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*

Hyperuricemia (HUA) and gout became typical metabolic disorders characterized by multiple pathogenic factors. Their incidence increased annually, affecting younger populations. Given that uric acid (UA) and inflammation were the primary disease mechanisms, the search for effective and low-side-effect UA-lowering and anti-inflammatory drugs became a pressing scientific priority. Traditional Chinese medicine (TCM) encompassed a rich array of theoretical and practical experience, along with a diverse range of chemical substances, making herbs or their components potential sources for therapeutic drugs. Despite the significant role that modern herbal medicines played in treating HUA and gout, the existing research literature remained fragmented, lacking comprehensive and systematic reviews. In this review, we focused on the regulation of UA and summarized the discovery of UA-lowering pharmacodynamic components or ingredients derived from herbs and formulas, as well as their multi-targeted mechanisms of action. Emphasizing this focus, we proposed that, compared to acute inflammation, low-grade inflammation may play a relatively "unnoticed" role in the disease process. In contrast to Western medicine, we discussed the risks and benefits of herbal medicines and their ingredients for treatment, drawing from theoretical insights and clinical practice. This review offered comprehensive perspectives on the research into anti-HUA and gout treatments using herbal medicines and their natural products. Additionally, it provided a forward-looking view on natural product discovery, the exploration of therapeutic strategies, and new drug research in this field.

ObjectiveTo validate the efficacy of Yunpi Huatan Tongqiao prescription （YHTP） in down-regulating glycolysis to modulate microglia phenotype and improve inflammation and cognitive memory deficits in obstructive sleep apnea （OSA） mice. MethodForty-eight male Balb/C mice were randomly divided into a normal group， a model group， a montelukast sodium group （30 mg·kg^-1）， and low， medium， and high dose groups of YHTP （8.28， 16.56， and 33.12 g·kg^-1）， with 8 mice in each group. All groups， except the normal group， received intraperitoneal injections of lipopolysaccharide （LPS） and underwent chronic intermittent hypoxia （CIH） modeling for 4 weeks. Subsequently， the mice were treated with medications for 4 weeks and then sampled. Animal behavioral tests assessed memory impairment due to hypoxia. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to measure mRNA expression levels of M1-associated inflammatory factors interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and markers such as T lymphocyte activation antigen （CD86） and inducible nitric oxide synthase （iNOS）， as well as M2-associated inflammatory factors interleukin-10 （IL-10）， transforming growth factor-β （TGF-β）， and the marker mannose receptor （CD206） in hippocampal tissue. Western blot was employed to detect differences in the expression of M1 and M2 microglia phenotypic markers （CD86， CD206） and glycolysis-related proteins glucose transporter type 1 （GLUT1）， hexokinase 2 （HK2）， phosphofructokinase （PFKM）， pyruvate kinase 2 （PKM2）， and monocarboxylic acid transporter 1 （MCT1）. ResultBehavioral tests showed that compared to the results in the normal group， the Y-maze autonomous alternation rate was significantly reduced in the model group （P<0.01）. The latency time for the target hole in the Barnes' maze during the training period （days 2， 3， 4） and testing period （days 5， 12） was significantly increased （P<0.05， P<0.01）. M1 glial cell markers CD86 and iNOS， as well as inflammatory factors IL-1β and TNF-α mRNA， were significantly elevated （P<0.01）. In contrast， the mRNA expression of M2 glial cell markers IL-10， CD206， and TGF-β was significantly reduced （P<0.01）. The protein expression of glycolytic proteins HK2， PFKM， PKM2， MCT1， and the M1 marker CD86 was significantly increased （P<0.05， P<0.01）， while M2 marker CD206 protein expression was significantly decreased （P<0.01）. Compared to the results in the model group， the Y-maze autonomous alternation rate was significantly increased in the medium and high dose groups of YHTP （P<0.05， P<0.01）. The latency time for the target hole during the training （day 4） and testing periods （days 5， 12） was significantly reduced （P<0.01）. Real-time PCR results indicated that mRNA expression levels of M1-related pro-inflammatory factors in the hippocampal tissue were significantly reduced in the low， medium， and high dose groups of YHTP （P<0.01）， while M2-related inflammatory factors' mRNA expression was significantly increased （P<0.01）. Western blot results showed that in the medium and high dose groups of YHTP， the expression of the M1 marker CD86 in the hippocampus was reduced， whereas the expression of the M2 marker CD206 was significantly increased （P<0.01）， with a significant decrease in the expression of glycolysis-related proteins （P<0.01）. ConclusionYHTP can improve inflammation and cognitive impairment induced by hypoxia in OSA model mice. This is achieved by downregulating glycolysis in brain microglia， inhibiting M1 activation， reducing pro-inflammatory factor release， and promoting M2 activation， thereby exerting a therapeutic effect on inflammation and cognitive impairment caused by OSA.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective This study aimed to explore the differences and influencing factors of static teeth exposure in different postures of orthognathic surgery patients.Methods A total of 148 patients were collected before or after or-thognathic surgery.Photographs were taken in the upright and supine positions,and the static teeth exposure values were measured to compare whether the difference among different positions was statistically significant.The patients were classified in accordance with gender,presence or absence of orthodontic brackets,measurement time(preoperative or postoperative),and maxillary movement direction(forward or backward),and the difference of static teeth exposure was compared.The correlation between the difference of static teeth exposure and age was analyzed.Results The diffe-rence of static teeth exposure between the two positions was 0.99 mm±0.95 mm,which was statistically significant(P=0.000).A statistical difference in the difference of static exposure was observed between female and male(P<0.05).No statistical difference in the difference of static expo-sure was observed among orthodontic brackets,preopera-tive or postoperative time points,and maxillary move-ment direction.In addition,no significant correlation was found between the difference of static teeth exposure and age(r=-0.087,P=0.291).Conclusion Compared with the upright position,the static exposure of teeth increased by ap-proximately 0.99 mm in the supine position.The difference of static exposure under different postures was greater in males than in females.Furthermore,orthodontic bracket,maxillary surgery,maxillary movement direction,and age had no effect on the difference of static teeth exposure in different postures.

