N,N-Dimethylglycine (DMG) is a glycine derivative, and its sodium salt (DMG-Na) has been demonstrated to possess various biological activities, including immunomodulation, free radical scavenging, and antioxidation, collectively contributing to the stability of tissue and cellular functions. However, its direct effects and underlying mechanisms in wound healing remain unclear. In this study, a full-thickness excisional wound model was established on the dorsal skin of mice, and wounds were treated locally with DMG-Na. Wound healing progression was assessed by calculating wound closure rates. Histopathological analysis was conducted using hematoxylin-eosin (HE) staining, and keratinocyte proliferation, migration, and differentiation were evaluated using CCK-8 assays, scratch wound assays, and quantitative reverse transcription PCR (qRT-PCR). Inflammation-related cytokine expression in keratinocytes was analyzed via ELISA and qRT-PCR. Results revealed that DMG-Na treatment significantly accelerated wound healing in mice and improved overall wound closure quality. The wound healing rates on days 3, 6, and 9 were 49.18%, 68.87%, and 90.55%, respectively, with statistically significant differences compared to the control group ( P<0.05). DMG-Na treatment downregulated the mRNA levels of keratinocyte differentiation markers while enhancing cell proliferation and migration ( P<0.05). Furthermore, DMG-Na decreased the secretion of LPS-induced keratinocyte inflammatory cytokines, including IL-1β, IL-6, IL-8, TNF-α, and CXCL10 ( P<0.05). These findings indicate that DMG-Na regulates inflammatory responses and promotes keratinocyte proliferation and migration, thereby facilitating the healing of skin wounds.
Animals ; Wound Healing/drug effects* ; Mice ; Cell Proliferation/drug effects* ; Keratinocytes/drug effects* ; Cell Movement/drug effects* ; Cell Differentiation/drug effects* ; Glycine/pharmacology* ; Skin/injuries* ; Male

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

Objective: To explore the correlation and lag effects of environmental factors on pediatric respiratory disease visits at hospital, so as to provide scientific basis for disease prediction and optimizing clinical diagnosis and treatment. Methods: Data from 503 889 pediatric respiratory disease outpatient and emergency visits a central hospital in Minhang District of Shanghai between 2017 and 2019, along with concurrent meteorological data were collected. A distributed lag non-linear models (DLNM) was constructed to explore the specific relationship between pediatric respiratory disease consultations and various environmental factors and to quantify the cumulative lag effects of environmental factors on respiratory disease consultations. Results: Among the environmental factors, temperature, fine particulate matter (PM 2.5 ), inhalable particulate matter (PM 10 ), nitrogen dioxide (NO 2), and sulfur dioxide (SO 2) were associated with pediatric respiratory disease visits. After adjusting for temperature, PM 2.5 and PM 10 concentrations did not show significant immediate or lag effects. The relative risk (RR) of pediatric respiratory disease visits increased with rising NO 2 concentrations. When NO 2 concentration ≥55 μg/m 3, significant immediate and lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.05, 1.13, 1.17, and 1.21( P <0.05). The RR values showed an inverted “U” shaped relationship with SO 2 concentrations. When SO 2 concentration ≥5 μg/m 3, significant lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.03 , 1.03, and 1.04 ( P <0.05). Conclusion High concentrations of NO 2 and SO 2 increase the risk of pediatric respiratory disease visits, with observable lag effects.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

