The goal of the research was to evaluate the application of self-developed virtual simulation software of fiber post all-ce-ramic crown restoration in the teaching of dental undergraduates.Fifty-five undergraduates majoring in stomatology were enrolled,including 26 sophomores and 29 senior students.Theoretical lecture and virtual simulation software of fiber post all-ceramic crown restoration were used for teaching.After class,questionnaires were completed by the students.The results of the questionnaire showed that more than half of the students were very interested in the virtual simulation software of this course(56.36％),and try-ing other forms of virtual simulation courses(52.73％).The simulation stimulated their interest in in-depth learning of prosthodon-tics(52.73％)and their expectation for the future working environment(54.55％).They were very satisfied with the virtual simula-tion effect(52.73％).Compared with two different grades,there are significant differences in the statistical data of three survey questions,including whether they are interested in in-depth study of prosthodontics,whether they have expectations for the future working environment,and whether they can clearly understand basic anatomical structure of teeth and basic concepts such as post,core and root canal.There was no significant difference in other questionnaire between grades.The virtual simulation software of fi-ber post all-ceramic crown restoration has a good effect on the teaching of dental undergraduates,which worth carrying out and pro-moting in the future teaching work.

Objective To investigate the changes of diameter of the main trunk of the extracranial segment of the facial nerve,local hemodynamics and facial muscle thickness in patients with peripheral facial palsy(PFP)at acute stage by high frequency ultrasound(HFUS).Methods Sixty patients with acute PFP were enrolled as the PFP group,and 30 healthy people were selected as the control group.The following facial param-eters were scanned and recorded using HFUS:diameter of the main trunk of the extracranial segment of the facial nerve(FN-d),facial artery diameter(FA-d),facial artery systolic velocity(FA-Vs),facial artery diastolic velocity(FA-Vd),facial artery resistance index(FA-RI),frontalis muscle thickness(FM-t),depressor anguli oris muscle thickness(DAO-t),and depressor labii inferioris muscle thickness(DLI-t).The feasibility of facial param-eters in the diagnosis of acute-phase peripheral facial palsy(PFP)was evaluated,with intra-group and inter-group variability comparisons performed.Pearson correlation analysis was conducted to evaluate the relationship between acute-phase facial parameters and House-Brackmann(H-B)scale scores in PFP patients.Results(1)The H-B score of the PFP group was significantly lower than that of the control group,and the difference was statistically significant(P＜0.05).(2)The reliability of repeated measurements of facial parameters by different testers is good(ICC＞0.75).(3)The FN-d and FA-RI values on the affected side of PFP group were higher than those on the healthy side and control group,and FA-Vs,FA-Vd,DAO-t and DLI-t values were lower than those on the healthy side and control group,with statistical significance(P＜0.05).(4)The FN-d and FA-RI values of the affected side in the PFP group were negatively correlated with the H-S scale score(r=-0.847,P＜0.05;r=-0.863,P＜0.05);FA Vs,FA Vd,DAO-t,DLI-t are positively correlated with H-S scale scores(r=0.808,P＜0.05;r=0.757,P＜0.05;r=0.836,P＜0.05;r=0.694,P＜0.05).Conclusions HFUS can effectively detect the characteristic changes such as the increase in the diameter of the extrcranial facial nerve trunk,local microcircula-tion disturbance and facial muscle atrophy in patients with PFP in the acute stage,and the increase and decrease of FN-d,FA Vs,FA Vd,FA-RI,DAO-t,and DLI-t can accurately reflect the improvement or progress of PFP,which has important guiding significance for clinical disease monitoring and efficacy evaluation.