Objective: To investigate the screening results of adolescent scoliosis in Chuzhou City, Anhui Province, and analyze the influencing factors for scoliosis, so as to provide insights into the prevention and control of scoliosis among adolescents. Methods: Students were selected from six primary and middle schools in Chuzhou City using the stratified random cluster sampling method from April to June 2023. Demographic information, daily behaviors and postures, and exercise status were collected through questionnaire surveys. Scoliosis was screened and diagnosed according to the Screening for Abnormal Spinal Curvature in Children and Adolescents. Influencing factors for scoliosis among primary and middle school students were identified using a multivariable logistic regression model. Results: A total of 1 823 questionnaires were allocated, and 1 768 effective questionnaires were recovered, with an effective response rate of 96.98%. There were 537 primary school students, 1 000 junior high school students and 231 senior high school students, with an average age of (13.40±1.92) years. There were 948 male students (53.62%) and 820 female students (46.38%). A total of 131 cases of scoliosis were screened positive, with a positive rate of 7.41%. The results of multivariable logistic regression analysis showed that gender (female, OR=1.759, 95%CI: 1.135-2.727), body mass index (OR=0.593, 95%CI: 0.538-0.654), sleeping position (side lying, OR=0.598, 95%CI: 0.377-0.951; prone lying, OR=2.336, 95%CI: 1.201-4.545), frequency of reading in bed (often, OR=2.099, 95%CI: 1.201-3.670), way of carrying backpack (shoulders, OR=0.580, 95%CI: 0.370-0.908), and exercise level (OR=0.428, 95%CI: 0.296-0.618) were influencing factors of scoliosis among primary and middle school students. Conclusion The positive rate of scoliosis screening among primary and middle school students in Chuzhou City was 7.41%, which was influenced by gender, age, body mass index, sleeping posture, reading in bed, way of carrying backpack and exercise level.