Objective:To explore the predictive efficacy of the HFA-ICOS score for cancer therapy-related cardiac dysfunction (CTRCD) in Chinese patients with breast cancer and lymphoma.Methods:This study was a single-center retrospective cohort study which included patients with breast cancer and lymphoma who were treated with anthracyclines from February 2018 to February 2025 at the First Affiliated Hospital of Dalian Medical University. Patients were evaluated at baseline with cardiac biomarkers and echocardiography, including left ventricular ejection fraction and global longitudinal strain of the left ventricle. After anthracycline therapy, they were followed up at 1, 3, 6, and 12 months. Data involved biomarkers and echocardiography were collected to determine whether CTRCD had occurred. The patients were categorized into low-risk, intermediate-risk, high-risk, and very-high-risk groups using the HFA-ICOS scoring model. The cumulative probability of CTRCD under different HFA-ICOS risk stratification was analyzed using Kaplan-Meier survival curves. The effect of HFA-ICOS risk stratification on CTRCD was assessed using an univariate Cox proportional hazards regression model. The predictive efficacy of the HFA-ICOS model and its utility in clinical decision-making were assessed with receiver operating characteristic (ROC) curves, calibration curves, and decision curves at each time point.Results:A total of 286 patients, aged 55 (44, 61) years, were enrolled, of whom 33 (11.5%) cases were male. And 113 (39.5%) patients developed CTRCD during a median follow-up time of 111 (70, 210) days. HFA-ICOS risk stratification showed that 228 (79.7%) were low-risk, 49 (17.1%) were intermediate-risk, and a total of 9 (3.1%) were high-risk and very high-risk. The difference in the occurrence of CTRCD over time between patients with different HFA-ICOS risk stratification was statistically significant ( Plog-rank<0.001). Cox proportional regression hazards analysis showed an increased risk of CTRCD development in intermediate-risk ( HR=1.95, 95% CI 1.22-3.00, P=0.006) and high-risk and very high-risk patients ( HR=4.12, 95% CI 1.66-8.54, P=0.004) compared with low-risk patients. The ROC curves showed that the area under the curve of the HFA-ICOS model predicting CTRCD was 0.532, 0.597, 0.600 and 0.577 at 1, 3, 6 and 12 months, respectively. The calibration curves indicated Brier scores of 0.041 (95% CI 0.013-0.067), 0.144 (95% CI 0.115-0.173), 0.232 (95% CI 0.215-0.249) and 0.236 (95% CI 0.220-0.251) at 1, 3, 6 and 12 months, correspondingly. The clinical decision curve suggested that clinical intervention may have a net benefit when the risk threshold is between 0.15 and 0.18 at 1 month, between 0.10 and 0.50 at 3 months, and between 0.30 and 0.70 at 6 and 12 months. Conclusion:The HFA-ICOS score could predict the occurrence of CTRCD in patients with breast cancer and lymphoma treated with anthracycline drugs, although its predictive efficacy is limited, and the prediction model requires further validation in a larger population.

Animal experiments are crucial in evaluating the preclinical safety and efficacy of new dental materials, drugs, instruments, and equipment by identifying and eliminating potential health risks to humans. An international team of several dental experts formulated a guideline named Preferred Reporting Items for Animal Studiesin Endodontology (PRIASE) 2021. Consisting of 11 domains, 43 individual items, and a flowchart. PRIASE provides guidance for animal experiments in dentistry and improves the quality of experiment design and reporting. This work introduces the process and basic content of the guideline and interprets the key items of its checklist with specific examples to provide reference for the reporting of animal experiment in dentistry in China.
Animals ; Animal Experimentation/standards* ; Checklist ; China ; Endodontics ; Guidelines as Topic ; Research Design

With the expansion of cross-regional medical services in China, the supervision of medical insurance funds is facing systemic challenges including insufficient inter-regional coordination and ambiguous multi-stakeholder responsibilities, necessitating the establishment of a collaborative regulatory framework tailored to China′s governance context. The authors constructed a revised " 4+ 1" collaborative regulatory model by integrating complex regulatory network spatial theory with the collaborative governance SFIC model, which included incorporating initial conditions, intervention leadership, institutional design, collaborative processes, and outcome feedback. The research systematically deconstructed China′s medical insurance fund regulatory practices, found reveal persistent challenges in the current collaborative regulatory system, including institutional friction among stakeholders, blocked cross-regional rule transmission, and insufficient dynamic feedback mechanisms, which collectively contributed to policy implementation deviations and diminished regional coordination efficacy. The authors proposed specific optimization paths, including innovating three-dimensional driven institutional supply, restructuring rights and responsibilities to assist collaborative leadership, implementing dynamic negotiation driven effective collaboration, and constructing a feedback loop through dual dimensional coupling.

