Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

With the rapid development of modern technology, the deep integration of computer science and medicine has greatly propelled the field of the dental diagnostics field. Multimodal medical image registration refers to the fusion of information from various modalities of medical imaging. In other words, with the assistance of computer technology, the image data acquired from various radiological examinations undergo spatial registration and are merged to create a comprehensive new image, serving the purpose of computer-aided diagnosis. The temporomandibular joint (TMJ) has complex anatomical structures, so there is a wide range of diseases associated with it. Traditional single-modal imaging methods can only provide partial anatomical information, which limits the comprehensive assessment and subsequently hinders the diagnosis and treatment of TMJ diseases. Multimodal medical image registration techniques, owing to their ability to provide comprehensive information, have been widely applied in the field of dentistry. This has greatly enhanced the efficiency of diagnosing and treating TMJ diseases. The article discusses the advancements in the application of multimodal medical image registration in the context of TMJ diseases.

Establishing a harmonious relationship between the fixed restoration-tooth-periodontium (RTP) at the interface is crucial for achieving successful and long-lasting outcomes in esthetic zone restorations. This paper focuses on this core issue by elucidating the ideal RTP interface relationship, detailing a biological-esthetic dual-axis diagnostic classification for esthetic zone restorations based on RTP interface situation, and discussing clinical decision-making and treatment plans guided by this classification. Furthermore, specific strategies for managing the restoration margins in the esthetic zone are explored, emphasizing approaches that minimize adverse impact and enhance periodontal soft tissue protection on RTP interface in different diagnostic categories.

With the innovation of digital technologies, the personalized fabrication of occlusal splints has shifted from traditional manual methods to an efficient and precise digital workflow. This paper systematically reviews the latest advancements in materials, design technologies, and clinical applications of digital occlusal splints, analyzes core issues in current clinical practice such as insufficient standardization and lack of long-term efficacy evidence, and proposes a dynamic diagnosis-and-treatment protocol based on four-dimensional virtual dental patient technology. Combined with the team′s developed functional anterior repositioning splint system and clinical cases, the innovative advantages in treating anterior disc displacement with reduction of the temporomandibular joint are highlighted: achieving precise jaw position regulation, functional restoration, and serialized treatment through multimodal data fusion. Finally, the paper envisions the optimization direction of full-process integration driven by artificial intelligence and new materials, providing theoretical support for the clinical translation of digital occlusal splints.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

With the rapid development of modern technology, the deep integration of computer science and medicine has greatly propelled the field of the dental diagnostics field. Multimodal medical image registration refers to the fusion of information from various modalities of medical imaging. In other words, with the assistance of computer technology, the image data acquired from various radiological examinations undergo spatial registration and are merged to create a comprehensive new image, serving the purpose of computer-aided diagnosis. The temporomandibular joint (TMJ) has complex anatomical structures, so there is a wide range of diseases associated with it. Traditional single-modal imaging methods can only provide partial anatomical information, which limits the comprehensive assessment and subsequently hinders the diagnosis and treatment of TMJ diseases. Multimodal medical image registration techniques, owing to their ability to provide comprehensive information, have been widely applied in the field of dentistry. This has greatly enhanced the efficiency of diagnosing and treating TMJ diseases. The article discusses the advancements in the application of multimodal medical image registration in the context of TMJ diseases.

Establishing a harmonious relationship between the fixed restoration-tooth-periodontium (RTP) at the interface is crucial for achieving successful and long-lasting outcomes in esthetic zone restorations. This paper focuses on this core issue by elucidating the ideal RTP interface relationship, detailing a biological-esthetic dual-axis diagnostic classification for esthetic zone restorations based on RTP interface situation, and discussing clinical decision-making and treatment plans guided by this classification. Furthermore, specific strategies for managing the restoration margins in the esthetic zone are explored, emphasizing approaches that minimize adverse impact and enhance periodontal soft tissue protection on RTP interface in different diagnostic categories.

With the innovation of digital technologies, the personalized fabrication of occlusal splints has shifted from traditional manual methods to an efficient and precise digital workflow. This paper systematically reviews the latest advancements in materials, design technologies, and clinical applications of digital occlusal splints, analyzes core issues in current clinical practice such as insufficient standardization and lack of long-term efficacy evidence, and proposes a dynamic diagnosis-and-treatment protocol based on four-dimensional virtual dental patient technology. Combined with the team′s developed functional anterior repositioning splint system and clinical cases, the innovative advantages in treating anterior disc displacement with reduction of the temporomandibular joint are highlighted: achieving precise jaw position regulation, functional restoration, and serialized treatment through multimodal data fusion. Finally, the paper envisions the optimization direction of full-process integration driven by artificial intelligence and new materials, providing theoretical support for the clinical translation of digital occlusal splints.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

BACKGROUND:Rapid developments in the field of bioinformatics have provided new methods for the diagnosis of osteoarthritis.Artificial neural networks have powerful data computing and classification capabilities,which have shown better performance in disease diagnosis. OBJECTIVE:To establish a new diagnostic predictive model of osteoarthritis based on artificial neural network and to verify the diagnostic value of the model in osteoarthritis with an external dataset. METHODS:The eligible osteoarthritis-related data sets were downloaded through GEO database search and divided into Train group and Test group.The gene expression matrix of the Train group was analyzed to screen the differentially expressed genes.GO and KEGG enrichment analyses were performed on the differentially expressed genes.Through Lasso regression model,support vector machine model and random forest tree model,the key genes of osteoarthritis were further identified from the differentially expressed genes.The R software"Neuralnet"package was then used to construct the osteoarthritis diagnosis model based on artificial neural network,and the model performance was evaluated by the five-fold cross-validation.Two independent data sets in the Test group were used to verify their diagnostic results. RESULTS AND CONCLUSION:A total of 90 differentially expressed genes related to osteoarthritis were obtained by differential analysis,of which 33 were down-regulated and 57 were up-regulated.GO enrichment analysis showed that the differentially expressed genes were mainly involved in the following biological processes,including leukocyte-mediated immunity,leukocyte migration in bone marrow and chemokine production.KEGG enrichment analysis showed that these genes were mainly enriched in rheumatoid arthritis,interleukin-17 signaling pathway and osteoclast differentiation pathway.Five key genes for the diagnosis of osteoarthritis,HMGB2,GADD45A,SLC19A2,TPPP3 and FOLR2,were identified by three machine learning methods.The artificial neural network model of five key genes in the Train group showed that the accuracy was 96.36%and the area under the curve was 0.997.The five-fold cross validation of the neural network model showed that the average area under the curve was greater than 0.9 and the model was of robustness.Two independent data sets in the Test group showed its area under the curve was 0.814 and 0.788 respectively.Therefore,the establishment of an artificial neural network model for the diagnosis of osteoarthritis has a certain diagnostic value.