Background: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, inconsistency, and low efficiency in imaging diagnosis. Deep learning network may be a solution to improve the accuracy and efficiency of periodontitis imaging staging diagnosis. This study aims to establish a comprehensive and accurate radiological staging model of periodontal alveolar bone loss based on panoramic images. Methods: A total of 640 panoramic images were included, and 3 experienced periodontal physicians marked the key points needed to calculate the degree of periodontal alveolar bone loss and the specific location and shape of the alveolar bone loss. A two-stage deep learning architecture based on UNet and YOLO-v4 was proposed to localize the tooth and key points, so that the percentage of periodontal alveolar bone loss was accurately calculated and periodontitis was staged. The ability of the model to recognize these features was evaluated and compared with that of general dental practitioners. Results: The overall classification accuracy of the model was 0.77, and the performance of the model varied for different tooth positions and categories; model classification was generally more accurate than that of general practitioners. Conclusions: It is feasible to establish deep learning model for assessment and staging radiographic periodontal alveolar bone loss using two-stage architecture based on UNet and YOLO-v4.

Background: Cannabinoid has long been used for medicinal purposes. Cannabinoid signaling has been considered the therapeutic target for treating pain, addiction, obesity, inflammation, and other diseases. Recent studies have suggested that in addition to CB1 and CB2, there are non-CB1 and non-CB2 cannabinoid-related orphan GPCRs including GPR18, GPR55, and GPR119. In addition, CB1 and CB2 display allosteric binding and biased signaling, revealing correlations between biased signaling and functional outcomes. Interestingly, new investigations have indicated that CB1 is functionally present within the mitochondria of striated and heart muscles directly regulating intramitochondrial signaling and respiration.Conclusion: In this review, we summarize the recent progress in cannabinoid-related orphan GPCRs, CB1/CB2 structure, Gi/Gs coupling, allosteric ligands and biased signaling, and mitochondria-localized CB1, and discuss the future promise of this research.