Objective:To construct classification models of traumatic brain injury (TBI) based on the injury data collected at the scene of the accidents and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the pre-hospital treatment data of 368 TBI patients admitted to the Second Affiliated Hospital of Army Military Medical University from January 2019 to December 2023, including 243 males and 125 females, aged 18-82 years [(48.1±20.8)years]. The patients′ Glasgow coma scale (GCS) scores were 3-15 points [11.0(3.0, 15.0)points] at emergency medical service arrival. The patients were randomly assigned to the training set ( n=257) and test set ( n=111) at a ratio of 7∶3. According to the admission diagnosis, the patients fell into the mild TBI group ( n=62), medium TBI group ( n=137), severe TBI group ( n=120), and extremely severe TBI group ( n=49). In the training set, 44 patients fell into mild TBI group, 98 into medium TBI group, 82 into severe TBI group and 33 into extremely severe TBI group, while in the test set, 18 patients fell into mild TBI group, 39 into medium TBI group, 38 into severe TBI group and 16 into extremely severe TBI group. The following 12 kinds of injury data, including MARCH [massive hemorrhage (M), airway obstruction (A), respiratory failure (R), circulatory failure (C) and hypothermia (H)], GCS, pre-hospital index (PHI), shock index (SI), reverse SI multiplied by GCS (rSIG), optic nerve sheath diameter (ONSD) measured by ultrasound, scalp and skull injuries were collected at the scene of the accidents. Three machine algorithm including random forest (RF), support vector machine (SVM) and logistic regression (LR) were used to construct scene data-based TBI classification models. The accuracy rate, precision rate, recall rate, F1 value and area under receiver operating characteristic (ROC) curve (AUC) of the 3 models were used to verify the efficiency of the models for TBI classification. Shapley additive explanations (SHAP) method was used to interpret the results of the optimal model. The 12 kinds of injury data in the models were sorted according to their contribution to the TBI classification and the injury data with greater contribution were selected. Results:In the test set, the accuracy rate of the RF, SVM and LR models was 0.93, 0.92 and 0.87, respectively; the precision rate was 0.93, 0.92 and 0.89, respectively; the recall rate was 0.93, 0.92 and 0.87, respectively; the F1 value was 0.93, 0.92 and 0.87, respectively. In the mild, medium, severe and extremely severe TBI groups in the test set, the AUC of the RF model was 0.96 (95% CI 0.92, 0.98), 0.98 (95% CI 0.94, 0.99), 0.97 (95% CI 0.95, 0.98), and 0.97 (95% CI 0.96, 0.98), respectively; the AUC of the SVM model was 0.90 (95% CI 0.88, 0.94), 0.95 (95% CI 0.92, 0.97), 0.96 (95% CI 0.94, 0.98), and 0.95 (95% CI 0.92, 0.99), respectively; the AUC of the LR model was 0.90 (95% CI 0.83, 0.96), 0.90 (95% CI 0.84, 0.95), 0.96 (95% CI 0.95, 0.98), and 0.95 (95% CI 0.94, 0.97), respectively. The RF model demonstrated optimal discriminative performance for TBI classification. As the SHAP′s interpretation of the RF model indicated, among the 12 kinds of injury data, those with greater contributions to the TBI classification were GCS, rSIG, SI, PHI, respiratory failure, ONSD, and circulatory failure in sequence. Conclusions:Of the scene data-based TBI classification models, the RF model achieves good predictive performance for TBI classification when compared with the SVM model and LR model. Besides, GCS, rSIG, SI, PHI, respiratory failure, ONSD and circulatory failure contribute significantly to the classification of TBI in the RF model, which may assist emergency medical personnel in field triage and management of TBI at accident scenes.

The goal of the research was to evaluate the application of self-developed virtual simulation software of fiber post all-ce-ramic crown restoration in the teaching of dental undergraduates.Fifty-five undergraduates majoring in stomatology were enrolled,including 26 sophomores and 29 senior students.Theoretical lecture and virtual simulation software of fiber post all-ceramic crown restoration were used for teaching.After class,questionnaires were completed by the students.The results of the questionnaire showed that more than half of the students were very interested in the virtual simulation software of this course(56.36％),and try-ing other forms of virtual simulation courses(52.73％).The simulation stimulated their interest in in-depth learning of prosthodon-tics(52.73％)and their expectation for the future working environment(54.55％).They were very satisfied with the virtual simula-tion effect(52.73％).Compared with two different grades,there are significant differences in the statistical data of three survey questions,including whether they are interested in in-depth study of prosthodontics,whether they have expectations for the future working environment,and whether they can clearly understand basic anatomical structure of teeth and basic concepts such as post,core and root canal.There was no significant difference in other questionnaire between grades.The virtual simulation software of fi-ber post all-ceramic crown restoration has a good effect on the teaching of dental undergraduates,which worth carrying out and pro-moting in the future teaching work.