Chronic hepatitis B(CHB)is the main cause of hepatocellular carcinoma(HCC).Early prediction and diagnosis of HCC in CHB patients can further reduce the onset risk of HCC and improve patient prognosis.Scholars at home and abroad have proposed a number of HCC risk prediction models for CHB patients,and these models have achieved new development and opti-mization in the era of antiviral therapy.Due to differences in research backgrounds,these models vary in the use of antiviral drugs,included variables(such as host factors,viral activity,cirrhosis status,etc.)and application scenarios.At the same time,the application of artificial intelligence and liquid biopsy technology in risk prediction models has become a new research highlight.This paper aims to compare the HCC risk prediction models reported so far for CHB patients,clarify the characteristics of each model,explore appropriate HCC risk prediction methods,and provide reference for the risk prediction of hepatitis B virus related HCC.

Objective:To investigate the characteristics and determinants of total scores of cerebral small vessel disease (CSVD) and to analyze the factors associated with enlarged perivascular space (EPVS) grading in pilots.Methods:The physical examination data of 72 pilots who were hospitalized and diagnosed with CSVD by MRI in the Air Force Medical Center (General Hospital of Air Force) between 2019 and 2022 was retrospectively analyzed. The pilots were grouped by the total CSVD score (0, 1, 2, 3, 4 points), and the distribution of CSVD imaging biomarkers was compared across groups. The severity of EPVS was classified into 3 levels: none or mild (0-10), moderate (11-20), and severe (>20). The impact of vascular risk factors on the total CSVD score and EPVS grading was analyzed.Results:The results of the total CSVD score showed that there were 19 cases (26.39%) with a score of 0, 43 cases (59.72%) with a score of 1, 10 cases (13.89%) with a score of 2, and 0 case with scores of 3 or 4. Among those who scored 1, there were 2 cases (4.65%) of lacunar infarction (LA), 1 case (2.33%) of moderate to severe white matter hyperintensity (WMH), 2 cases (4.65%) of cerebral microbleed (CMB), and 38 cases (88.37%) of moderate and severe EPVS. Among those who scored 2, there were 7 cases (70.00%) of LA combined with EPVS, 2 cases (20.00%) of CMB combined with EPVS, and 1 case (10.00%) of WMH combined with EPVS. According to the CSVD imaging classification of these pilots, there were 9 cases (12.50%) of LA, 52 cases (72.22%) of WMH, 4 cases (5.60%) of CMB and 61 cases (84.72%) of EPVS. Multiple ordered Logistic regression analysis showed that systolic blood pressure ( OR=1.068, 95% CI: 1.016-1.122) and high-density lipoprotein cholesterol ( OR=0.111, 95% CI: 0.015-0.843) made a difference in the total CSVD score. High-density lipoprotein cholesterol ( OR=0.166, 95% CI: 0.031-0.893) could affect the EPVS grading. Spearman′s correlation analysis showed that the systolic blood pressure level was positively correlated with the total CSVD score ( r=0.299, P=0.011), while the high-density lipoprotein cholesterol level was negatively correlated with the total CSVD score and EPVS grading ( r=-0.313, -0.263, P=0.041, 0.026). Conclusions:The total CSVD score of pilots is at a mild level with EPVS as the leading contributor. The systolic blood pressure and the high-density lipoprotein cholesterol level are determinants for the total CSVD score, while the high-density lipoprotein cholesterol level is a determinant for the EPVS grading of pilots. Blood pressure control and lipid regulation can go a long way towards preventing CSVD in pilots. The total CSVD score is of value for stratified evaluation and individual identification of pilots with CSVD.

Chronic hepatitis B(CHB)is the main cause of hepatocellular carcinoma(HCC).Early prediction and diagnosis of HCC in CHB patients can further reduce the onset risk of HCC and improve patient prognosis.Scholars at home and abroad have proposed a number of HCC risk prediction models for CHB patients,and these models have achieved new development and opti-mization in the era of antiviral therapy.Due to differences in research backgrounds,these models vary in the use of antiviral drugs,included variables(such as host factors,viral activity,cirrhosis status,etc.)and application scenarios.At the same time,the application of artificial intelligence and liquid biopsy technology in risk prediction models has become a new research highlight.This paper aims to compare the HCC risk prediction models reported so far for CHB patients,clarify the characteristics of each model,explore appropriate HCC risk prediction methods,and provide reference for the risk prediction of hepatitis B virus related HCC.

