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*

To explore the effect of resistance exercise on glycolipid metabolism in over-weight or obese people, with the aim of providing reference for the clinical development of appropriate resistance exercise programs.

Objective To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases. Methods A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.

Objectives:To examine the feasibility of using foundation model in computer vision for echocardiographic left ventricular ejection fraction measurement. Methods:Based on the most extensive publicly accessible repository of echocardiographic loops,EchoNet-Dynamic,featuring 10024 recordings from individual patients,a foundation model in computer vision,VideoMAE V2,was fine-tuned,validated,tested using 7460,1288,and 1276 echocardiographic loops,respectively. Results:The mean absolute error between left ventricular ejection fraction measurements of VideoMAE V2 and expert's measurements was 3.94％ (95％CI:3.79％-4.11％).The Pearson's correlation coefficient was 0.91 (95％CI:0.89-0.92).Additionally,VideoMAE V2 demonstrated exceptional accuracy in identifying patients with a left ventricular ejection fraction below 50％,achieving an AUC of 0.96 (95％CI:0.95-0.97). Conclusions:This study validates the feasibility of using foundation model in computer vision for measuring left ventricular ejection fraction in echocardiographic loops and lays the foundation for the development of a generalized multimodal automated interpretation system for echocardiography.

Objective:To explore the impact of early postoperative hypocaloric parenteral nutrition on perioperative infectious complications in patients undergoing hepatectomy for primary hepatic carcinoma.Methods:The data of 205 patients who underwent hepatectomy for primary hepatic carcinoma in the Division of Hepatobiliary and Transplantation Surgery at Nanjing Drum Tower Hospital between February 2020 and December 2022 were collected by a single center prospective cohort study. The patients were divided into a hypocaloric group ( n=108) and a normal calorie group ( n=97) based on whether they received hypocaloric parenteral nutrition within 72 hours postoperatively. The influence of early parenteral nutrition caloric on perioperative infectious complications was analyzed. Measurement data with normal distribution were expressed as mean±standard deviation ( ± s) and compared using t-test. Measurement data with skewed distribution were expressed as M( Q1, Q3) and compared using the Wilcoxon rank-sum test. Comparison of categorical data was performed using the chi-square test or Fisher′s exact test. To adjust for confounding factors, patients were grouped for comparison based on whether they experienced infectious complications within the 30-day postoperative follow-up period. Factors that may influence postoperative infectious complications were first analyzed using univariate analysis, and variables with statistical significance were then included in multivariate analysis. Results:A total of 82 patients experiencing infectious complications, resulting in an incidence rate of 40.0%. Patients in the hypocaloric parenteral nutrition group had significantly lower rates of hyperglycemic events (17.6% vs 29.9%, P=0.038) and gastrointestinal reactions (12.0% vs 22.7%, P=0.043) compared to the normal calorie parenteral nutrition group, with no intergroup differences in other nutrition-related complications. Univariate analysis results revealed that hypocaloric parenteral nutrition, hepatocellular carcinoma, malnutrition assessed by the GLIM criteria, open surgery, major hepatectomy, perioperative hyperglycemic events, and the presence of pleural or ascitic fluid were potential influencing factors for the occurrence of infectious complications ( P<0.05). Multivariate analysis results suggested that malnutrition ( OR=2.707, 95% CI: 1.153-6.354, P=0.022), open surgery ( OR=2.103, 95% CI: 1.073-4.122, P=0.030), perioperative hyperglycemic events ( OR=2.630, 95% CI: 1.228-5.631, P=0.013), and the presence of pleural or ascitic fluid ( OR=2.714, 95% CI: 1.388-5.306, P=0.004) were risk factors for perioperative infectious complications in patients undergoing hepatectomy for primary hepatic carcinoma, while early postoperative hypocaloric parenteral nutrition ( OR=0.388, 95% CI: 0.199-0.757, P=0.006) was a protective factor. Conclusion:For patients undergoing hepatectomy for primary hepatic carcinoma, early postoperative hypocaloric parenteral nutrition may reduce the incidence of perioperative infectious complications compared to normal caloric parenteral nutrition, thereby improving patient clinical outcomes.

