Wilson disease （WD） is a hereditary disorder of copper metabolism characterized by abnormal copper accumulation in tissues， including the liver and brain， which leads to severe hepatic and neurological damage. This disease is often accompanied by lipid metabolism abnormalities， and the exploration of related mechanisms has attracted increasing attention. This article introduces the clinical features of lipid metabolism disorders in WD patients， summarizes the research advances in the serum levels of lipids and hepatic steatosis， analyzes the potential mechanisms of the interaction between copper and lipid metabolism， and highlights the significance of lipid-related molecules in disease diagnosis and clinical evaluation. In clinical practice， the monitoring and assessment of lipid metabolism parameters should be taken seriously in patients with WD， in order to promote comprehensive disease management and improve the prognosis of patients.

ObjectiveTo investigate the effect of Zishen Huoxue Formula （ZSXHF） on molecular-targeted therapy-associated proteinuria in patients with primary liver cancer （PLC）， to assess the efficacy of ZSXHF in the treatment of molecular-targeted therapy-associated proteinuria， and to provide a basis for clinical medication. MethodsA retrospective cohort study was conducted among the PLC patients with molecular-targeted therapy-associated proteinuria who were diagnosed and treated in The Department of Hepatology of Chinese PLA General Hospital， from January 1， 2022 to July 1， 2025. With ZSXHF treatment as the exposure factor， the patients with a cumulative treatment duration of ≥9 weeks were enrolled as traditional Chinese medicine （TCM） group， while those without TCM treatment were enrolled as control group. Propensity score matching was performed for the two groups at a ratio of 1∶1 based on sex， age， 24-hour urinary protein， blood urea nitrogen， and serum creatinine. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between groups. Univariate and multivariate Logistic regression analyses were used to investigate the influencing factors for promoting the improvement of targeted-therapy-associated proteinuria. ResultsA total of 137 PLC patients with targeted-therapy-associated proteinuria were enrolled， with 34 patients in the TCM group and 103 in the control group. After follow-up for 6 months， the TCM group had a significant improvement in urinary protein grade compared with the control group （χ²=9.261， P=0.016）. There were 25 patients in each group after propensity score matching， and after follow-up for 6 months， there were significant differences between the two groups in urinary protein grade （χ²=15.689， P<0.001） and 24-hour urinary protein （Z=-3.075， P=0.002）. After cumulative treatment with ZSXHF for ≥9 weeks， the TCM group had a significantly greater change in 24-hour urinary protein from baseline compared with the control group （t=-2.514， P=0.016）， while there were no significant differences in the changes in liver and renal function after ZSXHF intervention between the two groups （all P>0.05）. The multivariate Logistic regression analysis showed that ZSXHF treatment （odds ratio=2.901， 95% confidence interval： 1.135 — 7.417， P=0.026） was an independent influencing factor for improvement in molecular-targeted therapy-associated proteinuria. ConclusionZSHXF can effectively alleviate molecular-targeted therapy-associated proteinuria in PLC patients with a favorable safety profile， which provides a new reference for TCM prevention and treatment of molecular-targeted therapy-associated adverse reactions in PLC patients.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective:To explore the relationship between the dark triad, fear of missing out and smartphone addiction, as well as the mediating role of fear of missing out between the dark triad and smartphone addiction.Methods:A total of 408 college students were assessed using dirty dozen, fear of missing out scale, and mobile phone addiction index. SPSS 24.0 software was used for common method bias tests, descriptive statistical analysis, and correlation analysis. Mplus 8.3 software was employed to construct a structural equation model, and the Bootstrap method was used for mediation effect analysis.Results:The dark triad (36.14±9.06) was positively correlated with fear of missing out (22.55±6.60) and smartphone addiction (46.77±13.62) ( r=0.48, 0.45, both P<0.01). Fear of missing out was also positively correlated with smartphone addiction ( r=0.54, P<0.01). Fear of missing out played a partial mediating role in the relationship between the dark triad and smartphone addiction, with a total effect value of 0.495 and a mediating effect value of 0.217. Conclusion:Fear of missing out partially mediates the relationship between the dark triad and smartphone addiction. The dark triad not only directly predicts smartphone addiction but also indirectly influences smartphone addiction through fear of missing out.

Objective:To examine the association among childhood emotional neglect, thwarted belongingness, perceived burdensomeness, and depression in junior high school students.Methods:From October to December 2024, a total of 314 junior high school students were recruited in Dongying City, Shandong Province. The Chinese versions of the childhood trauma questionnaire-short form (CTQ-SF), the center for epidemiologic studies depression scale (CES-D), and the interpersonal needs questionnaire (INQ) were administered for investigation. SPSS 27.0 software was used for common-method bias test, descriptive analysis, difference test, and correlation analysis. Mplus 8.3 software was employed to build a structural equation model, and the Bootstrap method was adopted for mediation analysis.Results:The scores of depression, childhood emotional neglect, thwarted belongingness, and perceived burdensomeness in junior high school students were 14.00 (9.00, 24.00), 9.00 (5.00, 12.00), 13.00 (8.00, 18.00) and 8.00 (6.00, 19.25), respectively. All variables were positively correlated with one another ( r=0.33-0.51, P<0.01). The total effect of childhood emotional neglect on depression was 0.493 (95% CI=0.396-0.591). The direct effect was 0.126 (95% CI=0.013-0.240), accounting for 25.56%(0.126/0.493) of the total effect. The total indirect effect was 0.367 (95% CI=0.287-0.447), accounting for 74.44%(0.367/0.493) of the total effect. Specifically, the pathway " childhood emotional neglect → thwarted belongingness→ depression" yielded an effect of 0.109, and the pathway " childhood emotional neglect → perceived burdensomeness → depression" yielded an effect of 0.258. Conclusion:Thwarted belongingness and perceived burdensomeness play parallel mediating effects between childhood emotional neglect and depression in junior high school students.

