OBJECTIVE To investigate the correlation of component content with colorimetric values during the roasting process of Ziziphus jujuba ， and to provide criteria for discriminating the roasting degree of Z. jujuba . METHODS Samples were prepared by dry stir-frying for different roasting times. The eight main components in raw Z. jujuba and the samples stir-fried for different roasting times-namely adenosine， magnoflorine， jujuboside A， spinosin， 6-feruloylspinosin， betulinic acid， oleic acid， and linoleic acid-were quantitativel y analyzed using ultra-performance liquid chromatography. The chromaticity values were determined using a UV spectrophotometer. The correlation and differences between the chromaticity values of Z. jujuba at different roasting times and their components content were analyzed by Pearson correlation analysis， linear regression analysis， principal component analysis （PCA） ， cluster heatmap analysis （CHA）， and partial least squares discriminant analysis （PLS-DA） to clarify the processing endpoint. RESULTS As the roasting time increased， the contents of linoleic acid and oleic acid decreased， while the contents of other components exhibited an increasing trend. Concurrently， the colorimetric value L* and E*ab were observed to decline， whereas the a* value demonstrated a gradual increase. Pearson correlation analysis revealed that L* and E*ab exhibited a significant negative correlation with the contents of adenosine， spinosin， 6-feruloylspinosin， jujuboside A， betulinic acid and magnoflorine （ P ＜0.05）. The results of linear regression analysis indicate that the content of six components, including adenosine， in the medicinal material can be preliminarily predicted by analyzing the colorimetric values of Z. jujuba powder. PCA and CHA successfully classified raw and stir-fried samples. The PLS-DA results indicated that L*， E*ab， a*， linoleic acid content， and oleic acid content were the main parameters that differentiated the color and quality of Z. jujuba at different roasting times. After frying for 9 to 10 minutes， the colorimetric values L* and E*ab decreased to their minimum values and stabilized， while a* remained consistently high with little variation；simultaneously， the concentrations of the six major components， excluding linoleic acid and oleic acid， reached their peak levels. CONCLUSIONS A significant correlation between the colorimetric values of Z. jujuba and the contents of six components， including adenosine， is confirmed. The optimal roasting time range is determined to be 9-10 minutes. Furthermore， the colorimetric value-component content correlation analysis method established in this study proved to be practical and applicable for discriminating the roasting degree of Z. jujuba .

Objective:To investigate the value of midtreatment 18F-FDG PET/CT metabolic parameters for predicting the pathological response in patients with locally advanced gastric cancer (LAGC) after neoadjuvant immunochemotherapy (NICT). Methods:Twenty-five LAGC patients (19 males, 6 females, age: (64.8±8.6) years) who underwent 18F-FDG PET/CT after NICT in Henan Cancer Hospital from August 2019 to June 2024 were retrospectively analyzed. The lesion′s ROI was delineated, then the SUV max and metabolic tumor volume (MTV) were measured, and the SUV max was divided by SUV mean of the descending aorta to obtain the tumor-to-background ratio (TBR). Patients underwent surgery after PET/CT imaging. Based on the tumor regression grade (TRG) system by the American Joint Committee on Cancer (AJCC) criteria on surgical specimen, patients were divided into responders (TRG0+ 1) and non-responders (TRG2+ 3). Independent-sample t test, Mann-Whitney U test, one-way analysis of variance, and Kruskal-Wallis rank-sum test were used to compare the differences of data. The predictive efficacy of PET/CT metabolic parameters was assessed by the ROC curve analysis. Results:Postsurgical pathology showed that 9 patients were responders and 16 were non-responders. The SUV max (3.10±1.95) and TBR (2.44±1.54) of primary lesions in responders were lower than those in non-responders (7.40±4.68, 5.85±3.74; t values: -2.61, -2.59, both P<0.05), while the MTV of primary tumors and short diameter and metabolic parameters of positive lymph nodes were not significantly different between those 2 groups ( t=-1.50, Z values: -1.09 to -0.75, all P>0.05). No significant relation was found between PET/CT parameters and pathological differentiation or Lauren classification, or other