With the expansion of cross-regional medical services in China, the supervision of medical insurance funds is facing systemic challenges including insufficient inter-regional coordination and ambiguous multi-stakeholder responsibilities, necessitating the establishment of a collaborative regulatory framework tailored to China′s governance context. The authors constructed a revised " 4+ 1" collaborative regulatory model by integrating complex regulatory network spatial theory with the collaborative governance SFIC model, which included incorporating initial conditions, intervention leadership, institutional design, collaborative processes, and outcome feedback. The research systematically deconstructed China′s medical insurance fund regulatory practices, found reveal persistent challenges in the current collaborative regulatory system, including institutional friction among stakeholders, blocked cross-regional rule transmission, and insufficient dynamic feedback mechanisms, which collectively contributed to policy implementation deviations and diminished regional coordination efficacy. The authors proposed specific optimization paths, including innovating three-dimensional driven institutional supply, restructuring rights and responsibilities to assist collaborative leadership, implementing dynamic negotiation driven effective collaboration, and constructing a feedback loop through dual dimensional coupling.

Objective:To investigate the characteristics and determinants of total scores of cerebral small vessel disease (CSVD) and to analyze the factors associated with enlarged perivascular space (EPVS) grading in pilots.Methods:The physical examination data of 72 pilots who were hospitalized and diagnosed with CSVD by MRI in the Air Force Medical Center (General Hospital of Air Force) between 2019 and 2022 was retrospectively analyzed. The pilots were grouped by the total CSVD score (0, 1, 2, 3, 4 points), and the distribution of CSVD imaging biomarkers was compared across groups. The severity of EPVS was classified into 3 levels: none or mild (0-10), moderate (11-20), and severe (>20). The impact of vascular risk factors on the total CSVD score and EPVS grading was analyzed.Results:The results of the total CSVD score showed that there were 19 cases (26.39%) with a score of 0, 43 cases (59.72%) with a score of 1, 10 cases (13.89%) with a score of 2, and 0 case with scores of 3 or 4. Among those who scored 1, there were 2 cases (4.65%) of lacunar infarction (LA), 1 case (2.33%) of moderate to severe white matter hyperintensity (WMH), 2 cases (4.65%) of cerebral microbleed (CMB), and 38 cases (88.37%) of moderate and severe EPVS. Among those who scored 2, there were 7 cases (70.00%) of LA combined with EPVS, 2 cases (20.00%) of CMB combined with EPVS, and 1 case (10.00%) of WMH combined with EPVS. According to the CSVD imaging classification of these pilots, there were 9 cases (12.50%) of LA, 52 cases (72.22%) of WMH, 4 cases (5.60%) of CMB and 61 cases (84.72%) of EPVS. Multiple ordered Logistic regression analysis showed that systolic blood pressure ( OR=1.068, 95% CI: 1.016-1.122) and high-density lipoprotein cholesterol ( OR=0.111, 95% CI: 0.015-0.843) made a difference in the total CSVD score. High-density lipoprotein cholesterol ( OR=0.166, 95% CI: 0.031-0.893) could affect the EPVS grading. Spearman′s correlation analysis showed that the systolic blood pressure level was positively correlated with the total CSVD score ( r=0.299, P=0.011), while the high-density lipoprotein cholesterol level was negatively correlated with the total CSVD score and EPVS grading ( r=-0.313, -0.263, P=0.041, 0.026). Conclusions:The total CSVD score of pilots is at a mild level with EPVS as the leading contributor. The systolic blood pressure and the high-density lipoprotein cholesterol level are determinants for the total CSVD score, while the high-density lipoprotein cholesterol level is a determinant for the EPVS grading of pilots. Blood pressure control and lipid regulation can go a long way towards preventing CSVD in pilots. The total CSVD score is of value for stratified evaluation and individual identification of pilots with CSVD.

