Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome

Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery. However, variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials. This heterogeneity in protocols may cause confusion among dental practitioners; therefore, guidelines and considerations for ITR should be explicated. This expert consensus discusses the biological foundation of ITR, the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration, and the main complications of this treatment, aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies; the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
Humans ; Tooth Replantation/methods* ; Consensus ; Periapical Periodontitis/surgery*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Objective:This study aims to initially establish a scoring system for comprehensively reflecting the severity of intracranial atherosclerotic lesions and to explore the correlation between this score and atherosclerotic risk factors as well as stroke events.Methods:This study retrospectively analyzed patients who underwent head and neck computer tomography angiography(CTA)examinations and had head MRI examinations within one month before or after the CTA examination from January 2021 to August 2024 in Beijing Hospital.An intracranial atherosclerosis disease score(ICADS)system was constructed based on the degree and number of vascular stenosis.The relationship between ICADS and atherosclerotic risk factors was explored by grouping patients according to the quartile of ICADS.Patients were divided into acute stroke group and non-acute stroke group to compare differences in ICADS and cerebrovascular disease risk factors between the two groups, and to investigate the correlation between stroke events and ICADS.Results:There were statistically significant differences in the proportions of patients with hypertension and diabetes among different ICADS groups.Multiple linear regression analysis showed that hypertension( B=1.17, 95% CI: 0.20-2.14, P<0.05)and diabetes( B=2.75, 95% CI: 1.85-3.64, P<0.001)were risk factors for higher ICADS.The ICADS was higher in the acute stroke group than in the non-acute stroke group(9 vs.6, P<0.001), and a higher ICADS was identified as a risk factor for stroke( OR=1.10, 95% CI: 1.07-1.14, P<0.001). Conclusions:ICADS can comprehensively reflect the severity of intracranial atherosclerotic lesions and is correlated with stroke events, making it useful for clinical screening of high-risk patients for stroke.

ObjectiveTo establish a rapid analytical method for identifying the differential components in Poria cocos medicinal materials based on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， combined with mass defect filtering（MDF） and molecular network integration techniques. MethodsUPLC-Q-Orbitrap-MS was used for MS data acquisition and identification of P. cocos medicinal materials， with the help of MDF for the study of cleavage behavior and structural identification of triterpenoids. According to the similarity of MS/MS fragmentation patterns of each component， global natural product social molecular network（GNPS） was established， and Cytoscape 3.6.1 was used to screen molecular clusters with similar structures and the the structure of main compound classes were identified and confirmed. Multivariate statistical analyses such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to screen the differential components of the five P. cocos medicinal materials with the variable importance in the projection（VIP） value>1 and P<0.05 as the criteria. ResultsA total of 66 compounds were identified by database comparison， 8 compounds were newly identified by MDF， 28 compounds were newly identified by GNPS， and a total of 102 chemical compounds were identified， including 43 triterpenoids， 16 saccharides， 26 amino acids and peptides， 3 nucleosides， and 14 other compounds. Triterpenoids were predominant in Poriae Cutis and wild Fushen， amino acids and peptides were the most abundant in Poria and cultivated Fushen， carbohydrates were the most abundant in Poriae Cutis. Type Ⅰ and Ⅱ triterpenoids had higher amounts in Poria and cultivated Fushen， type Ⅲ triterpenoids were more abundant in Poriae Cutis， all four types of triterpenoids were higher in Fushenmu， and type Ⅰ， Ⅱ， and Ⅳ triterpenoids were higher in wild Fushen. A total of 12 common differential chemical constituents were screened， including serine， guanosine， gallic acid， 2-octenal， maltotriose， trametenolic acid， dehydroeburicoic acid， dehydrotrametenolic acid， poricoic acid A， poricoic acid B， poricoic acid E and G， but the relative contents of them varied significantly among different medicinal materials. ConclusionAmong the five P. cocos medicinal materials， the types of constituents are generally similar， but their relative contents differed significantly among these medicinal materials， especially in the distribution of triterpenoids. The integration of UPLC-Q-Orbitrap-MS， MDF and GNPS can provide a reference for the rapid qualitative analysis of other Chinese medicines.

