Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Objective:To aid in the detection of thyroid cancer by using deep learning to differentiate the unique bioimpedance parameter patterns of different thyroid tissues.Methods:An electrical impedance system was designed to measure 331 ex-vivo thyroid specimens from 321 patients during surgery. The impedance data was then analyzed with one dimensional convolution neural (1D-CNN) combining with long short-term memory (LSTM) network models of deep learning. In the process of analysis, we assigned 80% of the data to training set (1072/1340) and the remaining 20% data to the test set (268/1340). The performance of final model was assessed using receiver operating characteristic (ROC) curves. In addition, sensitivity, specificity, positive predictive value, negative predictive value, Youden index were applied to compare impedance model with ultrasound results.Results:The ROC curve of the two-classification (malignant /non-malignant tissue) model showed a good performance (area-under-the-curve AUC=0.94), with an overall accuracy of 91.4%. To better fit clinical practice, we further performed a three-classification (malignant/ benign/ normal tissue) model, of which the areas under ROC curve were 0.91, 0.85, 0.92 for normal, benign, and malignant group, respectively. The results indicated that the area under micro-average ROC curve and the macro-average ROC curve were 0.91 and 0.90, respectively. Moreover, compared with ultrasound, the impedance model exhibited higher specificity.Conclusions:A deep learning model (CNN-LSTM) trained by thyroid electrical impedance spectroscopy (EIS) parameters shows an excellent performance in distinguishing among different in-vitro thyroid tissues, which is promising for applications. In future clinical utility, our study does not replace existing tests, but rather complements others, thus contributing to therapeutic decision-making and management of thyroid disease.

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

Digital guided therapy (DGT) has been advocated as a contemporary computer-aided technique for treating endodontic diseases in recent decades. The concept of DGT for endodontic diseases is categorized into static guided endodontics (SGE), necessitating a meticulously designed template, and dynamic guided endodontics (DGE), which utilizes an optical triangulation tracking system. Based on cone-beam computed tomography (CBCT) images superimposed with or without oral scan (OS) data, a virtual template is crafted through software and subsequently translated into a 3-dimensional (3D) printing for SGE, while the system guides the drilling path with a real-time navigation in DGE. DGT was reported to resolve a series of challenging endodontic cases, including teeth with pulp obliteration, teeth with anatomical abnormalities, teeth requiring retreatment, posterior teeth needing endodontic microsurgery, and tooth autotransplantation. Case reports and basic researches all demonstrate that DGT stand as a precise, time-saving, and minimally invasive approach in contrast to conventional freehand method. This expert consensus mainly introduces the case selection, general workflow, evaluation, and impact factor of DGT, which could provide an alternative working strategy in endodontic treatment.
Humans ; Consensus ; Endodontics/methods* ; Tooth ; Printing, Three-Dimensional ; Dental Care ; Cone-Beam Computed Tomography ; Root Canal Therapy

Purpose To explore the artificial intelligence(AI)-assisted diagnosis system of thyroid cancer based on deep transfer learning and evaluate its clinical application value.Methods The HE sections of 682 cases thyroid disease patients(including benign lesions,papillary carcinoma,follicular carci-noma,medullary carcinoma and undifferentiated carcinoma)in the Pathology Department of the Renmin Hospital of Wuhan Uni-versity were collected,scanned into digital sections,divided into training sets and internal test sets according to the ratio of 8 ∶ 2,and the training sets were labeled at the pixel level by patholo-gists.The thyroid cancer classification model was established u-sing VGG image classification algorithm model.In the process of model training,the parameters of the breast cancer region recog-nition model were taken as the initial values,and the parameters of the thyroid cancer region recognition model were optimized through the transfer learning strategy.Then the test set and 633 intraoperative frozen HE section images of thyroid disease in Jianli County People's Hospital,Jingzhou City,Hubei Province wereused as the external test set to evaluate the performance of the established AI-assisted diagnostic model.Results In the internal test set,without the use of the breast cancer region rec-ognition model transfer learning,the accuracy of the AI-assisted diagnosis model was 0.882,and the area under the Receiver op-erating characteristic(AUC)valuewas0.938;However,inthe use of the Transfer learning model,the accuracy of the AI-assis-ted diagnosis model for was 0.926,and the AUC value was 0.956.In the external test set,the accuracy of the zero learning model was 0.872,the AUC value was 0.915,and the accuracy of the Transfer learning model was 0.905,the AUC value was 0.930.Conclusion The AI-assisted diagnosis method for thy-roid cancer established in this study has good accuracy and gen-eralization.With the continuous development of pathological AI research,transfer learning can help improve the performance and generalization ability of the model,and improve the accura-cy of the diagnostic model.

