Objective To observe the value of fetal MRI in diagnosis of duodenal obstruction(DO).Methods A total of 35 fetuses with suspected DO according to MRI were retrospectively included.The length and the maximum diameter of the dilated duodenum were measured,so as site(categorized in descending order from proximal to distal as descending segment,horizontal segment and ascending duodenum/proximal jejunum)and the degree of obstruction(complete or incomplete)were assessed.Taken findings of labor induction specimen,postnatal neonatal surgery or follow-up data as standards,the positive predictive value(PPV)of MRI for diagnosing fetal DO was calculated,while the correlations of the measured parameters of dilated duodenum and the confirmed obstruction site/degree were analyzed.Results Among 35 fetuses,DO was confirmed in 34 fetuses,yielding an overall PPV of 97.14％(34/35)for MRI.In 34 fetuses with confirmed DO,there were 23 with descending DO(DDO),4 with horizontal DO(HDO)and 7 with ascending DO/proximal jejunum obstruction(ADO/PJO),including 12 with complete DO and 22 with incomplete DO.PPV of MRI for diagnosing DDO,HDO and ADO/PJO was 87.50％(21/24),50.00％(2/4)and 100％(7/7),respectively,for diagnosing complete and incomplete DO was 90.00％(9/10)and 84.00％(21/25),respectively.Both the length and the maximum diameter of fetal proximal dilated duodenum showed on MRI were positively correlated with the actual obstruction site(from proximal to distal)(rs=0.736,P＜0.001;rs=0.424,P=0.011,respectively),but had no significant rank correlation with the degree of obstruction(rs=-0.216,P=0.212;rs=-0.285,P=0.097,respectively).Conclusion Fetal MRI could effectively evaluate the length and the maximum diameter of dilated duodenum hence indicating the level and degree of DO.

Hypercholesterolemia is a significant risk factor for the development of atherosclerosis. 2',3',5'-Tri-O-acetyl-N ⁶-(3-hydroxyphenyl) adenosine (IMM-H007), a novel AMPK agonist, has shown protective effects in metabolic diseases. However, its impact on cholesterol and triglyceride metabolism in hypercholesterolemia remains unclear. In this study, we aimed to elucidate the effects and specific mechanisms by which IMM-H007 regulates cholesterol and triglyceride metabolism. To achieve this goal, we used Apoe ^-/- and Ldlr ^-/- mice to establish a hypercholesterolemia/atherosclerosis model. Additionally, hepatocyte-specific Ampka1/2 knockout mice were subjected to a 5-week high-cholesterol diet to establish hypercholesterolemia, while atherosclerosis was induced via AAV-PCSK9 injection combined with a 16-week high-cholesterol diet. Our results demonstrated that IMM-H007 improved cholesterol and triglyceride metabolism in mice with hypercholesterolemia. Mechanistically, IMM-H007 modulated the AMPKα1/2-LDLR signaling pathway, increasing cholesterol uptake in the liver. Furthermore, IMM-H007 activated the AMPKα1-FXR pathway, promoting the conversion of hepatic cholesterol to bile acids. Additionally, IMM-H007 prevented hepatic steatosis by activating the AMPKα1/2-ATGL pathway. In conclusion, our study suggests that IMM-H007 is a promising therapeutic agent for improving hypercholesterolemia and atherosclerosis through the activation of AMPKα.

Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

AIM:To investigate the therapeutic effect of recombinant human interleukin-37(rhIL-37)inter-vention on extracellular matrix deposition in human bronchial epithelial cells exposed to fine particulate matter(PM2.5),and to explore the underlying mechanisms.METHODS:An airway injury cell model was established using normal human bronchial epithelial 16HBE cells treated with various concentrations(6.25,12.5,25 and 50 mg/L)of PM2.5.Western blot and immunofluorescence were employed to assess the expression level of Wnt family member 5a(Wnt5a).The con-centration of PM2.5 that maximized Wnt5a expression was identified as the optimal concentration for further analysis.The cells were divided into 3 groups,PM2.5+siRNA,PM2.5+Wnt5a siRNA and control+Wnt5a siRNA,to evaluate the expres-sion of fibronectin,the secretion of IL-6 and IL-1β,and the production of reactive oxygen species(ROS).A subsequent set of experiments was organized into PM2.5+rhIL-37,PM2.5 and control groups to determine whether rhIL-37 down-regu-lates the expression of Wnt5a and fibronectin,and reduces the secretion of IL-6 and IL-1β.RESULTS:(1)After 24 h of exposure to various concentrations of PM2.5,the expression of Wnt5a in 16HBE cells was significantly elevated,except at 50 mg/L,compared with control group(P＜0.05).The highest Wnt5a expression was observed at 12.5 mg/L PM2.5(P＜0.01).(2)Fibronectin expression peaked after 24 h of exposure to PM2.5 at 12.5 mg/L(P＜0.01).(3)Successful knock-down of Wnt5a resulted in decreased levels of fibronectin and nuclear factor E2-related factor(Nrf2).Additionally,the production of ROS and the secretion of IL-6 and IL-1β were significantly reduced compared with control group(P＜0.01).(4)The administration of rhIL-37 before PM2.5 exposure led to decreased levels of Wnt5a,fibronectin and Nrf2 compared with PM2.5 group(P＜0.05).Furthermore,rhIL-37 treatment reduced the ROS production and the secretion of IL-6 and IL-1β(P＜0.05).CONCLUSION:In vitro cell models demonstrate that PM2.5 can induce extracellular matrix deposition in bronchial epithelial cells,potentially through the modulation of inflammatory response and oxidative stress influenced by Wnt5a.Additionally,rhIL-37 appears to mitigate inflammatory response and oxidative stress by down-regulating Wnt5a.

Objective:To explore the application effect of high-fidelity intelligent simulator combined with scenario simulation for emergency response training in the Department of Radiology, and to improve the emergency preparedness of medical, nursing, and technical staff in managing contrast agent adverse reactions.Methods:From January to July 2024, 132 medical, nursing, and technical staff from the Department of Radiology of a tertiary hospital in Chengdu City, China were selected as the training subjects. The high-fidelity intelligent simulator combined with scenario simulation teaching mode was used to conduct emergency response training for the participants. The differences in theoretical knowledge and post competence regarding contrast agent adverse reactions among the staff were compared before and after the training. A self-made questionnaire was used to investigate their needs and satisfaction of the emergency response training. SPSS 26.0 was used for data analysis. The differences in theoretical knowledge and post competence scores before and after training were compared using the paired samples t test. Results:After the training, the average score of theoretical knowledge examination increased from (84.32±10.19) points to (90.34±7.87) points, and the difference was statistically significant ( P<0.001). After the training, the scores of knowledge reserve, operational skills, situational decision-making ability, professional literacy, comprehensive literacy, and overall post competency were all significantly higher than those before the training ( P<0.05). The satisfaction score of emergency response training was (4.17±0.25) points. Conclusions:High-fidelity intelligent simulator combined with scenario simulation training improved the emergency preparedness and teamwork of radiology staff in clinical emergencies. The training received high recognition and satisfaction from the participants, which is of great significance for clinical emergency response and patient safety.

Objective:In response to the subjectivity and poor real-time performance in methods for evaluating the quality of medical theory teaching, this study aims to develop an objective and real-time evaluation method for medical theory teaching quality.Methods:Classroom behavior data from both teachers and students in the course "medical image processing" were collected. An approach combining chain-like agent genetic algorithm with support vector regression machines was employed to analyze the collected classroom behavior data, and a classroom behavior-based evaluation model for medical theory teaching quality was established.Results:The predicted value generated by the model showed minimal error compared to students' actual answer accuracy, with an average absolute error of 4.84%. Additionally, the model demonstrated low time computation, with an average modeling time of 8.63 seconds and an average prediction time of 21.00 milliseconds.Conclusions:The constructed teaching quality assessment model shows high fitting precision and low time consumption.