To analyze the current quality of treatment for hospitalized cancer patients in Beijing, identify major issues in treatment practices, and propose improvements.

Objective To investigate the value of ESRS score combined with inflammatory factors in predicting cerebral small vessel disease （CSVD） in patients with vertigo in Qinghai area， China. Methods A total of 394 patients who were admitted and diagnosed with vertigo in Department of Neurology， Qinghai Provincial People’s Hospital， from June 2022 to June 2023 were enrolled as subjects， among whom there were 201 patients with central vertigo and 193 patients with peripheral vertigo. Inflammation-related indicators were collected， including neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， monocyte to high-density lipoprotein cholesterol ratio， and lymphocyte-to-monocyte ratio， and ESRS score and MRI examination were performed for all patients. Results Among the 201 patients with central vertigo， 118 （58.7%） developed CSVD， and among the 193 patients with peripheral vertigo， 78 （40.4%） developed CSVD. The univariate analysis showed that there were significant differences in systolic blood pressure， NLR， PLR， MHR， LMR， and ESRS score between the patients with CSVD and those without CSVD in the central vertigo group and the peripheral vertigo group， and there were significant differences in age and ESRS score between the central vertigo CSVD group and the peripheral vertigo CSVD group. For the patients with central vertigo， the risk of CSVD in the low-， medium-， and high-risk ESRS score groups was 25.49%， 68.75%， and 100.00%， respectively， and for those with peripheral vertigo， the risk of CSVD in the low-， medium-， and high-risk ESRS score groups was 32.10%， 66.70%， and 100.00%， respectively. The logistic regression analysis showed that ESRS score， NLR， and PLR were independent risk factors for CSVD in patients with vertigo. In the central vertigo group， ESRS score， NLR， and PLR alone had an area under the ROC curve （AUC） of 0.790， 0.721， and 0.635， respectively， in predicting CSVD， and the combination of the three indices had an AUC of 0.846； in the peripheral vertigo group， ESRS score， NLR， and PLR alone had an AUC of 0.757， 0.714， and 0.632， respectively， in predicting CSVD， and the combination of the three indices had an AUC of 0.816. Conclusion The risk of CSVD in patients with vertigo in Qinghai area increases with the increase in ESRS score， and the risk of CSVD in patients with vertigo in Qinghai area is positively correlated with NLR and PLR. ESRS score combined with NLR and PLR is more sensitive than the above indices used alone in the risk assessment of CSVD in patients with vertigo in Qinghai area. The central vertigo CSVD group has a higher ESRS score than the peripheral vertigo CSVD group， suggesting that patients with central vertigo tend to develop CSVD.
Vertigo