AIM: To observe the preliminary application of fully automatic feedback perimeter based on the eye gaze tracking technique in the college students and to verify its test performance.METHODS: Home computer, monitor and eye tracker were used to complete the new automatic feedback perimeter meter. Based on the two characteristic eye movements of fixation and pulsation, the abnormal visual field is determined by analyzing whether the participant perceives the visual target, line-of-sight scan path and the fixation towards the visual target. RESULTS: A total of 63 participants(119 eyes)were collected with valid eye movement data. The average time for all participants was 82.46±14.68 s, the average time for right eyes was 88.21±15.30 s, and average time for the left eyes was 76.42±11.29 s(P<0.05).CONCLUSION: The fully automatic feedback perimeter based on eye gaze tracking technique can realize automatic human-computer interaction, and the detection method is simple and easy, which shortens the time of perimetry and improves the experience of participants.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome elements in type 2 diabetes mellitus （T2DM） patients based on maximum body mass index （maxBMI） and explore their association with complication risks. MethodsA retrospective cross-sectional study was used to collect clinical data from hospitalized T2DM patients， extracting age， gender， smoking history， alcohol consumption history， duration of disease， HbA1c level， complications， and TCM syndromes， and extracting the syndrome elements of disease location and disease nature based on their TCM syndromes. MaxBMI was calculated by telephone survey of patients' self-reported maximum body weight； patients with maxBMI ≥24 kg/m² were classified into spleen-heat syndrome group， and those with maxBMI ＜24 kg/m² were classified into consumptive-heat syndrome group. The distribution of TCM syndrome types and syndrome elements of patients in the two groups were analysed. Then the propensity score matching method was used to balance the baseline characteristics between the two groups and compare the differences in the distribution of syndrome types and syndrome elements and the risk of macrovascular and microvascular complications between the two groups. ResultsAmong the 1178 T2DM patients， syndrome elements in spleen-heat patients （1034 cases） were primarily located in the spleen （351 cases， 33.95%）， liver （240 cases， 23.21%）， and stomach （139 cases， 13.44%）， while in consumptive-heat patients （144 cases）， they were concentrated in the spleen （57 cases， 39.58%）， liver （34 cases， 23.61%）， and kidneys （17 cases， 11.81%）； regarding syndrome elements of disease nature， spleen-heat patients were predominantly characterized by qi deficiency （481 cases， 46.52%）， phlegm （353 cases， 22.73%）， and dampness （241 cases， 23.31%）， whereas consumptive-heat patients showed more qi deficiency （84 cases， 58.33%） and yin deficiency （44 cases， 30.56%）. After propensity score matching， 132 cases were included in each group， and no statistically significant differences were observed in the distribution of syndrome elements of disease location between the two groups （P＞0.05）， but the phlegm element was significantly more prevalent in spleen-heat patients than in consumptive-heat patients （P = 0.006）. Regarding the risk of complications， spleen-heat patients had a significantly higher risk of developing macrovascular complications compared to consumptive-heat patients （OR=2.04， P=0.010）， while no significant differences were found between groups in the occurrence of microvascular complications （P＞0.05）. ConclusionThe spleen-heat T2DM patients show a more frequent syndrome element of disease nature of phlegm， and a higher risk of developing macrovascular complications compared to consumptive-heat patients.

Objective: To investigate the expression and functional role of FK506 binding protein 10 (FKBP10) in oral squamous cell carcinoma (OSCC), and to provide a research basis for the estimated prognosis and targeted therapy of OSCC. Methods: A total of 284 OSCC samples and 19 normal samples were selected from the Cancer Genome Atlas (TCGA) database, and diagnostic analysis was performed to determine mRNA expression. Survival analysis for FKBP10 and OSCC was conducted on a gene expression profile interaction analysis website. Real-time fluorescence quantitative PCR and Western Blot were used to detect the mRNA and protein expression of FKBP10 in four OSCC cell lines and SAS and SCC9 cells transfected with siRNA. The cell proliferation ability of FKBP10-silenced cells was detected using the CCK8 method, and the cell cycle distribution and apoptosis were detected by flow cytometry. Cell migration and invasion ability were detected through wound healing and invasion experiments. The expression changes of total protein and phosphatidylinositol 3-kinase (PI3K)-serine/threonine kinase (AKT) after FKBP10 silencing were analyzed by proteomics and Western Blot. Results: According to the analysis of gene expression levels, the mRNA expression level of FKBP10 in OSCC was significantly higher than that in normal tissues (P < 0.001). In terms of diagnosis, the expression level of FKBP10 has unique diagnostic value for OSCC (P < 0.05). The survival analysis of FKBP10 and OSCC showed that a high expression of FKBP10 led to a decrease in patient survival and poor prognosis (P < 0.05). The expression of FKBP10 mRNA and protein in OSCC cell lines was higher than that in normal oral keratinocytes (P < 0.001). Silencing FKBP10 can reduce the proliferation, invasion, and migration ability of SAS and SCC9 (P < 0.001), and also block their cell cycle in the G0/G1 phase (P < 0.001), with a significant increase in apoptosis (P < 0.05). Protein mass spectrometry and Western blot analysis revealed that FKBP10 silencing significantly downregulated the expression of multiple proteins in the RAP1 signaling pathway, mainly RAP guanine nucleotide exchange factor 1 (RAPGEF1) (P < 0.05) and the phosphorylation of PI3K-AKT proteins (P < 0.05). Conclusion FKBP10 is highly expressed in OSCC, leading to poor prognosis for patients. Downregulated FKBP10 expression can inhibit the proliferation, migration, and invasion ability of OSCC cells, hinder cell cycle progression, and promote apoptosis via the RAP1-PI3K-AKT axis. FKBP10 is a potential therapeutic target and prognostic biomarker for OSCC.