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

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:Knee osteoarthritis(KOA)is a common chronic inflammatory disease that causes damage to joint cartilage and surrounding tissues.Immune cells play an important role in the immune-inflammatory response in knee osteoarthritis,but the specific mechanisms involved are still not fully understood. OBJECTIVE:To evaluate the potential causal relationship between 731 immune cell phenotypes and the risk of knee osteoarthritis using Mendelian randomization. METHODS:Summary statistics of genome-wide association studies(GWAS)for 731 immune cell phenotypes(from GCST0001391 to GCST0002121)obtained from the GWAS catalog and GWAS data for knee osteoarthritis from the IEUGWAS database(ebi-a-GCST007090)were used.Inverse variance-weighted method,MR-Egger regression,weighted median method,weighted mode method,and simple mode method were employed to investigate the causal relationship between immune cells and knee osteoarthritis.Sensitivity analyses were conducted to assess the reliability of the Mendelian randomization results.Reverse Mendelian randomization analysis was also performed using the same methods. RESULTS AND CONCLUSION:The forward MR analysis indicated significant causal relationships(FDR<0.20)between knee osteoarthritis and four immune cell phenotypes,namely CD27 on CD24+CD27+in B cells(OR=1.026,P=0.000 26,Pfdr=0.18),CD33 on CD33dim HLA DR-in myeloid cells(OR=1.014,P=0.000 50,Pfdr=0.18),and CD45RA+CD28-CD8br%CD8br in Treg cells(OR=1.001,P=0.000 78,Pfdr=0.18),and PDL-1 on monocytes in mononuclear cells(OR=0.952,P=0.000 98,Pfdr=0.18).These immune cell phenotypes showed direct positive or negative causal associations with the risk of knee osteoarthritis.Reverse Mendelian randomization analysis revealed no significant causal relationships(FDR<0.20)between knee osteoarthritis as exposure and any of the 731 immune cell phenotypes.The results of sensitivity analysis show that the P-values of the Cochran's Q test and the MR-Egger regression method for bidirectional Mendelian randomization were both greater than 0.05,indicating that there is no significant heterogeneity and pleiotropy in the causal effect analysis between immune cell phenotypes and knee osteoarthritis.To conclude,there may be four potential causal relationships between immune cell phenotypes,such as CD27 on CD24+CD27+cells,CD33 on CD33dim HLA DR-cells,CD45RA+CD28-CD8br%CD8br cells,and PDL-1 on monocytes,and knee osteoarthritis.These findings provide valuable clues for studying the biological mechanisms of knee osteoarthritis and exploring early prevention and treatment strategies.They also offer new directions for the development of intervention drugs.

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.

Objective To identify the characteristic genes associated with osteosarcoma(OS)disulfidptosis by machine learning al-gorithm,and to construct a diagnostic prediction model,so as to provide theoretical support for further exploring the potential biomarkers and molecular mechanisms of early diagnosis of OS.Methods Differential expression analysis was used to identify OS differential expres-sion disulfidptosis-related genes(DE-DRG).The least absolute shrinkage and selection operator(LASSO),support vector machines(SVM)and random forest(RF)algorithms were used to further identify the diagnostically valuable OS disulfidptosis characteristic genes,and evaluated their diagnostic value by plotting the receiver operating characteristic(ROC)curve.At the same time,a nomogram was constructed to assess the risk of disease,and the effective performance of the nomogram was evaluated by calibration curve and clinical de-cision curve.The expression of characteristic genes in OS tissues was detected by real-time quantitative polymerase chain reaction(RT-qPCR).Results A total of two genes(NDUFA11,RPN1)were identified with high diagnostic value of characteristic genes asso-ciated with osteosarcoma(OS)disulfidptosis,and the nomogram constructed had high reliability for predicting disease risk.The results of RT-qPCR showed that NDUFA11 expression was significantly reduced,while RPN1 was significantly increased in OS tissue(P＜0.01).Conclusion The established genetic diagnostic model of OS disulfidptosis in this study has certain diagnostic value.

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.

BACKGROUND:Rheumatoid arthritis is a chronic systemic autoimmune disease.It is important to study the immunological changes involved in it for diagnosis and treatment. OBJECTIVE:To identify immune-related biomarkers associated with rheumatoid arthritis utilizing bioinformatics techniques and examine alterations in immune cell infiltration as well as the relationship between immune cells and biomarkers. METHODS:Differential expression analysis was used to identify the immune-related genes that were up-regulated in rheumatoid arthritis based on the GEO and Immport databases.Kyoto encyclopedia of genes and genomes(KEGG)and gene ontology(GO)enrichment analyses were used to investigate the possible function of these elevated genes.The immunological characteristic genes associated with rheumatoid arthritis were screened using least absolute shrinkage and selection operator(Lasso)and support vector machine recursive feature elimination(SVM-RFE).Independent datasets were used for difference validation,and the diagnostic performance was evaluated by plotting receiver operating characteristic curves for feature genes.Immune cell infiltration was used to analyze the differential profile of immune cells in rheumatoid arthritis and the correlation between the characterized genes and immune cells.In order to ascertain the causal relationship between monocytes and rheumatoid arthritis in immune cells,Mendelian randomization analysis was ultimately employed. RESULTS AND CONCLUSION:There were 39 upregulated differentially expressed genes in rheumatoid arthritis.The genes were primarily enriched in chemotaxis,cytokine activity,and immune receptor activity,according to GO enrichment analysis,while kEGG enrichment analysis revealed that the genes were considerably enriched in the tumor necrosis factor signaling pathway and peripheral leukocyte migration.Lasso and SVM-RFE identified five feature genes:CXCL13,SDC1,IGLC1,PLXNC1,and SLC29A3.Independent dataset validation of the feature genes found them to be similarly highly expressed in rheumatoid arthritis samples,with area under the curve values greater than 0.8 for all five feature genes in both datasets.Immune cell infiltration indicated that most immune cells,including natural killer cells and monocytes,exhibited increased levels of infiltration in rheumatoid arthritis samples.The correlation analysis revealed a significant positive correlation between memory B cells and immature B cells and these five feature genes.Correlation analysis showed that the five feature genes were positively correlated with memory B cells and immature B cells.The inverse variance weighting method revealed that monocytes were associated with the risk of developing rheumatoid arthritis.

