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*

Objective This study aims to evaluate the safety and efficacy of internal carotid artery(ICA)embolization for the resection of head and neck tumors invading the ICA.Methods A retrospective analysis was conducted on eight patients with ICA-invading head and neck tumors treated between August 2022 and June 2024 in Beijing Tongren Hospital,Capital Medical University.All patients underwent a preoperative balloon occlusion test(BOT),which yielded negative results before undergoing ICA embolization.Parameters from BOT,technical success rates of embolization procedures,perioperative complications,and follow-up outcomes were recorded.Results During BOT assessments,the mean reflux pressure was found to be 75.4％±10.3％of the pre-occlusion pressure.Patency of both anterior and posterior communicating arteries was observed in three cases;four cases exhibited patency solely in the anterior communicating artery,while one case showed patency only in the posterior communicating artery.The technical success rate of embolization was 100％.One patient experienced acute cerebral infarction following embolization treatment,while two patients had migraine attacks post-procedure.All patients achieved complete tumor resection without new-onset neurological deficits.Conclusion For patients with head and neck tumors invading the ICA who are negative on BOT,preoperative ICA embolization is a safe and feasible approach that enhances surgical safety during tumor resection.

Objective To summarize the clinical experience of using 3D planar guide plate combined with bundle diameter technology for extracorporeal pre-fenestration in treating complex thoracoabdominal aortic diseases.Methods The clinical data of 31 patients with complex thoracoabdominal aortic diseases,who were treated with 3D planar guide plate combined with bundle diameter technology of extracorporeal pre-fenestration at the First Affiliated Hospital of Soochow University of China from January 2017 to February 2024,were retrospectively analyzed.The patients' preoperative thin-layer chest and abdominal vascular CTA data were imported into specialized software and to create a 3D planar guide plate.Under the guidance of 3D planar guide plate technology,precise extracorporeal pre-fenestration of aortic covered stent was performed,and combined with bundle diameter technology the endovascular repair of complex thoracoabdominal aortic disease was accomplished.Results Successful operation was accomplished in all patients,and two patients had failed visceral artery reconstruction surgery.The median follow-up time was 55 months,with a technical success rate of 97.6％.The postoperative follow-up blood flow patency rate was 100％,and the phase Ⅰ patency rate of branch arteries was 98％.Three patients experienced internal leakage after surgery,and none of them developed paraplegia or died during the perioperative period.Conclusion In treating complex thoracoabdominal aortic diseases,the use of 3D planar guide plate combined with bundle diameter technology of extracorporeal pre-fenestration is simple,safe and effective,with good short-term therapeutic effect,although its long-term efficacy need to be further investigated.

Objective:To systematically evaluate the bias risk and applicability of short-term mortality risk prediction models within 30 days after stroke, providing a basis for selecting or developing standardized risk prediction models.Methods:Research on short-term mortality risk prediction models within 30 days after stroke was electronically retrieved from China National Knowledge Infrastructure, WanFang Data, VIP, and China Biomedical Database, PubMed, Web of Science, Embase, Cochrane Library and CINAHL. The search period was from database establishment to December 5, 2023. Two researchers independently conducted literature screening and quality evaluation.Results:Twelve studies were included, and a total of 31 models were internally validated, with 7 models undergoing external validation based on internal validation. 26 models reported discriminative power, and 18 models reported calibration methods. The most frequent predictors of modeling were age, hypertension, atrial fibrillation, diabetes and admission Glasgow Coma Scale score. Due to methodological problems such as insufficient sample size, improper handling of missing variables, and inadequate reporting of modeling information, all included studies were rated as high risk of bias.Conclusions:The research on short-term mortality risk prediction models for stroke patients is still in the development stage. Although it has good applicability, the risk of bias is relatively high. Future research should be designed and reported based on prediction model risk of bias assessment tool (PROBAST) and transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) to avoid common problems summarized in this study and reduce the risk of bias.