Objective:The residual cancer burden (RCB) evaluation system was used to analyze the influencing factors of the efficacy of neoadjuvant therapy in breast cancer, and to explore the prognostic value of RCB evaluation in neoadjuvant therapy.Methods:Clinicopathologic data and postoperative RCB grading of 364 breast cancer patients who underwent neoadjuvant therapy in Renmin Hospital of Wuhan University from Nov. 2019 to Nov. 2022 were collected. Chi-square test was used to analyze the relationship between RCB grading and clinicopathological parameters, and Spearman’s rank correlation analysis was performed to evaluate the correlation between RCB grading and clinicopathological characteristics. Factors influencing pathologic complete response (pCR) were analyzed by Logistic regression. Kaplan-Meier survival analysis and log-rank test were used to evaluate cumulative survival.Results:Among the 364 patients who underwent neoadjuvant therapy, 129 cases of RCB grade 0 and 235 cases of RCB gradeⅠ-Ⅲ (including 46 cases of RCB gradeⅠ, 109 cases of RCB grade Ⅱ and 80 cases of RCB grade Ⅲ) were obtained after surgery. Histological classification ( χ 2=21.757, P=0.000), estrogen receptor (ER) ( χ 2=52.837, P=0.000), progesterone receptor (PR) ( χ 2=55.658, P=0.000), human epidermal growth factor receptor-2 (HER2) ( χ2=89.040, P=0.000), Ki67 expression ( χ2=12.927, P=0.005), molecular typing ( χ 2=80.793, P=0.000) and preoperative lymph node status ( χ 2=25.764, P=0.000) were all associated with postoperative RCB grading. Further correlation analysis showed that histological grade ( r=-0.229, P=0.000), HER2 expression ( r=-0.465, P=0.000) and Ki67 expression ( r=-0.179, P=0.000) were negatively correlated with RCB grading, while ER ( r=0.352, P=0.000), PR ( r=0.379, P=0.000) and lymph node metastasis ( r=0.214, P=0.000) were positively correlated with RCB grading. Logistic regression analysis showed that high histological grade, negative expression of ER, PR and AR, positive expression of HER2, high proliferation index of Ki67 and no lymph node metastasis were favorable factors for postoperative pCR, and PR, AR and HER2 were independent predictors of postoperative pCR. Kaplan-Meier survival analysis showed significant differences in postoperative cumulative survival among patients with different RCB grades ( P=0.004) . Conclusions:Postoperative RCB grading of breast cancer is closely related to many clinicopathological features before neoadjuvant therapy and survival prognosis. Clinicopathological factors closely related to RCB grading are also important influencing factors affecting the pCR of patients with neoadjuvant therapy. Therefors, RCB grading has a high prognostic value.

Objective:To evaluate the effectiveness and safety of concurrent chemoradiotherapy combined with nimotuzumab in the treatment of patients with inoperable esophageal squamous cell carcinoma (ESCC).Methods:A retrospective analysis was conducted on the clinical data of 503 patients with inoperable ESCC who underwent concurrent chemoradiotherapy in the Department of Radiation Oncology, Changzhou No. 2 People′s Hospital Affiliated to Nanjing Medical University and Department of Radiation Oncology, Affiliated Hospital of Jiangnan University from 2014 to 2020. Among these patients, 69 received concurrent chemoradiotherapy combined with nimotuzumab (the combined therapy group) and 434 received concurrent chemoradiotherapy alone (the concurrent chemoradiotherapy group). Patients of both groups were matched at a ratio of 1∶2 using the propensity score matching (PSM) method. As a result, 168 patients were determined for clinical analysis, including 61 in the combined therapy group and 107 in the concurrent chemoradiotherapy group. The short-term efficacy and adverse reactions of both groups were compared. The overall survival (OS) curves and progression-free survival (PFS) curves were plotted using the Kaplan-Meier method for the Log-rank test.Results:The two groups showed no statistical difference ( P > 0.05) in clinical baseline characteristics after the PSM. The objective response rate (ORR) of the combined therapy group was significantly higher than that of the concurrent chemoradiotherapy group with statistically significant differences (85.2% vs. 71.0%, χ2 = 4.33, P = 0.037). There was no statistical difference (98.4% vs. 91.6%, P > 0.05) in the disease control rate (DCR) between the two groups. The combined therapy group had median PFS of 28.07 months and 1-, 3-, and 5-year PFS ratios of 78.2%, 37.5% and 29.1%, respectively. The concurrent chemoradiotherapy group had mPFS of 19.54 months and 1-, 3-, and 5-year PFS ratios of 72.9%, 28.3% and 21.3%, respectively. Both groups showed statistically significant differences in PFS ( χ2 = 4.49, P = 0.034). The combined group had median OS of 34.93 months and 1-, 3-, and 5-year OS ratios of 88.5%, 46.8% and 37.4%, respectively. The concurrent chemoradiotherapy group had mOS of 24.30 months and 1-, 3-, and 5-year OS ratios of 81.3%, 35.2% and 28.0%, respectively. Both groups showed statistically significant differences in OS (χ 2= 5.11, P = 0.024), but did not show statistical differences ( P > 0.05) in the severity degree of each adverse effect during the treatment. Conclusions:Concurrent chemoradiotherapy combined with nimotuzumab can improve the ORR and prolong the PFS and OS of patients with inoperable ESCC compared with concurrent chemoradiotherapy alone. Furthermore, combining with nimotuzumab does not increase adverse effects and can be tolerated by patients with high safety.