pathological features ( t values: -1.55 to 1.38, Z values: -1.84 to 0, F values: 0.12-2.43, H values: 0.13-0.98, all P>0.05). ROC curve showed that the cut-off value of SUV max for predicting postoperative TRG was 5.40, and the AUC reached 0.77 (95% CI: 0.56-0.91), with the sensitivity and specificity of 9/16, 9/9, respectively. With TBR=3.54 as the cut-off value, its AUC reached 0.77 (95% CI: 0.56-0.91), and the sensitivity and specificity were 11/16, 8/9, respectively. The sensitivity and specificity of PET/CT for predicting lymph node positivity of patients were 8/12 and 13/13, respectively. Conclusion:Interim 18F-FDG PET/CT metabolic parameters can accurately predict the pathological response of LAGC patients after NICT.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To study the impact of fluoride exposure through drinking water on the risk of hypertension among residents in Jishan County, Shanxi Province.Methods:From March to April 2023, a cluster sampling method was used to select permanent residents aged ≥18 years and residing for ≥10 years in 12 villages in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province as the survey subjects. A questionnaire survey, physical examination, and morning urinary fluoride level testing were conducted. The least absolute shrinkage and selection operator (Lasso) regression were used to analyze the key influencing factors of hypertension. Restricted cubic spline was used to evaluate the linear relationship between urinary fluoride and hypertension. Logistic regression was used to analyze the impact of urinary fluoride on hypertension.Results:Finally, 2 453 survey subjects were included, aged (62 ± 10) years, including 1 565 patients (63.80%) with hypertension. There were significant differences in the distribution of age, gender, education level, annual household income, body mass index (BMI), and the level and distribution of urinary fluoride between hypertension group and normal blood pressure group ( P < 0.05). The Lasso regression results showed that age, education level, BMI, and urinary fluoride were the key influencing factors of hypertension, with coefficients of 1.04, - 0.12, 0.24 and 0.01, respectively. The results of the restricted cubic spline showed that there was a linear relationship between urinary fluoride and hypertension after adjusting for age, education level, and BMI ( Poverall = 0.018, Pnonlinear = 0.482). The logistic regression results showed that after adjusting for age, education level, and BMI, urinary fluoride > 4.68 mg/L was a risk factor for hypertension ( OR = 1.42, 95% CI: 1.10 - 1.84, P = 0.007). Conclusion:High urinary fluoride is a risk factor for hypertension in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province.

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 value of midtreatment 18F-FDG PET/CT metabolic parameters for predicting the pathological response in patients with locally advanced gastric cancer (LAGC) after neoadjuvant immunochemotherapy (NICT). Methods:Twenty-five LAGC patients (19 males, 6 females, age: (64.8±8.6) years) who underwent 18F-FDG PET/CT after NICT in Henan Cancer Hospital from August 2019 to June 2024 were retrospectively analyzed. The lesion′s ROI was delineated, then the SUV max and metabolic tumor volume (MTV) were measured, and the SUV max was divided by SUV mean of the descending aorta to obtain the tumor-to-background ratio (TBR). Patients underwent surgery after PET/CT imaging. Based on the tumor regression grade (TRG) system by the American Joint Committee on Cancer (AJCC) criteria on surgical specimen, patients were divided into responders (TRG0+ 1) and non-responders (TRG2+ 3). Independent-sample t test, Mann-Whitney U test, one-way analysis of variance, and Kruskal-Wallis rank-sum test were used to compare the differences of data. The predictive efficacy of PET/CT metabolic parameters was assessed by the ROC curve analysis. Results:Postsurgical pathology showed that 9 patients were responders and 16 were non-responders. The SUV max (3.10±1.95) and TBR (2.44±1.54) of primary lesions in responders were lower than those in non-responders (7.40±4.68, 5.85±3.74; t values: -2.61, -2.59, both P<0.05), while the MTV of primary tumors and short diameter and metabolic parameters of positive lymph nodes were not significantly different between those 2 groups ( t=-1.50, Z values: -1.09 to -0.75, all P>0.05). No significant relation was found between PET/CT parameters and pathological differentiation or Lauren classification, or