Objective Previous studies on the association between lipid profiles and chronic kidney disease(CKD)have yielded inconsistent results and no defined thresholds for blood lipids. Methods A prospective cohort study including 32,351 subjects who completed baseline and follow-up surveys over 5 years was conducted.Restricted cubic splines and Cox models were used to examine the association between the lipid profiles and CKD.A regression discontinuity design was used to determine the cutoff value of lipid profiles that was significantly associated with increased the risk of CKD. Results Over a median follow-up time of 2.2(0.5,4.2)years,648(2.00%)subjects developed CKD.The lipid profiles that were significantly and linearly related to CKD included total cholesterol(TC),triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),TC/HDL-C,and TG/HDL-C,whereas low-density lipoprotein cholesterol(LDL-C)and LDL-C/HDL-C were nonlinearly correlated with CKD.TC,TG,TC/HDL-C,and TG/HDL-C showed an upward jump at the cutoff value,increasing the risk of CKD by 0.90%,1.50%,2.30%,and 1.60%,respectively,whereas HDL-C showed a downward jump at the cutoff value,reducing this risk by 1.0%.Female and participants with dyslipidemia had a higher risk of CKD,while the cutoff values for the different characteristics of the population were different. Conclusion There was a significant association between lipid profiles and CKD in a prospective cohort from Northwest China,while TG,TC/HDL-C,and TG/HDL-C showed a stronger risk association.The specific cutoff values of lipid profiles may provide a clinical reference for screening or diagnosing CKD risk.

This study reports a case of pachydermoperiostosis combined with posterior cruciate ligament femoral insertion avulsion fracture. The avulsion fracture was treated by arthroscopic surgery of suspension fixation. The symptom of the pachydermoperiostosis was relieved by non-steroidal anti-inflammatory drugs. Literature search and review were carried out by searching the key words of ("pachydermoperiostosis" OR "primary hypertrophic osteoarthropathy" OR "Touraine-solente-gole syndrome") OR ("posterior cruciate ligament" AND "avulsion fracture"). This patient was confirmed to be the first case reported suffering both diseases mentioned above. For the search results, there were 14 articles on posterior cruciate ligament femoral insertion avulsion fracture and 7 articles on pachydermoperiostosis. This study focused on the impact of pachydermoperiostosis on bone quality, possible factors for the avulsion fracture, and the advantages of arthroscopic surgery. Pachydermoperiostosis is a rare autosomal recessive disease. The incidence of posterior cruciate ligament femoral insertion avulsion fracture is extremely low. It is a seriously sports injury affecting the stability of the knee joint. Standardized surgical treatment can help patients obtain a satisfactory clinical outcome.

Tumor metastasis is closely related to high mortality rate of cancer.It is well known that glutamine plays an important role in the malignant progression of cancer.Notably,as an important carbon and nitrogen donor,glutamine has been found to be closely related to tumor metastasis in recent years.Glutamine is not only involved in regulating the proliferation of tumor cells,but is also closely related to the migration and invasion of tumor cells.Furthermore,various enzymes along with transporters in the metabolism of glutamine are involved in the process of tumor metastasis through different signaling pathways.This review provided a summary of the role of glutamine in tumor metastasis in recent years and proposed therapeutic targets to provide new strategies for the clinical treatment of tumor metastases.

Objective:To summarize the best evidence for the prevention and nursing of immune checkpoint inhibitor (ICI) associated skin toxicity in lung cancer patients, providing reference for clinical and nursing staff.Methods:Evidence-based nursing issues were constructed using the population, intervention, professional, outcome, setting and type of evidence (PIPOST) model of the Joanna Briggs Institute Evidence Based Health Care Center. The "6S" pyramid model was used to search for guidelines, expert consensus, systematic reviews, best practices, evidence summary, and original research on the prevention and nursing of ICI associated skin toxicity in lung cancer patients from top to bottom in domestic and foreign databases, professional association websites, and guideline websites. Articles that met the inclusion criteria was screened, evaluated for quality, and evidence was extracted. The search period was from the establishment of the database to October 1, 2022.Results:A total of 14 articles were included, involving 6 expert consensuses, 5 guidelines, and 3 systematic reviews. A total of 24 best evidences were summarized from 7 aspects, including high-risk factors, baseline screening, immune checkpoint inhibitors (ICIs) treatment monitoring, daily skin nursing, multidisciplinary management, symptom management, and health education.Conclusions:Medical and nursing staff should combine clinical situations, consider the needs and preferences of patients, and use the best evidence to develop scientific and personalized nursing plans to reduce the occurrence of ICI associated skin toxicity.

