AIM: To investigate the potential inhibitory effect of pterostilbene on the endothelial-to-mesenchymal transition(EndMT)induced by high glucose conditions in human retinal microvascular endothelial cells(HRMECs).METHODS: The optimal concentration of pterostilbene for treating HRMECs was determined using the CCK-8 assay, with 12.5 and 25 μmol/L concentrations selected for subsequent experiments. Four experimental groups were established: control group, high glucose group, high glucose combined with 12.5 μmol/L pterostilbene treatment group, and high glucose combined with 25 μmol/L pterostilbene treatment group. The expression levels of HDAC7 and EndMT-associated markers were detected via Western blot analysis. Cell migration ability was assessed using Transwell migration assays and scratch wound healing tests, while vasculogenic capability was evaluated through tube formation assays.RESULTS: The CCK-8 assay revealed that pterostilbene at a concentration of 22.07 μmol/L inhibited 50% of cell viability in HRMECs. Western blot analysis demonstrated that compared with the control group, the expression levels of HDAC7, ZEB1, Vimentin, and Snail were significantly upregulated in HRMECs cultured in high glucose(all P<0.01), while the expressions of VE-cadherin and CD31 were significantly reduced(all P<0.01). Compared to the high glucose group, the treatment with 12.5 and 25 μmol/L pterostilbene significantly reduced the expression of HDAC7, ZEB1, Vimentin, and Snail under high glucose conditions(all P<0.01). Notably, 25 μmol/L pterostilbene enhanced the expression of VE-cadherin and CD31(all P<0.01). Scratch wound healing tests revealed that HRMECs treated with high glucose exhibited a significantly increased cell migration rate compared to the control group(P<0.05), while the application of 25 μmol/L pterostilbene significantly suppressed HRMECs migration under high glucose conditions(P<0.01). Transwell migration assays demonstrated that the cell migration rate in the high glucose group was significantly higher than that in the control group(P<0.01), with cell migration rate markedly reduced following treatment with both of 12.5 and 25 μmol/L pterostilbene(all P<0.01). The tube formation assay revealed that the ability of HRMECs to form tubular structures was significantly enhanced under high glucose conditions(P<0.01), and both 12.5 and 25 μmol/L of pterostilbene effectively inhibited this effect(all P<0.01).CONCLUSION: Pterostilbene can inhibit HDAC7 expression, suppress EndMT-mediated migration of HRMECs, and impair tube formation under high-glucose conditions.

AIM: To investigate the potential inhibitory effect of pterostilbene on the endothelial-to-mesenchymal transition(EndMT)induced by high glucose conditions in human retinal microvascular endothelial cells(HRMECs).METHODS: The optimal concentration of pterostilbene for treating HRMECs was determined using the CCK-8 assay, with 12.5 and 25 μmol/L concentrations selected for subsequent experiments. Four experimental groups were established: control group, high glucose group, high glucose combined with 12.5 μmol/L pterostilbene treatment group, and high glucose combined with 25 μmol/L pterostilbene treatment group. The expression levels of HDAC7 and EndMT-associated markers were detected via Western blot analysis. Cell migration ability was assessed using Transwell migration assays and scratch wound healing tests, while vasculogenic capability was evaluated through tube formation assays.RESULTS: The CCK-8 assay revealed that pterostilbene at a concentration of 22.07 μmol/L inhibited 50% of cell viability in HRMECs. Western blot analysis demonstrated that compared with the control group, the expression levels of HDAC7, ZEB1, Vimentin, and Snail were significantly upregulated in HRMECs cultured in high glucose(all P<0.01), while the expressions of VE-cadherin and CD31 were significantly reduced(all P<0.01). Compared to the high glucose group, the treatment with 12.5 and 25 μmol/L pterostilbene significantly reduced the expression of HDAC7, ZEB1, Vimentin, and Snail under high glucose conditions(all P<0.01). Notably, 25 μmol/L pterostilbene enhanced the expression of VE-cadherin and CD31(all P<0.01). Scratch wound healing tests revealed that HRMECs treated with high glucose exhibited a significantly increased cell migration rate compared to the control group(P<0.05), while the application of 25 μmol/L pterostilbene significantly suppressed HRMECs migration under high glucose conditions(P<0.01). Transwell migration assays demonstrated that the cell migration rate in the high glucose group was significantly higher than that in the control group(P<0.01), with cell migration rate markedly reduced following treatment with both of 12.5 and 25 μmol/L pterostilbene(all P<0.01). The tube formation assay revealed that the ability of HRMECs to form tubular structures was significantly enhanced under high glucose conditions(P<0.01), and both 12.5 and 25 μmol/L of pterostilbene effectively inhibited this effect(all P<0.01).CONCLUSION: Pterostilbene can inhibit HDAC7 expression, suppress EndMT-mediated migration of HRMECs, and impair tube formation under high-glucose conditions.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective:To find out factors influencing the compliance of supportive treatment of patients with periodontitis who have received implant restoration therapy.Methods:Patients who had completed periodontal and implant restoration treatment for more than 5 years in Department of Periodontology,Pe-king University Hospital of Stomatology were subjected to inclusion between March 2022 and August 2023.A questionnaire was compiled to gather the information including patients'basic information(gen-der,age,and educational background etc.),smoking habits,general health conditions,oral hygiene habits,willingness to undertake periodontal and dental implant supportive treatment,actual fact on sup-portive treatment recorded in medical records,whether medical advices were correctly remembered,and reasons affected them to implement supportive therapy.The questionnaires were handed out to the above patients and filled during the process of follow-up treatment.Chi-square test,univariate and multivariate analysis of Logistic regression were employed to explore the correlations of these factors and the patients'compliance.Results:In the study,92 patients and questionnaires were collected and analyzed.The re-sults indicated that oral hygiene habits and whether medical advices were correctly remembered had sig-nificant correlation with compliance(P＜0.05).Time constraint(47.0％)and difficulty in appointment registration(24.8％)were the top 2 reasons obstructed them to undertake supportive treatment.Al-though the vast majority of the patients indicated willingness to perform follow-ups,55.4％of them wouldn't come back until the dentist called them back.The results of our study also indicated that the patients placed significantly less importance on the health of natural teeth than implants.Conclusion:In order to improve the compliance of supportive treatment,we suggest that dentists should put more empha-sis on oral hygiene instruction,and knowledge regarding periodontitis should also be added as part of pa-tient education contents.In the early stages of treatment,the patient should develop the habit of regular follow-up checks,More attention and patience should be given to elderly patients and those with lower level of education;use language that is easy to understand and printed medical instructions to help them remember.Patients can memorize better from refined doctors'advice,reinforcing care knowledge and refining medical advices can promote better follow-up treatment results.Motivating patients based on their characteristics is critical to improving compliance.