other pathological features ( t values: -1.55 to 1.38, Z values: -1.84 to 0, F values: 0.12-2.43, H values: 0.13-0.98, all P>0.05). ROC curve showed that the cut-off value of SUV max for predicting postoperative TRG was 5.40, and the AUC reached 0.77 (95% CI: 0.56-0.91), with the sensitivity and specificity of 9/16, 9/9, respectively. With TBR=3.54 as the cut-off value, its AUC reached 0.77 (95% CI: 0.56-0.91), and the sensitivity and specificity were 11/16, 8/9, respectively. The sensitivity and specificity of PET/CT for predicting lymph node positivity of patients were 8/12 and 13/13, respectively. Conclusion:Interim 18F-FDG PET/CT metabolic parameters can accurately predict the pathological response of LAGC patients after NICT.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

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 study the impact of fluoride exposure through drinking water on the risk of hypertension among residents in Jishan County, Shanxi Province.Methods:From March to April 2023, a cluster sampling method was used to select permanent residents aged ≥18 years and residing for ≥10 years in 12 villages in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province as the survey subjects. A questionnaire survey, physical examination, and morning urinary fluoride level testing were conducted. The least absolute shrinkage and selection operator (Lasso) regression were used to analyze the key influencing factors of hypertension. Restricted cubic spline was used to evaluate the linear relationship between urinary fluoride and hypertension. Logistic regression was used to analyze the impact of urinary fluoride on hypertension.Results:Finally, 2 453 survey subjects were included, aged (62 ± 10) years, including 1 565 patients (63.80%) with hypertension. There were significant differences in the distribution of age, gender, education level, annual household income, body mass index (BMI), and the level and distribution of urinary fluoride between hypertension group and normal blood pressure group ( P < 0.05). The Lasso regression results showed that age, education level, BMI, and urinary fluoride were the key influencing factors of hypertension, with coefficients of 1.04, - 0.12, 0.24 and 0.01, respectively. The results of the restricted cubic spline showed that there was a linear relationship between urinary fluoride and hypertension after adjusting for age, education level, and BMI ( Poverall = 0.018, Pnonlinear = 0.482). The logistic regression results showed that after adjusting for age, education level, and BMI, urinary fluoride > 4.68 mg/L was a risk factor for hypertension ( OR = 1.42, 95% CI: 1.10 - 1.84, P = 0.007). Conclusion:High urinary fluoride is a risk factor for hypertension in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province.

Objective To analyze the mortality and its changing trend, and composition and order of causes of death of residents in Mengzi City, and to provide a basis for further disease prevention and control. Methods The death causes surveillance data from 2018 to 2021 were derived from the all-cause-of-death surveillance system in Mengzi City. A retrospective analysis was performed on the mortality rate, life expectancy, life expectancy eliminating causes of death, and life loss. The annual percentage change (APC) was analyzed by the Joinpoint regression model to describe changes in mortality trends. Results The overall crude mortality rate was 633.88/100,000. The age-adjusted mortality was 866.87/100,000. There was a significant downward trend in the crude and standardized mortality (APC=-1.73% , APC=-5.96% , P<0.05). Deaths due to chronic non-communicable diseases (NCDs) accounted for 76.44% of the total deaths. The top 5 causes of death of the residents were cerebrovascular diseases (140.38/100 000), heart diseases (104.24/100 000), malignant neoplasms (92.75/100 000), injuries (79.37/100 000), and respiratory diseases (63.17/100 000) in order, accounting for 75.71% of all causes of death. Life expectancy was 75.67 years, 72.32 years and 79.49 years in the whole-population, males and females, respectively. The potential life expectancy loss due to injury, malignant tumor and cerebrovascular disease accounted for 65.45% of all causes of death. Conclusion Chronic non-communicable diseases are the focus of prevention and control work in Mengzi City. Particular attention should be paid to the damage to health and loss of life caused by injuries, malignancies and cerebrovascular diseases.