Objective:To analyze clinical features of coronavirus disease 2019 in patients with autoimmune blistering diseases (AIBDs), and to explore risk factors for the development of severe coronavirus disease 2019 in patients with AIBDs.Methods:Clinical data were collected from patients with AIBDs who were hospitalized in Zhongda Hospital, Southeast University from August 2021 to December 2022, and were retrospectively analyzed. Independent sample t-test, Mann-Whitney U test, or chi-square test (Fisher′s exact test) were used to analyze factors associated with severe coronavirus disease 2019 in AIBD patients. Results:A total of 30 patients with AIBDs accompanied by coronavirus disease 2019 were included, they were aged 62.90 ± 15.72 years, and included 16 males and 14 females; pemphigus vulgaris (12 cases, 40.00%) and bullous pemphigoid (13 cases, 43.33%) predominated in the disease spectrum of AIBDs in these patients. The common clinical manifestations of coronavirus disease 2019 were cough (25 cases, 83.33%), fatigue (22 cases, 73.33%), and fever (15 cases, 50.00%) ; most patients had mild clinical symptoms, while 7 (23.33%) developed into severe coronavirus disease 2019, including 2 out of 14 aged 30 - 59 years and 5 out of 16 elderly patients aged ≥ 60 years, and 2 out of the 5 elderly patients finally died. According to the clinical classification criteria of coronavirus disease 2019, the 30 patients were divided into the mild-to-moderate group (23 cases) and severe group (7 cases) ; the duration of AIBDs was significantly shorter in the severe group (10.71 ± 10.72 months) than in the mild-to-moderate group (27.61 ± 19.67 months, t = 2.16, P = 0.040) ; the remission rate of AIBDs was significantly higher in the mild-to-moderate group (21/23) than in the severe group (4/7, χ2 = 4.36, P = 0.037) ; the average daily dosage of methylprednisolone during the last month was significantly lower in the mild-to-moderate group ( M[ Q1, Q3]: 8 [4, 14] mg) than in the severe group (24 [12, 47] mg, U = 133.50, P = 0.007), and the proportion of patients treated with methylprednisolone at an average dosage of > 8 mg was significantly higher in the severe group (6/7) than in the mild-to-moderate group (8/23, χ2 = 5.59, P = 0.031) . Conclusions:Among the patients with AIBDs accompanied by coronavirus disease 2019, the incidence and mortality of severe coronavirus disease 2019 were higher in elderly patients than in young patients. The short course and no-remission of AIBDs, and the average daily dosage of methylprednisolone being>8 mg/d during the last month were risk factors for the development of severe coronavirus disease 2019 in the patients with AIBDs.

Objective A knowledge graph construction pipeline of traditional Chinese medicine(TCM)diagnosis and treatment was designed and applied,aiming at the automatic construction of the"disease-symptom-pathogenesis-and medicine"knowledge graph based on the medical records of famous TCM physicians,to analyze,organize and present medical records efficiently.Methods Firstly,The entity extraction method of medical records combining Deep Learning and Regular Expression was designed to extract disease,symptom,pathogenesis,and TCM entities from unstructured medical records automatically;secondly,entity relationships were defined and the correlations between entities were calculated using HAN method,and then the"entity-relation-entity"triplets were built;the graph database Neo4j and Gephi were used for knowledge storage and visual display separately;Finally,the application was verified in the Medical records of lung cancer treated by the old famous TCM physicians.Results The precision,Recall and F1 of the knowledge extraction model for medical records entities extraction are 88.49%,90.02%and 89.25%,respectively,and each index is better than the comparison methods.A total of 1077 triples are extracted through entity correlation calculation,and the knowledge graph is successfully constructed.It can reflect the relationship between 'disease-symptom-pathogenesis-medicine' in the treatment of lung cancer by the famous specialists of TCM.Conclusion The method in this paper can effectively solve the extraction,organization and expression of clinical medical records of famous TCM physicians,and realize the automatic construction process from the text of medical records to the knowledge graph.Relevant research ideas and methods proposed in this paper could provide a reference for the construction of the diagnosis and treatment knowledge graph of famous TCM physicians based on medical records.

Enterotoxigenic Escherichia coli（ETEC）infection can induce watery diarrhea，leading to dehydration，electrolyte disturbance，and even death in severe cases. Recombinant B subunit/inactivated whole-cell cholera（rBS/WC）vaccine is effective in preventing ETEC infectious diarrhea. On the basis of the latest evidence on etiology and epidemiology of ETEC，as well as the effectiveness，safety，and health economics of rBS/WC vaccine，National Clinical Research Center for Child Health（The Children’s Hospital，Zhejiang University School of Medicine）and Zhejiang Provincial Center for Disease Control and Prevention invited experts to develop expert consensus on rBS/WC vaccine in prevention of ETEC infectious diarrhea. It aims to provide the clinicians and vaccination professionals with guidelines on using rBS/WC vaccine to reduce the incidence of ETEC infectious diarrhea.