Objective:To investigate the recognition of the post competency index system among rural general practice assistant physicians and its influencing factors.Methods:This study was a cross-sectional survey. A questionnaire survey on the recognition of post competency index system was conducted from October 2020 to September 2021 among rural general practice assistant physicians from 10 provinces/municipalities selected by stratified cluster sampling method. The recognition of rural general practice assistant physicians at all levels of indexs and the factors influencing recognition were analyzed.Results:A total of 1 123 questionnaires were distributed and 1 024 valid ones were collected with a recovery rate of 91.18%. Of the 1 024 respondents, 529 were male(51.7%) and 435 were aged 40-49 years(42.5%), which was the highest proportion by age group. The average overall recognition score of the index system was 4.41, and the scores of the primary indexes were 4.32-4.45. Three primary indexes had the highest recognition scores: professional competence, basic health care services, and interpersonal communication and teamwork. The recognition scores on the second level index were 4.18-4.61, and the proportion of recognition scores greater than 4 was over 80%. There were significant differences in the recognition scores of the index system among assistant physicians with different working years, educational background, professional title and work unit ( F/H=6.41, 14.83, 12.45, 7.53, P<0.01). Educational background(associate degree: B=0.091, P=0.015; bachelor degree and above: B=0.196, P<0.001) and professional title(intermediate professional title and above: B=-0.234, P<0.001) were the independent factors influencing the recognition degree of the index system for rural general practice assistant physicians. Conclusions:The post competency index system is generally recognized by rural general practice assistant physician, and academic qualifications and professional title status may influence its recognition.

Objective:To evaluate the application feasibility of the post competency index system of rural general practice assistant physicians, and to analyze and compare the post competency of rural general practice assistant physicians with different characteristics through a survey among rural general practice assistant physicians in China.Methods:This study was a cross-sectional study. A questionnaire survey was conducted among rural general practice assistant physicians in 10 provinces/municipalities selected by stratified cluster sampling method from October 2020 to September 2021. The post competency scores were self-evaluated based on the post competency index system of rural general practice assistant physicians. The results of the survey were analyzed and the application feasibility of the index system was evaluated.Results:A total of 1 123 questionnaires were distributed and 1 024 valid questionnaires were returned with a recovery rate of 91.2%. Of the 1 024 respondents, 529 were males (51.7%), 435 were aged 40-49 years (42.5%), 434 had a secondary school education or less (42.4%), and 531 were junior practitioners (51.9%). The Cronbach′s α coefficient of the overall questionnaire was 0.987, and the Cronbach′s α coefficient of the first level index ranged from 0.897 to 0.974. The cumulative variance contribution rate of exploratory factor analysis was 72.012%. The confirmatory factor analysis showed χ2/ df=3.926, RMSEA=0.076, CFI=0.858, IFI=0.859, indicating that the model fit was basically good. The average self-evaluation scores of the first level index ranged from 3.95 to 4.25, and the average self-evaluation scores of the second level index ranged from 3.74 to 4.36. There were significant differences in self-evaluation scores of post competency among rural general practice assistant physicians with different working years, professional titles, working units and economic regions( F=4.67, 10.54, 22.16 and 20.90,all P<0.05). People with low self-evaluation scores of post competency had the following characteristics: working 10-19 years, intermediate or above titles, working in community health service centers, located in the eastern region.People with high self-evaluation scores of post competency had the following characteristics: primary professional title, working in the village clinic. Conclusion:The competency index system of rural general practice assistant physicians has good application feasibility,and it can be used to evaluate post competency for the education and training of rural general practice assistant physicians.