Objective To investigate the changes of diameter of the main trunk of the extracranial segment of the facial nerve,local hemodynamics and facial muscle thickness in patients with peripheral facial palsy(PFP)at acute stage by high frequency ultrasound(HFUS).Methods Sixty patients with acute PFP were enrolled as the PFP group,and 30 healthy people were selected as the control group.The following facial param-eters were scanned and recorded using HFUS:diameter of the main trunk of the extracranial segment of the facial nerve(FN-d),facial artery diameter(FA-d),facial artery systolic velocity(FA-Vs),facial artery diastolic velocity(FA-Vd),facial artery resistance index(FA-RI),frontalis muscle thickness(FM-t),depressor anguli oris muscle thickness(DAO-t),and depressor labii inferioris muscle thickness(DLI-t).The feasibility of facial param-eters in the diagnosis of acute-phase peripheral facial palsy(PFP)was evaluated,with intra-group and inter-group variability comparisons performed.Pearson correlation analysis was conducted to evaluate the relationship between acute-phase facial parameters and House-Brackmann(H-B)scale scores in PFP patients.Results(1)The H-B score of the PFP group was significantly lower than that of the control group,and the difference was statistically significant(P＜0.05).(2)The reliability of repeated measurements of facial parameters by different testers is good(ICC＞0.75).(3)The FN-d and FA-RI values on the affected side of PFP group were higher than those on the healthy side and control group,and FA-Vs,FA-Vd,DAO-t and DLI-t values were lower than those on the healthy side and control group,with statistical significance(P＜0.05).(4)The FN-d and FA-RI values of the affected side in the PFP group were negatively correlated with the H-S scale score(r=-0.847,P＜0.05;r=-0.863,P＜0.05);FA Vs,FA Vd,DAO-t,DLI-t are positively correlated with H-S scale scores(r=0.808,P＜0.05;r=0.757,P＜0.05;r=0.836,P＜0.05;r=0.694,P＜0.05).Conclusions HFUS can effectively detect the characteristic changes such as the increase in the diameter of the extrcranial facial nerve trunk,local microcircula-tion disturbance and facial muscle atrophy in patients with PFP in the acute stage,and the increase and decrease of FN-d,FA Vs,FA Vd,FA-RI,DAO-t,and DLI-t can accurately reflect the improvement or progress of PFP,which has important guiding significance for clinical disease monitoring and efficacy evaluation.