Objective:To explore the predictive efficacy of the HFA-ICOS score for cancer therapy-related cardiac dysfunction (CTRCD) in Chinese patients with breast cancer and lymphoma.Methods:This study was a single-center retrospective cohort study which included patients with breast cancer and lymphoma who were treated with anthracyclines from February 2018 to February 2025 at the First Affiliated Hospital of Dalian Medical University. Patients were evaluated at baseline with cardiac biomarkers and echocardiography, including left ventricular ejection fraction and global longitudinal strain of the left ventricle. After anthracycline therapy, they were followed up at 1, 3, 6, and 12 months. Data involved biomarkers and echocardiography were collected to determine whether CTRCD had occurred. The patients were categorized into low-risk, intermediate-risk, high-risk, and very-high-risk groups using the HFA-ICOS scoring model. The cumulative probability of CTRCD under different HFA-ICOS risk stratification was analyzed using Kaplan-Meier survival curves. The effect of HFA-ICOS risk stratification on CTRCD was assessed using an univariate Cox proportional hazards regression model. The predictive efficacy of the HFA-ICOS model and its utility in clinical decision-making were assessed with receiver operating characteristic (ROC) curves, calibration curves, and decision curves at each time point.Results:A total of 286 patients, aged 55 (44, 61) years, were enrolled, of whom 33 (11.5%) cases were male. And 113 (39.5%) patients developed CTRCD during a median follow-up time of 111 (70, 210) days. HFA-ICOS risk stratification showed that 228 (79.7%) were low-risk, 49 (17.1%) were intermediate-risk, and a total of 9 (3.1%) were high-risk and very high-risk. The difference in the occurrence of CTRCD over time between patients with different HFA-ICOS risk stratification was statistically significant ( Plog-rank<0.001). Cox proportional regression hazards analysis showed an increased risk of CTRCD development in intermediate-risk ( HR=1.95, 95% CI 1.22-3.00, P=0.006) and high-risk and very high-risk patients ( HR=4.12, 95% CI 1.66-8.54, P=0.004) compared with low-risk patients. The ROC curves showed that the area under the curve of the HFA-ICOS model predicting CTRCD was 0.532, 0.597, 0.600 and 0.577 at 1, 3, 6 and 12 months, respectively. The calibration curves indicated Brier scores of 0.041 (95% CI 0.013-0.067), 0.144 (95% CI 0.115-0.173), 0.232 (95% CI 0.215-0.249) and 0.236 (95% CI 0.220-0.251) at 1, 3, 6 and 12 months, correspondingly. The clinical decision curve suggested that clinical intervention may have a net benefit when the risk threshold is between 0.15 and 0.18 at 1 month, between 0.10 and 0.50 at 3 months, and between 0.30 and 0.70 at 6 and 12 months. Conclusion:The HFA-ICOS score could predict the occurrence of CTRCD in patients with breast cancer and lymphoma treated with anthracycline drugs, although its predictive efficacy is limited, and the prediction model requires further validation in a larger population.

By reviewing ancient materia medica， medical and prescription books， combined with modern literature， the textual research of Stephaniae Tetrandrae Radix has been conducted to verify the name， origin， producing area， harvesting and processing methods. Through textual research， the results show that the mainstream name of this herb recorded in the past dynasties is Fangji， which is also called Hanzhong Fangji because it is produced in Hanzhong city， and after the Tang dynasty， it was gradually divided into Hanfangji and Mufangji， and there is the saying that Han Zhushuiqi， Mu Zhufengqi. The names of Fenfangji and Guangfangji were first seen in the republic of China. In addition， Fenfangji was once distributed in Hankou， so it was also known as "Hanfangji"， which is easily confused with the traditional Hanzhong Fangji for short. Based on the original research， it is concluded that Aristolochia heterophylla（Hanzhong Fangji）is the mainstream of Stephaniae Tetrandrae Radix used in the Qing dynasty and before， and the application history of Cocculus orbiculatus can be traced back to before the Tang dynasty. After the Ming dynasty， Stephania tetrandra gradually became another main origin， and in the Republic of China， A. fangchi was used as a medicine for Stephaniae Tetrandrae Radix， but in modern times it was banned because it contained aristolochic acid as a toxic ingredient， and S. tetrandra has become the mainstream legal origin. The traditional production area of Hanzhong Fangji is Hanzhong， Shaanxi province， while today the mainstream of S. tetrandra is manly produced in Jiangxi and other places. Based on the quality evaluation research， the quality of Hanzhong Fangji is better with the radial texture of section used as radial solution， yellow solid and fragrant. Fenfangji with solid quality， white inside， powdered enough， less fiber and radiating texture is better. From the harvesting and processing research， the root of Fangji is mostly harvested in spring and autumn， and the outer bark should be removed in some literature. Before the Ming dynasty， this herb was dried in the shade， and after the Ming dynasty， it was dried in the sun. The modern production processing of Fangji is to harvest it in autumn， wash it， remove the rough bark， dry it to half dry， cut it into sections， and then cut it longitudinally if it is large， and dry it. Based on the results， combined with current studies on the toxicity of aristolochic acid and influencing factors such as commercial circulation， it is suggested that S. tetrandra should be used as the origin of Fangji， the processed products are selected according to the prescription requirements， and those without specified requirements can be processed by referring to the raw products in the 2020 edition of Chinese Pharmacopoeia.