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

The dental operative microscope has been widely employed in the field of dentistry, particularly in endodontics and operative dentistry, resulting in significant advancements in the effectiveness of root canal therapy, endodontic surgery, and dental restoration. However, the improper use of this microscope continues to be common in clinical settings, primarily due to operators' insufficient understanding and proficiency in both the features and established operating procedures of this equipment. In October 2019, Professor Jingping Liang, Vice Chairman of the Society of Cariology and Endodontology, Chinese Stomatological Association, organized a consensus meeting with Chinese experts in endodontics and operative dentistry. The objective of this meeting was to establish a standard operation procedure for the dental operative microscope. Subsequently, a consensus was reached and officially issued. Over the span of about four years, the content of this consensus has been further developed and improved through practical experience.
Humans ; Dentistry, Operative ; Consensus ; Endodontics ; Root Canal Therapy ; Dental Care

The latest epidemiological data suggests that the situation of adult diabetes in China is severe, and metabolic diseases have become significant chronic illnesses that have a serious impact on public health and social development. After more than six years of practice, the National Metabolic Management Center(MMC) has developed distinctive approaches to manage metabolic patients and has achieved a series of positive outcomes, continuously advancing the standardized diagnosis and treatment model. In order to further improve the efficiency, based on the first edition, the second edition guideline was composed by incorporating experience of the past six years in conjunction with the latest international and domestic guidelines.

Background Global warming may increase the frequency of compound hot extreme (CHE).However, there is still a lack of studies assessing the associations between CHE and preterm birth (PTB), and the underlying biological mechanisms remain unclear. Objective To estimate the association of exposure to CHE during pregnancy with PTB, and to explore the roles of inflammatory, endothelial dysfunction, and oxidative stress in the association between CHE and PTB. Methods All participants were selected from the Prenatal Environments and Offspring Health (PEOH), a prospective birth cohort conducted in Guangzhou. In this study, a total of 2449 participants who gave birth from May to October in 2014 to 2017 were enrolled, and among them blood samples were collected from 311 preterm (n=43) and full-term (n=268) pregnant women at the time of delivery. A hot day/night was identified as a day when the daily maximum temperature/minimum temperature was higher than its 90th percentile in the study period, and a CHE was defined as having both a hot night and a following hot day. The meteorological data were obtained from the China Meteorological Data Sharing Service System. Anusplin was used to assess the daily maximum temperature, daily minimum temperature, and relative humidity of the participant residence. Enzyme-linked immunosorbent assay (ELISA) was used to measure C reactive protein (CRP), endothelin-1 (ET-1), and malondialdehyde (MDA) levels in maternal serum, and their results were transformed by natural logarithm. A distributed lag nonlinear model was used to investigate the associations of exposures to hot day, hot night, and CHE during pregnancy with PTB at different lag days, and a logistic regression model was used to investigate the associations of CRP, ET-1, and MDA with PTB. Results The incidence rate of PTB was 6.2% in all selected participants. Compared with the non-hot day, the RRs (95%CIs) of CHE in lag 3, 7, and 14 days on PTB were 1.43 (1.12-1.84), 1.24 (1.08-1.43), and 1.17 (1.05-1.30), respectively, and the cumulative effects (% difference) (95%CI) of CHE in lag 14 days on maternal serum CRP, ET-1, and MDA were 0.33% (−0.45%-1.12%), 0.59% (0.11%-1.07%), and 0.57% (0.09%-1.05%), respectively. Compared with the Q1 (lowest quartile) for CRP, ET-1 and MDA, the RRs (95%CIs) of Q4 (highest quartile) for PTB were 1.27 (0.50-3.22), 1.51 (0.61-3.72), and 2.07(0.81-5.27), respectively. Conclusion Maternal exposure to CHE during pregnancy might be associated with an increased risk of PTB. Prenatal exposure to CHE is positively associated with maternal serum CRP, ET-1, and MDA, and the three biochemical indicators are also positively associated with PTB. However, the above conclusions still need further confirmation.

Objective:To explore the risk factors for early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH), and construct a clinical-radiomics combined model to predict HE after sICH.Methods:From April 2014 to September 2020, 339 patients with sICH who underwent plain CT scans in Radiology Department of our hospital were recruited. Patients were divided into HE group and non-HE group according to whether HE occurred (HE was defined as an increase in hematoma volume>33% or 6 mL on the follow-up CT within 24 h). The clinical data of non-HE group and HE group were compared, and multivariate Logistic regression analysis was used to detect independent risk factors for HE. The radiomics features were extracted from the regions of interest of the hematoma in the first CT scan images; the optimal radiomics features were selected using least absolute shrinkage and selection operator (LASSO) regression model and 10-fold cross-validation method, and then, the radiomics scores (R-score) were calculated; the risk factors for HE (clinical data) and R-score (radiomics data) were used to construct the clinical model, R-score model, and clinical-radiomics combined model; receiver operating characteristic (ROC) curve was performed to evaluate the prediction performance of clinical model, R-score model, and clinical-radiomics combined model; the best model was visualized as a nomogram and a calibration curve was drawn to evaluate the prediction accuracy of this model.Results:As compared with patients in the non-HE group, patients in the HE group had shorter time from sICH onset to first CT, higher percentage of patients with diabetes, lower platelet count, lower Glasgow Coma Scale (GCS) scores, and larger baseline hematoma volume in CT image, with significant differences ( P<0.05). Multivariate Logistic regression analysis showed that baseline hematoma volume ( OR=1.015, 95%CI: 1.000-1.030, P=0.046), GCS scores ( OR=0.914, 95%CI: 0.839-0.995, P=0.039), time from sICH onset to first CT ( OR=0.855, 95%CI: 0.741-0.987, P=0.032), and diabetes ( OR=0.522, 95%CI: 0.311-0.875, P=0.014) were independent risk factors for HE. By using LASSO regression and 10-fold cross-validation method, 20 optimal radiomics features were finally selected. The area under ROC curve of clinical model, R-score model, and clinical-radiomics combined model were 0.650, 0.860, and 0.870, respectively. The calibration curve showed that the prediction accuracy of clinical-radiomics combined model in early HE had good consistency with the actual occurrence probability. Conclusion:The clinical-radiomics combined model could effectively predict early HE with good calibration, which is helpful in individualized clinical assessment of risk of early HE in SICH patients.