We report a case of fetal akinesia deformation sequence (FADS), which was prenatally suspected on ultrasound and confirmed by whole exome sequencing and Sanger sequencing after mid-term termination. Prenatal ultrasonography revealed multiple abnormalities in a fetus at 21 +4 weeks of gestation, consisting of fixed posture of limbs, narrow thorax, markedly shrunken gastric vacuole, and thickened nuchal fold. After genetic counseling, the pregnancy was terminated, and the appearance of the fetus was consistent with the ultrasound findings. Whole exome sequencing and Sanger sequencing of the fetal tissue verified a compound heterozygous variation of the RAPSN gene--c.149_153delins AGATGGGCCGCTACAAGGAGATGG (p.V50Efs*114) and c.227T>C (p.L76P), which were inherited from the father and mother, respectively, ultimately confirming the diagnosis of FADS.

Objective:To investigate the current situation of nurses′ professionalism in secondary and tertiary general hospitals, analyze its influence factors, and establish norms of nurses′ professionalism in secondary and tertiary hospitals, so as to provide references for evaluation the level of professionalism in nurses.Methods:From May to December 2016, the nurses′ professionalism evaluation system was used to investigate 3 315 nurses in 35 secondary and tertiary general hospitals in 14 cities of 7 regions in China by using random cluster sampling, and the corresponding norm, classification norm and delimitation norm were defined.Results:The average norm scores of nurses′ professionalism in the secondary and tertiary general hospitals was (71.02 ± 16.70), and the average norm scores of each dimension were professional ethics (18.97 ± 4.52) , comprehensive capabilities (17.99 ± 4.46), professional skills (17.07 ± 4.80), professional emotions (16.98 ± 4.70) . According to the differences in characteristics, the classification norms for different gender, age, working years, educational background, professional title, position, department, marital status, with or without children were formed. The level of nurses′ professionalism was divided into five grades: the total score in the interval [90.92, 100.00] was excellent, in the interval [78.31, 90.92) was good, in the interval [64.27, 78.31) was general, in the interval [50.49, 64.27) was relatively poor, in the interval [0.00, 50.49) was poor.Conclusions:Nurses′ professionalism in secondary and tertiary hospitals was in the general level and affected by a variety of factors, medical managers and nursing managers should take corresponding measures to improve nurses′ professionalism.

Objective:To explore the status and influencing factors of incontinence-associated dermatitis among elderly inpatients in 52 hospitals nationwide, and to analyze the nursing of elderly inpatients with incontinence, so as to provide a reference for clinical intervention.Methods:On March 31, 2021, convenience sampling was used to select 14 675 elderly inpatients from 52 hospitals across the country as the research object. The self-designed Incontinence-associated Dermatitis Questionnaire for Elderly Inpatients was used to collect general demographic data, health status, incontinence, and skin nursing. Binomial Logistic regression was used to investigate the influencing factors of incontinence-associated dermatitis in elderly inpatients.Results:Among 14 675 elderly inpatients, the prevalence rates of xerosis cutis, incontinence and incontinence-associated dermatitis were 38.78% (5 691/14 675) , 11.06% (1 623/14 675) and 1.91% (280/14 675) , respectively. The prevalence of mild, moderate and severe incontinence-associated dermatitis were 1.27% (186/14 675) , 0.55% (81/14 675) , and 0.09% (13/14 675) , respectively. Among the nursing of 1 623 elderly inpatients with incontinence, the items with low implementation rate were the use neutral lotion to clean skin (14.17%, 230/1 623) , use of skin protectant after moisturizing (17.68%, 287/1 623) , moisturizing after cleansing the skin (28.90%, 469/1 623) . The results of binomial Logistic regression analysis showed that xeroderma, fecal incontinence, urinary and fecal incontinence, ≥2 kinds of combined medication, and hospital stay >30 days were risk factors for incontinence-associated dermatitis in elderly inpatients.Conclusions:The risk factors of incontinence-associated dermatitis in elderly inpatients mainly include xerosis cutis, type of incontinence, ≥2 kinds of combined medication, and hospital stay >30 days.