Background: Facial symmetry severely affects appearance and function. Large numbers of patients seek orthodontic treatment to improve facial symmetry. However, the correlation between hard- and soft-tissue symmetry is still unclear. Our aim was to investigate the hard- and soft-tissue symmetry in subjects with different levels of menton deviation and sagittal skeletal classes with 3D digital analysis and to investigate the relationship between the entire and individual hard- and soft-tissues. Methods: A total of 270 adults (135 males and 135 females) consisting of 45 subjects of each sex in each sagittal skeletal classification group. All subjects were further classified into relative symmetry (RS), moderate asymmetry (MA) and severe asymmetry (SA) groups based on the degree of menton deviation from the mid-sagittal plane (MSP). The 3D images were segmented into anatomical structures and mirrored across the MSP after establishing a coordinate system. Original and mirrored images were registered by a best-fit algorithm, and the corresponding root mean square (RMS) values and colormap were obtained. The Mann‒Whitney U test and Spearman correlation were conducted for statistical analysis. Results: The RMS increased with greater deviations with regard to the deviation of the menton in most of anatomical structures. Asymmetry was represented in the same way regardless of sagittal skeletal pattern. The soft-tissue asymmetry had a significant correlation with dentition in the RS group (0.409), while in the SA group, it was related to the ramus (0.526) and corpus (0.417) in males and was related to the ramus in the MA (0.332) and SA (0.359) groups in females. Conclusions: The mirroring method combining CBCT and 3dMD provides a new approach for symmetry analysis. Asymmetry might not be influenced by sagittal skeletal patterns. Soft-tissue asymmetry might be reduced by improving the dentition in individuals with RS group, while among those with MA or SA, whose menton deviation was larger than 2 mm, orthognathic treatment should be considered.

Background: Three-dimensional facial soft tissue landmark prediction is an important tool in dentistry, for which several methods have been developed in recent years, including a deep learning algorithm which relies on converting 3D models into 2D maps, which results in the loss of information and precision. Methods: This study proposes a neural network architecture capable of directly predicting landmarks from a 3D facial soft tissue model. Firstly, the range of each organ is obtained by an object detection network. Secondly, the prediction networks obtain landmarks from the 3D models of different organs. Results: The mean error of this method in local experiments is $2.62\pm 2.39$, which is lower than that in other machine learning algorithms or geometric information algorithms. Additionally, over 72% of the mean error of test data falls within $\pm 2.5$ mm, and 100% falls within 3 mm. Moreover, this method can predict 32 landmarks, which is higher than any other machine learning-based algorithm. Conclusions: According to the results, the proposed method can precisely predict a large number of 3D facial soft tissue landmarks, which gives the feasibility of directly using 3D models for prediction.

Metabolic alterations in chondrocytes play a crucial role in the progression of temporomandibular joint osteoarthritis (TMJOA). However, the precise molecular mechanisms underlying these changes remain poorly understood. In this study, we identify ubiquitin-specific protease 32 (USP32) as a key regulator of TMJOA progression through its interaction with pyruvate kinase M2 (PKM2), a vital enzyme in glycolysis. Our results demonstrate that USP32 is significantly upregulated in TMJOA cartilage and inflammatory chondrocytes. USP32 stabilizes PKM2 by removing K48- and K11-linked ubiquitin chains, thereby preventing its proteasomal degradation. This stabilization promotes the accumulation of PKM2, leading to enhanced glycolysis, increased lactate production, and mitochondrial dysfunction, all of which exacerbate chondrocyte apoptosis and the degradation of extracellular matrix. Knocking down USP32 or PKM2 mitigates these detrimental effects, restoring mitochondrial function and reducing inflammation. Furthermore, cartilage-specific knockdown of USP32 alleviates TMJOA pathology in a rat model, highlighting the therapeutic potential of targeting the USP32-PKM2 axis. Our findings reveal a novel mechanism through which USP32 regulates chondrocyte metabolism and inflammation via PKM2 deubiquitination, providing new insights into the pathogenesis of TMJOA and potential therapeutic strategies for its treatment.

The aesthetic improvement of the midface is a critical goal in treating growing children with Angle Class III malocclusion. While the skeletal effects of m