Objective:To explore the feasibility of using faster regional convolutional neural network (Faster R-CNN) to evaluate the status of circumferential resection margin (CRM) of rectal cancer in the magnetic resonance imaging (MRI).Methods:This study was registered in the Chinese Clinical Trial Registry (ChiCTR-1800017410). Case inclusion criteria: (1) the positive area of CRM was located between the plane of the levator ani, anal canal and peritoneal reflection; (2) rectal malignancy was confirmed by electronic colonoscopy and histopathological examination; (3) positive CRM was confirmed by postoperative pathology or preoperative high-resolution MRI. Exclusion criteria: patients after neoadjuvant therapy, recurrent cancer after surgery, poor quality images, giant tumor with extensive necrosis and tissue degeneration, and rectal tissue construction changes in previous pelvic surgery. According to the above criteria, MRI plain scan images of 350 patients with rectal cancer and positive CRM in The Affiliated Hospital of Qingdao University from July 2016 to June 2019 were collected. The patients were classified by gender and tumor position, and randomly assigned to the training group (300 cases) and the validation group (50 cases) at a ratio of 6:1 by computer random number method. The CRM positive region was identified on the T2WI image using the LabelImg software. The identified training group images were used to iteratively train and optimize parameters of the Faster R-CNN model until the network converged to obtain the best deep learning model. The test set data were used to evaluate the recognition performance of the artificial intelligence platform. The selected indicators included accuracy, sensitivity, positive predictive value, receiver operating characteristic (ROC) curves, areas under the ROC curves (AUC), and the time taken to identify a single image.Results:The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the CRM status determined by the trained Faster R-CNN artificial intelligence approach were 0.884, 0.857, 0.898, 0.807, and 0.926, respectively; the AUC was 0.934 (95% CI: 91.3% to 95.4%). The Faster R-CNN model's automatic recognition time for a single image was 0.2 s.Conclusion:The artificial intelligence model based on Faster R-CNN for the identification and segmentation of CRM-positive MRI images of rectal cancer is established, which can complete the risk assessment of CRM-positive areas caused by in-situ tumor invasion and has the application value of preliminary screening.

Objective:To explore the feasibility of using faster regional convolutional neural network (Faster R-CNN) to evaluate the status of circumferential resection margin (CRM) of rectal cancer in the magnetic resonance imaging (MRI).Methods:This study was registered in the Chinese Clinical Trial Registry (ChiCTR-1800017410). Case inclusion criteria: (1) the positive area of CRM was located between the plane of the levator ani, anal canal and peritoneal reflection; (2) rectal malignancy was confirmed by electronic colonoscopy and histopathological examination; (3) positive CRM was confirmed by postoperative pathology or preoperative high-resolution MRI. Exclusion criteria: patients after neoadjuvant therapy, recurrent cancer after surgery, poor quality images, giant tumor with extensive necrosis and tissue degeneration, and rectal tissue construction changes in previous pelvic surgery. According to the above criteria, MRI plain scan images of 350 patients with rectal cancer and positive CRM in The Affiliated Hospital of Qingdao University from July 2016 to June 2019 were collected. The patients were classified by gender and tumor position, and randomly assigned to the training group (300 cases) and the validation group (50 cases) at a ratio of 6:1 by computer random number method. The CRM positive region was identified on the T2WI image using the LabelImg software. The identified training group images were used to iteratively train and optimize parameters of the Faster R-CNN model until the network converged to obtain the best deep learning model. The test set data were used to evaluate the recognition performance of the artificial intelligence platform. The selected indicators included accuracy, sensitivity, positive predictive value, receiver operating characteristic (ROC) curves, areas under the ROC curves (AUC), and the time taken to identify a single image.Results:The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the CRM status determined by the trained Faster R-CNN artificial intelligence approach were 0.884, 0.857, 0.898, 0.807, and 0.926, respectively; the AUC was 0.934 (95% CI: 91.3% to 95.4%). The Faster R-CNN model's automatic recognition time for a single image was 0.2 s.Conclusion:The artificial intelligence model based on Faster R-CNN for the identification and segmentation of CRM-positive MRI images of rectal cancer is established, which can complete the risk assessment of CRM-positive areas caused by in-situ tumor invasion and has the application value of preliminary screening.