ObjectiveTo establish a rapid analytical method for identifying the differential components in Poria cocos medicinal materials based on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， combined with mass defect filtering（MDF） and molecular network integration techniques. MethodsUPLC-Q-Orbitrap-MS was used for MS data acquisition and identification of P. cocos medicinal materials， with the help of MDF for the study of cleavage behavior and structural identification of triterpenoids. According to the similarity of MS/MS fragmentation patterns of each component， global natural product social molecular network（GNPS） was established， and Cytoscape 3.6.1 was used to screen molecular clusters with similar structures and the the structure of main compound classes were identified and confirmed. Multivariate statistical analyses such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to screen the differential components of the five P. cocos medicinal materials with the variable importance in the projection（VIP） value>1 and P<0.05 as the criteria. ResultsA total of 66 compounds were identified by database comparison， 8 compounds were newly identified by MDF， 28 compounds were newly identified by GNPS， and a total of 102 chemical compounds were identified， including 43 triterpenoids， 16 saccharides， 26 amino acids and peptides， 3 nucleosides， and 14 other compounds. Triterpenoids were predominant in Poriae Cutis and wild Fushen， amino acids and peptides were the most abundant in Poria and cultivated Fushen， carbohydrates were the most abundant in Poriae Cutis. Type Ⅰ and Ⅱ triterpenoids had higher amounts in Poria and cultivated Fushen， type Ⅲ triterpenoids were more abundant in Poriae Cutis， all four types of triterpenoids were higher in Fushenmu， and type Ⅰ， Ⅱ， and Ⅳ triterpenoids were higher in wild Fushen. A total of 12 common differential chemical constituents were screened， including serine， guanosine， gallic acid， 2-octenal， maltotriose， trametenolic acid， dehydroeburicoic acid， dehydrotrametenolic acid， poricoic acid A， poricoic acid B， poricoic acid E and G， but the relative contents of them varied significantly among different medicinal materials. ConclusionAmong the five P. cocos medicinal materials， the types of constituents are generally similar， but their relative contents differed significantly among these medicinal materials， especially in the distribution of triterpenoids. The integration of UPLC-Q-Orbitrap-MS， MDF and GNPS can provide a reference for the rapid qualitative analysis of other Chinese medicines.

Reconstruction of low-dose CT image faced problems such as low resolution,blurred artifacts and strong noise.Deep learning reconstruction met the needs of reducing radiation dose and improving imaging quality,promoted reconstruction of CT image towards high efficiency,intelligence and integration of clinical diagnosis and treatment.The research progresses in deep learning low-dose CT imaging reconstruction were reviewed in this article.

Brain age prediction is of great significance to the in-depth understanding of individual neurodevelopment,early diagnosis of neuropsychiatric disorders,and formulation of personalized treatment plans. With the continuous advancement of deep learning,more and more researches focus on using such algorithms to predict brain age. Compared with traditional regression algorithms,deep learning which has the advantages of complex pattern learning,end-to-end learning and high adaptability can more accurately reveal the neuropathological mechanisms of neuropsychiatric disorders,and provide more precise tools for clinical assessment,assisted diagnosis and prognosis prediction. Herein the study reviews the recent advances in the application of deep learning algorithms in brain age prediction,introduces the achievements in deep learning model optimization,multimodal data inputs and interpretability studies for brain age prediction,discusses the methods for the establishment of integrated deep learning architectures and the future challenges of developing unified benchmarking,and provides an outlook on the application of deep learning in brain age prediction.

Objective:To investigate expression and clinical significance of T cell activation related membrane molecules in infertility patients with polycystic ovary syndrome(PCOS).Methods:A total of 80 PCOS infertility patients who visited Second Affiliated Hospital of Hainan Medical College from January 2020 to June 2021 were selected as observation group,and 80 cases of women who underwent physical examination at same time were selected as control group.Expressions of membrane molecules related to T cell acti-vation in peripheral blood of patients between two groups were compared.Patients with PCOS infertility were divided into pregnant group[66(82.5％)]and non pregnant group[14(17.5％)]according to different prognosis.General clinical data,peripheral blood inflammatory factors and T cell activation related membrane molecules expressions were compared between two groups,focusing on correlation between T cell activation related membrane molecules expressions and prognosis of PCOS infertility patients,ROC curve and decision-making curve of T cell activation related membrane molecule expressions were drawn to predict prognosis of PCOS infer-tility patients,whose prediction efficiency and net profitability were further analyzed.Pearson correlation analysis was used to explore correlation between T cell activation related membrane molecules expressions and clinical characteristics of PCOS infertility patients.Results:CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients in observation group were significantly higher than control group(P<0.05).Total testosterone(T),TNF-α,IFN-γ,CD4+CD45+T and CD4+CD63+T cells expressions of patients in non pregnancy group were significantly higher than pregnancy group(P<0.05).Multivariate Logistic regression analysis showed that CD4+CD45+T and CD4+CD63+T cells were independent predictors of prognosis of PCOS infertility patients(P<0.05),ROC analysis showed that AUC of CD4+CD45+T cells predicting prognosis of PCOS infertility patients was 0.756(0.721～0.826),and the best diag-nostic cut-off point was 48.1％,AUC of CD4+CD63+T cells was 0.746(0.711～0.834),and the best cut-off point for diagnosis was 31.2％,while AUC of CD4+CD45+T and CD4+CD63+T cells combination was 0.948(0.897～0.986).Decision curve analysis showed that combined prediction of CD4+CD45+T and CD4+CD63+T cells was higher than a single indicator.Correlation analysis showed that CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients with PCOS infertility was related to T,TNF-α,insulin resistance index(HOMA-IR),IFN-γ,IL-2 and IL-10(P<0.05).Conclusion:The higher the CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood,the worse the prognosis of patients with PCOS infertility.