Objective: The aim of this study was to investigate the effect of changes in nasal tip protrusion on the sense of upper lip protrusion in different populations and to provide a reference for the improvement of soft tissue beauty. Methods : Informed consent and portrait authorization were obtained from the model. A female model whose face met the criteria was selected, and a 3D model of her was obtained using a 3D stereo camera. Based on the original model, ZBRUSH2019 software was used to simulate changes in nose tip protrusion. Then, 9 segments of facial dynamic rotation videos were produced, and an electronic questionnaire was created through a questionnaire website to evaluate the effect of different nose tip protrusions on perceived upper lip protrusion. Randomly selected orthodontic patients, orthodontics professionals and general adults completed the electronic questionnaire. In the questionnaire, a Visual Analog Scale was used to evaluate the perceived degree of protrusion of the upper lip. The higher the score, the more prominent the upper lip of the model in the image. The questionnaire data were statistically analyzed using a generalized linear mixed model. Results : As the nasal tip position became progressively more retracted, the subjects' upper lip protrusion scores increased. Among male subjects, the results showed that the general population thought that the upper lip protrusion was higher than the patients did when the nasal tip protrusion was +6 mm and +4.5 mm (P = 0.023, P = 0.047). When the nasal tip protrusion was +6 mm, the scores of the general population were higher than those of the orthodontics professionals (P = 0.023). However, when the nasal tip variable was -6 mm, their score was lower than that of the patients (P = 0.003), and there was no significant difference in other retest distances between groups (P>0.05). Conclusion When the protrusion of the nasal tip decreased, the three groups experienced a visual illusion of upper lip protrusion. When the nasal tip protrusion is too large, the general population perceived the visual illusion of the upper lip protrusion as being more obvious.

Objective To analyze the epidemiological characteristics of mumps in Guangxi from 2011 to 2019, and to provide a scientific basis for formulating effective prevention and control strategies. Methods Descriptive epidemiological method was used to analyze the incidence data of mumps in Guangxi from 2011 to 2019. Results From 2011 to 2019, a total of 146,132 cases of mumps were reported in Guangxi, with an average annual incidence rate of 34.23 /100 000. There were 88,919 male cases (60.85%) and 57,213 female cases (39.15%). The incidence rate decreased from 62.26/100 000 in 2011 to 16.46/100 000 in 2015, and increased from 18.60/100 000 in 2016 to 46.90/100 000 in 2019. There were seasonal variations in the incidence, with the incidence peaks occurring from April to July and from October to the following January. 85.39% of cases were under 15 years of age, and 76.82% of cases were among kindergarteners or school children. A total of 228 mumps outbreaks were reported during 2011-2019，including 5,347 cases, accounting for 3.66% of the total cases. The incidence rates of mumps in Nanning (56.09/100 000), Hechi (48.26/100 000), Liuzhou (46.77/100 000), Baise (46.34/100 000) and Fangchenggang (40.68/100,000) were relatively higher than other places. Conclusion The mumps incidence is on an upward trend in Guangxi since 2015-2019, occurring mainly in older children or students. It is suggested to adhere to the second dose of mumps containing vaccine for kindergarten and school children and strengthen the surveillance and outbreak control of mumps in schools.

Objective? To explore the effects of fast track surgery (FTS) nursing on fatigue and quality of life among hepatocellular carcinoma patients. Methods? From June 2017 to June 2018, we selected 80 primary hepatic carcinoma patients with hepatocellular carcinoma resection of hepatobiliary surgery at Peking Union Medical College Cancer Hospital as subjects by convenience sampling. All of the patients were divided into control group and observation group with the method of random number table, 40 cases in each group. Observation group carried out FTS, while control group adopted routine nursing. The intervention effects were compared with the Cancer Fatigue Scale (CFS) and the Quality of Life Questionnaire Core 30 (QLQ-C30). Results? Before intervention, there was no statistical difference in the score of CFS between two groups (P＞0.05). After intervention, the total score and dimension scores of CRF of observation group were lower than those of control group with statistical differences (P＜ 0.01). Before intervention, there was no statistical difference in the score of QLQ-C30 between two groups (P＞ 0.05). After intervention, the total score of QLQ-C30 of observation group was higher than that of control group with a statistical difference (P＜ 0.01). Conclusions? FTS can effectively improve the postoperative fatigue of hepatocellular carcinoma patients and quality of life of patients which is worthy of clinical popularization and application.