Objective:To explore the relationship between insomnia, depression, sense of meaning in life and suicidal behavior among college students.Methods:A cross-sectional survey was conducted among 7 260 college students at a university in Hebei Province from September to November 2024. The insomnia severity index (ISI), patient health questionnaire(PHQ-9), meaning in life questionnaire(MLQ), and suicide behavior questionnaire-revised (SBQ-R) were used for assessment. Structural equation modeling test was conducted by Mplus 8.0 to test the mediating effect of depression and the moderating effect of sense of meaning in life.Results:(1) The scores of insomnia (6.00 (4.00, 8.00)), depression (2.50 (0, 2.00)), and suicidal behavior (4.00 (3.00, 4.00)) were significantly and positively correlated with each other ( r=0.51-0.66, all P<0.01). The sense of meaning in life (47.80 (39.00, 58.00)) was negatively correlated with insomnia, depression, and suicidal behavior ( r=-0.04--0.22, all P<0.01). (2) Insomnia could positively predict suicidal behavior among college students ( β= 0.15, P<0.01). (3) Depression played a partial mediating role between insomnia and suicidal behavior, with a mediating effect value of 0.40 (95% CI= 0.37-0.43), accounting for 72.73%(0.40/0.55) of the total effect. Conclusion:Depression plays a partial mediating role between insomnia and suicidal behavior among college students. The sense of meaning in life can moderate the impact of insomnia on depression and suicidal behavior.

Objective To observe the efficacy and safety of 3 D video-assisted thoracoscopic segmentectomy in patients with stage Ⅰ lung cancer treated with indocyanine green(ICG)fluorescence reverse-staining.Methods A total of 132 patients with stage Ⅰ lung cancer who were admitted from May 2022 to September 2024 all underwent three-dimensional video-assisted thoracoscopic segmental resection of the lung.They were divided into the observation group(63 cases)and the control group(69 cases)according to the method of intersegmental plane exposure.The control group was treated with the modified expansion and collapse method,while the observation group was treated with the ICG fluorescence backstaining method.The surgical conditions,pulmonary function,postoperative pain degree,quality of life and complications of the two groups were compared.Results The postoperative chest tube retention time,surgical time,postoperative hospitalization time,total postoperative thoracic drainage volume,and inter-segmental plane exposure time in the observation group were as follows(2.13±0.37)d,(145.12±25.26)min,(5.21±0.95)d,(261.41±28.57)ml and(9.15±1.73)s,respectively.The data of the control groups were(3.29±0.48)d,(178.31±30.45)min,(6.34±1.36)d,(352.03±36.74)ml and(1 651.28±179.84)s,respectively.There was a statistically significant difference between the two groups(P＜0.05).There was no statistically significant difference in the number of intraoperative blood loss and intraoperative lymph node dissections between the two groups(P＞0.05).There was no statistically significant difference in the levels of maximal expiratory flow(PEF),forced expiratory volume in one second(FEV1),and FEV1/forced vital capacity(FVC)between the two groups before the operation and one month after the operation(P＞0.05).The Visual Analogue Scale(VAS)scores of the observation group at 12 hours,48 hours and 72 hours after the operation were(3.25±0.46)points,(2.13±0.35)points and(1.02±0.24)points respectively.The control groups were(4.11±0.59)points,(2.98±0.42)points,and(1.73±0.30)points,respectively.There was a statistically significant difference between the two groups(P＜0.05).There was no statistically significant difference in the scores of negative and positive items between the two groups before the operation and one month after the operation(P＞0.05).There was no statistically significant difference in the total incidence of complications between the two groups(P＞0.05).Conclusion The modified dilatation collapse method and ICG fluorescence reverse staining method have no significant effects on lung function and complications in patients with stage Ⅰ lung cancer,and both can improve the quality of life.Compared with the modified dilatation collapse method,ICG fluorescence reverse staining method can shorten the plane exposure time between segments and the operation time,promote postoperative rehabilitation and alleviate postoperative pain.

Objective To study the hemodynamic characteristics of autologous arteriovenous fistula(AVF)and provide a theoretical basis for reducing its stenosis rate.Methods Bidirectional fluid-structure interaction(FSI)simulations were conducted on a modified AVF model.Flow field and wall shear stress(WSS)distributions in the internal fistula at different periods and angles in a cardiac cycle were analyzed for retrograde flow(confluence)and anterograde flow(shunt)modes in models with varying anastomosis angles.Results Under confluence modes,the WSS＜1 Pa area in the 60° anastomosis angle model was the smallest(7.027 mm2),while the 45°,60°,and 90° models showed no significant differences in eddy current size and intensity.Under shunt modes,the 45° anastomosis angle model had the smallest WSS＜1 Pa area(9.079 mm2),but the 60° model exhibited the lowest eddy current intensity and distribution area.In addition,the difference in the WSS＜1 Pa area between the 60° and 45° models was only 2.661 mm2.Conclusions Under both confluence and shunt flow modes,establishing an AVF with 60° anastomosis angle is conducive to reducing the risk of vascular stenosis in arteriovenous fistula.