bromelain inhibits the expression of inflammatory cytokines in LPS-stimulated hDPCs. The inhibitory effect of bromelain on inflammatory mediators is related to decreased NF-κB and the MAPK pathway. Therefore, bromelain might have the potential to be used for regenerative endodontics, including vital pulp therapy.

The value of the temporomandibular joint (TMJ) projections of panoramic radiography for diagnosing TMJ osteoarthritis is not completely elucidated. This study aimed to assess the diagnostic accuracy and reliability of panoramic TMJ radiography to detect bony lesions in patients with TMJ osteoarthritis. This study included 55 TMJs of 44 subjects who were diagnosed with TMJ osteoarthritis. They underwent panoramic radiography (PanRad), lateral (LatTMJ) and frontal (FrnTMJ) projection panoramic TMJ radiography, and cone-beam computed tomography (CBCT). All images were examined by two observers for flattening, erosion, and osteophytes on the condylar head and articular eminence of the TMJ. For detecting flattening lesions on the mandibular condyle, the sensitivities of PanRad, LatTMJ, and FrnTMJ were less than 67% and the combination of LatTMJ and FrnTMJ (ComTMJ) had the highest sensitivity for both observers (67.6% and 79.7%, respectively). For erosion lesions, the sensitivity of ComTMJ for observer 1 was the highest, at 84.3%, whereas the specificity of ComTMJ was the lowest, at 37.5%. The sensitivities of all four methods for observer 2 were less than 54% and the specificities ranged from 75.0% to 100%. The overall diagnostic accuracy was highest for ComTMJ (64.3%), followed by LatTMJ (59.5%). The intraobserver reliability was good for one observer and excellent for the other, and the interobserver reliability was fair or moderate. Panoramic TMJ radiography demonstrated limited diagnostic accuracy and acceptable reliability in detecting bony lesions of the TMJ, although it was better than conventional panoramic radiography.

Objective: Mid-to-long term use of provisional crowns in the oral cavity is associated with bacterial adhesion and biofilm formation, thus necessitating provisional crowns exhibiting antibacterial properties to prevent the occurrence of gingivitis and periodontal disease. This study aimed to evaluate the antibacterial effect of zirconia nanoparticle-containing polyethyl methacrylate (PEMA) resin for provisional restorations. Methods: Zirconia nanoparticles were added to the monomer of PEMA resin for provisional restorations, and the mixture was stirred for 2 h using a magnetic stirrer. Disk-shaped specimens were prepared by mixing the polymer with the nanoparticle solution. The control group contained pure PEMA resin samples, and the experimental groups Group Z2, Group Z4, and Group Z8 included PEMA resin specimens containing 2, 4, and 8% w/v zirconia nanoparticles, respectively. After analyzing the sample surfaces, the antibacterial effect of the specimens was evaluated using Streptococcus mutans. Statistical analysis was performed using Tukey’s test and Mann–Whitney U-test, according to the normality result in the Shapiro–Wilk test. Results: FE-SEM and EDX analyses revealed the successful addition of zirconia nanoparticles. Results showed no significant difference in the measured values for surface roughness and contact angle between the experimental and control groups; however, adhesion and biofilm thickness of S. mutans were significantly decreased in Group Z2, Group Z4, and Group Z8 compared to the control group (P < 0.05, P < 0.01, P < 0.01, respectively). Conclusion: The addition of zirconia nanoparticles can lower the incidence of adhesion and biofilm thickness of S. mutans on PEMA resin used for provisional crowns. Thus, incorporating zirconia nanoparticles in repair materials for provisional crowns and PEMA resin can produce an antibacterial effect and prevent gingivitis, periodontal disease, and dental caries.

The relationship between serum vitamin D levels and temporomandibular disorders (TMDs) remains unclear. Therefore, this study aimed to investigate the association between serum 25-hydroxyvitamin D (25[OH]D) levels and TMD incidence using large-scale health data. Clinical data from the electronic health records of six secondary or tertiary hospitals in Korea were used to evaluate the relationship between serum 25(OH)D levels and TMD incidence. The data were converted to the Observational Medical Outcomes Partnership Common Data Model. A cohort study was designed using the Cox proportional hazards model to examine the hazard ratio (HR) of TMD development after propensity score matching (PSM). An aggregate meta-analysis of the HR was subsequently performed. After 1:4 PSM, a target group with deficient 25(OH)D levels (<20 ng/mL) (N = 34,560) and comparator group with non-deficient 25(OH)D levels (≥20 ng/mL) (N = 47,359) were pooled from six hospital databases. HR meta-analysis demonstrated a significant association between deficient 25(OH)D levels and TMD incidence (pooled HR: 1.50; 95% confidence interval: 1.07–2.12). In conclusion, deficient 25(OH)D levels were found to be associated with an increased TMD risk. Therefore, vitamin D deficiency is a potential risk factor for TMD development.

To evaluate the repeatability of the surface EMG variables of myoelectric signals from the masseter and temporalis muscles according to three methods to induce maximum voluntary contraction (MVC) i...

Background and Objective: The tongue mucosa often changes due to various local and systemic diseases or conditions. This study aimed to investigate whether deep learning can help detect abnormal regions on the dorsal tongue surface in patients and healthy adults. Materials and Methods: The study collected 175 clinical photographic images of the dorsal tongue surface, which were divided into 7782 cropped images classified into normal, abnormal, and non-tongue regions and trained using the VGG16 deep learning model. The 80 photographic images of the entire dorsal tongue surface were used for the segmentation of abnormal regions using point mapping segmentation. Results: The F1-scores of the abnormal and normal classes were 0.960 (precision: 0.935, recall: 0.986) and 0.968 (precision: 0.987, recall: 0.950), respectively, in the prediction of the VGG16 model. As a result of evaluation using point mapping segmentation, the average F1-scores were 0.727 (precision: 0.717, recall: 0.737) and 0.645 (precision: 0.650, recall: 0.641), the average intersection of union was 0.695 and 0.590, and the average precision was 0.940 and 0.890, respectively, for abnormal and normal classes. Conclusions: The deep learning algorithm used in this study can accurately determine abnormal areas on the dorsal tongue surface, which can assist in diagnosing specific diseases or conditions of the tongue mucosa.