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively.The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

Objective: To explore the features of ascending aortic distensibility (AAD) and risk factors in pre-hypertension (PHT) patients. Methods: A total of 206 participants who received retrospective ECG-triggered coronary CTA by physical check-up or by clinically suspected coronary artery disease (CTA) were enrolled. The participants were divided into 2 groups: Control group, the subjects with normal blood pressure,n=85 and Pre-hypertension group,n=121. A 128 slice dual-source CT scanner was used and the image was automatically reconstructed at every 5% absolute phases in entire R-R interval. The beginning of left coronary artery plane was deifned as the reference and 25 mm above the reference plane was deifned as interested region. ADD value was calculated. Results: Compared with Control group, Pre-hypertension group had decreased AAD,P<0.01 and similar normalized cross-sectional area (Ss),P>0.05; ADD value was similar among different gender and blood lipid levels. Correlation analysis presented that AAD was negatively related to age (r=-0.69,P=0.001), systolic blood pressure (r=-0.37,P=0.001), pulse pressure(r=-0.43,P=0.001) and glycosylated hemoglobin (r=-0.43,P<0.05). Age and systolic blood pressure were the independent risk factors for AAD decline (standardized β=-0.66,P=0.001) and (standardized β=-0.44,P=0.001). Conclusion: Without additional contrast media consumption and radiation dosage, retrospective ECG-triggered coronary CTA may detect AAD changes with risk factors at the early stage in pre-hypertension patients which is helpful to distinguish the high risk individuals.

Objective To investigate the effect of intermittent fasting on metabolize and gut microbiota in obese presenium rats fed with high-fat-sugar-diet. Methods We fed the Wistar rats with high-fat and high-sugar diet to induce adiposity, and the rats for intermittent fasting were selected base on their body weight. The rats were subjected to fasting for 72 h every 2 weeks for 18 weeks. OGTT test was performed and fasting blood samples and fecal samples were collected for measurement of TC, TG, HDL-C and LDL-C and sequence analysis of fecal 16S rRNA V4 tags using Illumina. Gut microbial community structure was analyzed with QIIME and LEfSe. Results After the intervention, the body weight of the fasting rats was significantly lower than that in high-fat diet group (P<0.01). OGTT results suggested impairment of sugar tolerance in the fasting group, which showed a significantly larger AUC than compared with the high-fat diet group (P<0.05). Intermittent fasting significantly reduced blood HDL-C and LDL-C levels (P<0.05) and partially restored liver steatosis, and improved the gut microbiota by increasing the abundance of YS2, RF32 and Helicobacteraceae and reducing Lactobacillus, Roseburia, Erysipelotrichaceae and Ralstonia. Bradyrhizobiaceae was found to be positively correlated with CHOL and HDL-C, and RF39 was inversely correlated with the weight of the rats. Conclusion Intermittent fasting can decrease the body weight and blood lipid levels and restore normal gut microbiota but can cause impairment of glucose metabolism in obese presenium rats.

Objective To investigate the effect of intermittent fasting on metabolize and gut microbiota in obese presenium rats fed with high-fat-sugar-diet. Methods We fed the Wistar rats with high-fat and high-sugar diet to induce adiposity, and the rats for intermittent fasting were selected base on their body weight. The rats were subjected to fasting for 72 h every 2 weeks for 18 weeks. OGTT test was performed and fasting blood samples and fecal samples were collected for measurement of TC, TG, HDL-C and LDL-C and sequence analysis of fecal 16S rRNA V4 tags using Illumina. Gut microbial community structure was analyzed with QIIME and LEfSe. Results After the intervention, the body weight of the fasting rats was significantly lower than that in high-fat diet group (P<0.01). OGTT results suggested impairment of sugar tolerance in the fasting group, which showed a significantly larger AUC than compared with the high-fat diet group (P<0.05). Intermittent fasting significantly reduced blood HDL-C and LDL-C levels (P<0.05) and partially restored liver steatosis, and improved the gut microbiota by increasing the abundance of YS2, RF32 and Helicobacteraceae and reducing Lactobacillus, Roseburia, Erysipelotrichaceae and Ralstonia. Bradyrhizobiaceae was found to be positively correlated with CHOL and HDL-C, and RF39 was inversely correlated with the weight of the rats. Conclusion Intermittent fasting can decrease the body weight and blood lipid levels and restore normal gut microbiota but can cause impairment of glucose metabolism in obese presenium rats.