Objective:To construct classification models of traumatic brain injury (TBI) based on the injury data collected at the scene of the accidents and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the pre-hospital treatment data of 368 TBI patients admitted to the Second Affiliated Hospital of Army Military Medical University from January 2019 to December 2023, including 243 males and 125 females, aged 18-82 years [(48.1±20.8)years]. The patients′ Glasgow coma scale (GCS) scores were 3-15 points [11.0(3.0, 15.0)points] at emergency medical service arrival. The patients were randomly assigned to the training set ( n=257) and test set ( n=111) at a ratio of 7∶3. According to the admission diagnosis, the patients fell into the mild TBI group ( n=62), medium TBI group ( n=137), severe TBI group ( n=120), and extremely severe TBI group ( n=49). In the training set, 44 patients fell into mild TBI group, 98 into medium TBI group, 82 into severe TBI group and 33 into extremely severe TBI group, while in the test set, 18 patients fell into mild TBI group, 39 into medium TBI group, 38 into severe TBI group and 16 into extremely severe TBI group. The following 12 kinds of injury data, including MARCH [massive hemorrhage (M), airway obstruction (A), respiratory failure (R), circulatory failure (C) and hypothermia (H)], GCS, pre-hospital index (PHI), shock index (SI), reverse SI multiplied by GCS (rSIG), optic nerve sheath diameter (ONSD) measured by ultrasound, scalp and skull injuries were collected at the scene of the accidents. Three machine algorithm including random forest (RF), support vector machine (SVM) and logistic regression (LR) were used to construct scene data-based TBI classification models. The accuracy rate, precision rate, recall rate, F1 value and area under receiver operating characteristic (ROC) curve (AUC) of the 3 models were used to verify the efficiency of the models for TBI classification. Shapley additive explanations (SHAP) method was used to interpret the results of the optimal model. The 12 kinds of injury data in the models were sorted according to their contribution to the TBI classification and the injury data with greater contribution were selected. Results:In the test set, the accuracy rate of the RF, SVM and LR models was 0.93, 0.92 and 0.87, respectively; the precision rate was 0.93, 0.92 and 0.89, respectively; the recall rate was 0.93, 0.92 and 0.87, respectively; the F1 value was 0.93, 0.92 and 0.87, respectively. In the mild, medium, severe and extremely severe TBI groups in the test set, the AUC of the RF model was 0.96 (95% CI 0.92, 0.98), 0.98 (95% CI 0.94, 0.99), 0.97 (95% CI 0.95, 0.98), and 0.97 (95% CI 0.96, 0.98), respectively; the AUC of the SVM model was 0.90 (95% CI 0.88, 0.94), 0.95 (95% CI 0.92, 0.97), 0.96 (95% CI 0.94, 0.98), and 0.95 (95% CI 0.92, 0.99), respectively; the AUC of the LR model was 0.90 (95% CI 0.83, 0.96), 0.90 (95% CI 0.84, 0.95), 0.96 (95% CI 0.95, 0.98), and 0.95 (95% CI 0.94, 0.97), respectively. The RF model demonstrated optimal discriminative performance for TBI classification. As the SHAP′s interpretation of the RF model indicated, among the 12 kinds of injury data, those with greater contributions to the TBI classification were GCS, rSIG, SI, PHI, respiratory failure, ONSD, and circulatory failure in sequence. Conclusions:Of the scene data-based TBI classification models, the RF model achieves good predictive performance for TBI classification when compared with the SVM model and LR model. Besides, GCS, rSIG, SI, PHI, respiratory failure, ONSD and circulatory failure contribute significantly to the classification of TBI in the RF model, which may assist emergency medical personnel in field triage and management of TBI at accident scenes.

Accurate segmentation of oral surgery-related tissues from cone beam computed tomography(CBCT)images can significantly accelerate treatment planning and improve surgical accuracy.In this paper,we propose a fully automated tissue segmentation system for dental implant surgery.Specifically,we propose an image preprocessing method based on data distribution histograms,which can adaptively process CBCT images with different parameters.Based on this,we use the bone segmentation network to obtain the segmentation results of alveolar bone,teeth,and maxillary sinus.We use the tooth and mandibular regions as the ROI regions of tooth segmentation and mandibular nerve tube segmentation to achieve the corresponding tasks.The tooth segmentation results can obtain the order information of the dentition.The corresponding experimental results show that our method can achieve higher segmentation accuracy and efficiency compared to existing methods.Its average Dice scores on the tooth,alveolar bone,maxillary sinus,and mandibular canal segmentation tasks were 96.5%,95.4%,93.6%,and 94.8%,respectively.These results demonstrate that it can accelerate the development of digital dentistry.

Drugs under special management include narcotic drugs,psychotropic drugs,toxic drugs for medical use,radiopharmaceuticals,and pharmaceutical precursor chemicals.Supervising and guiding the clinical use of drugs under special management is one of the important responsibilities of the Pharmaceutical Management and Drug Therapy Committee(Group)of medical institutions.The standard for drugs under special management is led by the Pharmaceutical Professional Committee of the China Hospital Association,which standardizes 16 key elements of organizational management,process management,and quality control management drugs under special management in medical institutions.It can guide the standardized implementation of Pharmaceuticals under special control work in various levels and types of medical institutions.This article elaborates on the methods and contents of formulating standards for Pharmaceuticals under special management,to provide reference and inspiration for medical institutions to carry out special drug drug management and daily related work.

