Background Direct pulp capping is a vital pulp therapy for a pin-point dental pulp exposure. Applying a pulp capping material leads to the formation of a dentin bridge and protects pulp vitality. The aim of this study was to compare the effects of four dental materials, DyCal®, ProRoot® MTA, Biodentine™, and TheraCal™ LC in vitro. Methods Human dental pulp stem cells (hDPs) were isolated and characterized. Extraction medium was prepared from the different pulp capping materials. The hDP cytotoxicity, proliferation, and migration were examined. The odonto/osteogenic differentiation was determined by alkaline phosphatase, Von Kossa, and alizarin red s staining. Osteogenic marker gene expression was evaluated using real-time polymerase chain reaction. Results ProRoot® MTA and Biodentine™ generated less cytotoxicity than DyCal® and TheraCal™ LC, which were highly toxic. The hDPs proliferated when cultured with the ProRoot® MTA and Biodentine™ extraction media. The ProRoot® MTA and Biodentine™ extraction medium induced greater cell attachment and spreading. Moreover, the hDPs cultured in the ProRoot® MTA or Biodentine™ extraction medium migrated in a similar manner to those in serum-free medium, while a marked reduction in cell migration was observed in the cells cultured in DyCal® and TheraCal™ LC extraction media. Improved mineralization was detected in hDPs maintained in ProRoot® MTA or Biodentine™ extraction medium compared with those in serum-free medium. Conclusion This study demonstrates the favorable in vitro biocompatibility and bioactive properties of ProRoot® MTA and Biodentine™ on hDPs, suggesting their superior regenerative potential compared with DyCal® and TheraCal™.

Objective The aim of this study was to employ artificial intelligence (AI) via convolutional neural network (CNN) for the separation of oral lichen planus (OLP) and non-OLP in biopsy-proven clinical cases of OLP and non-OLP. Materials and Methods Data comprised of clinical photographs of 609 OLP and 480 non-OLP which diagnosis has been confirmed histopathologically. Fifty-five photographs from the OLP and non-OLP groups were randomly selected for use as the test dataset, while the remaining were used as training and validation datasets. Data augmentation was performed on the training dataset to increase the number and variation of photographs. Performance metrics for the CNN model performance included accuracy, positive predictive value, negative predictive value, sensitivity, specificity, and F1-score. Gradient-weighted class activation mapping was also used to visualize the important regions associated with discriminative clinical features on which the model relies. Results All the selected CNN models were able to diagnose OLP and non-OLP lesions using photographs. The performance of the Xception model was significantly higher than that of the other models in terms of overall accuracy and F1-score. Conclusions Our demonstration shows that CNN models can achieve an accuracy of 82 to 88%. Xception model performed the best in terms of both accuracy and F1-score.

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In this article, the reduction of insertion torque on the orthodontic mini-screw implants (OMI) was studied. Three types of diamond-like carbon (DLC) films (DLC, Si-DLC, and F-DLC) were deposited on the OMIs by plasma-based ion implantation technique. The maximum insertion torque (MIT) value was measured using a physiodispenser during insertion on a mandibular pig jaw. Ten OMIs of each condition were used to evaluate the MIT values compared to the Ti-6Al-4V typed OMI. The statistical analysis of data was analyzed by One-way analysis of variance (ANOVA) and Tukey HSD. The results indicated that the Ti-6Al-4V showed the highest MIT but not significantly different from the F-DLC (P >0.05). DLC and Si-DLC showed a significant reduction in MIT comparing to the Ti-6Al-4V (P <0.05). However, the Si-DLC showed the lowest MIT among groups (P <0.05). This phenomenon was due to the decreasing friction coefficient during OMI's insertion on a mandibular pig jaw. Therefore, the DLC coating, especially Si-DLC, could reduce the MIT value of OMI. It is thought that the lowering friction coefficient yields the lowering of MIT value. Keywords: Diamond-like carbon, Friction, Insertion torque, Mini-screw implant