Objective:To evaluate the clinical efficacy of Fried Licorice Decoction Plus-minus in combination with PD-1 therapy for patients with advanced non-small cell lung cancer(NSCLC)with Qi-Yin deficiency.Methods:From December 2020 to December 2022,72 patients diagnosed with advanced NSCLC with Qi-Yin deficiency were enrolled in this study.The patients were recruited from Jilin Provincial Cancer Hospital and the Affiliated Hospital of Changchun University of Chinese Medicine.The patients were randomly assigned into two groups,with 36 patients in each group.The control group received PD-1 treatment alone,and the treatment group received PD-1 combined with Fried Licorice Decoction Plus-minus.The measures of primary outcomes included immune function(CD3+,CD3+/CD4+,and CD3+/CD8+)and quality of life score(Kamofsky,KPS).The measures of secondary outcomes included the objective response rate(ORR);traditional Chinese medicine(TCM)symptom score;serum tumor marker carcinoembryonic antigen(CEA);neuron-specific enolase(NSE);cytokeratin fragment(CYFRA211);and incidence of immune-related adverse events such as gastrointestinal toxicity,pulmonary toxicity,hepatotoxicity,and thyroid toxicity.Results:Regarding immune function regulation,a significant improvement was observed in CD3+,CD3+/CD4+,and CD3+/CD8+.Furthermore,at T3 and T4 time points,an improvement was observed in patient quality of life indicators such as the tumor markers CEA and CY211.In addition,symptoms related to TCM syndrome,including coughing,fatigue,palpitations,and diarrhea were significantly reduced compared to the baseline levels.Moreover,the treatment group exhibited superior outcomes compared to those of the control group in terms of reducing immune-associated pneumonia and diarrhea(P<0.05).The ORR for both groups was similar;36%for those receiving com-bination therapy vs.25%for those receiving PD-1 monotherapy.Therefore,no significant differences between these two groups were ob-served(P>0.05).Conclusions:The combination of Fried Licorice Decoction Plus-minus and PD-1 in the treatment of patients with advanced NSCLC showed a significant enhancement in immune function,improvement in clinical efficacy,reduction in immune-related adverse reac-tions,and had an excellent safety profile.

Objective:To explore the current situation of nurses' turnover intention and its influencing factors based on the intergenerational differences, analyze the similarities and differences.Methods:From January to March 2018, 12 291 nurses from 23 general hospitals were selected by stratified cluster sampling. The nurses were investigated with the Turnover Intention Questionnaire, Work-Family Conflict Scale and Perceived Person-Environment Fit Scale. Pearson correlation analysis was used to explore the correlation between nurses' work-family conflict, person-environment fit and turnover intention. Multiple linear regression analysis was used to explore the influencing factors of nurses' turnover intention among different generations. A total of 12 291 questionnaires were distributed and 12 291 were retrieved. After eliminating the questionnaires with obvious logical errors, 11 753 valid questionnaires were finally recovered, with an effective recovery rate of 95.62% (11 753/12 291) .Results:The turnover intention of post-70s nurses was lower than that of post-80s and post-90s nurses. Work-family conflict, person-environment fit and whether the nurses have experienced negative events in the past year were the common influencing factors of nurses' turnover intention among different generations ( P<0.01) . The professional title, the number of night shifts and the fertility were the specific influencing factors of the post-90s nurses' turnover intention ( P<0.05) . The employment form was the specific influencing factor of post-80s nurses' turnover intention ( P<0.05) . Conclusions:The turnover intention of post-80s and post-90s nurses were higher than that of the post-70s nurses. There are differences in the current situation and influencing factors of nurses' turnover intention in different birth years. It is suggested that intervention strategies should be formulated according to the intergenerational characteristics of nurses to effectively reduce nurses' turnover intention.