Objective:To explore the application effect of high-fidelity intelligent simulator combined with scenario simulation for emergency response training in the Department of Radiology, and to improve the emergency preparedness of medical, nursing, and technical staff in managing contrast agent adverse reactions.Methods:From January to July 2024, 132 medical, nursing, and technical staff from the Department of Radiology of a tertiary hospital in Chengdu City, China were selected as the training subjects. The high-fidelity intelligent simulator combined with scenario simulation teaching mode was used to conduct emergency response training for the participants. The differences in theoretical knowledge and post competence regarding contrast agent adverse reactions among the staff were compared before and after the training. A self-made questionnaire was used to investigate their needs and satisfaction of the emergency response training. SPSS 26.0 was used for data analysis. The differences in theoretical knowledge and post competence scores before and after training were compared using the paired samples t test. Results:After the training, the average score of theoretical knowledge examination increased from (84.32±10.19) points to (90.34±7.87) points, and the difference was statistically significant ( P<0.001). After the training, the scores of knowledge reserve, operational skills, situational decision-making ability, professional literacy, comprehensive literacy, and overall post competency were all significantly higher than those before the training ( P<0.05). The satisfaction score of emergency response training was (4.17±0.25) points. Conclusions:High-fidelity intelligent simulator combined with scenario simulation training improved the emergency preparedness and teamwork of radiology staff in clinical emergencies. The training received high recognition and satisfaction from the participants, which is of great significance for clinical emergency response and patient safety.

Objective:In response to the subjectivity and poor real-time performance in methods for evaluating the quality of medical theory teaching, this study aims to develop an objective and real-time evaluation method for medical theory teaching quality.Methods:Classroom behavior data from both teachers and students in the course "medical image processing" were collected. An approach combining chain-like agent genetic algorithm with support vector regression machines was employed to analyze the collected classroom behavior data, and a classroom behavior-based evaluation model for medical theory teaching quality was established.Results:The predicted value generated by the model showed minimal error compared to students' actual answer accuracy, with an average absolute error of 4.84%. Additionally, the model demonstrated low time computation, with an average modeling time of 8.63 seconds and an average prediction time of 21.00 milliseconds.Conclusions:The constructed teaching quality assessment model shows high fitting precision and low time consumption.

Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

AIM:To investigate the therapeutic effect of recombinant human interleukin-37(rhIL-37)inter-vention on extracellular matrix deposition in human bronchial epithelial cells exposed to fine particulate matter(PM2.5),and to explore the underlying mechanisms.METHODS:An airway injury cell model was established using normal human bronchial epithelial 16HBE cells treated with various concentrations(6.25,12.5,25 and 50 mg/L)of PM2.5.Western blot and immunofluorescence were employed to assess the expression level of Wnt family member 5a(Wnt5a).The con-centration of PM2.5 that maximized Wnt5a expression was identified as the optimal concentration for further analysis.The cells were divided into 3 groups,PM2.5+siRNA,PM2.5+Wnt5a siRNA and control+Wnt5a siRNA,to evaluate the expres-sion of fibronectin,the secretion of IL-6 and IL-1β,and the production of reactive oxygen species(ROS).A subsequent set of experiments was organized into PM2.5+rhIL-37,PM2.5 and control groups to determine whether rhIL-37 down-regu-lates the expression of Wnt5a and fibronectin,and reduces the secretion of IL-6 and IL-1β.RESULTS:(1)After 24 h of exposure to various concentrations of PM2.5,the expression of Wnt5a in 16HBE cells was significantly elevated,except at 50 mg/L,compared with control group(P＜0.05).The highest Wnt5a expression was observed at 12.5 mg/L PM2.5(P＜0.01).(2)Fibronectin expression peaked after 24 h of exposure to PM2.5 at 12.5 mg/L(P＜0.01).(3)Successful knock-down of Wnt5a resulted in decreased levels of fibronectin and nuclear factor E2-related factor(Nrf2).Additionally,the production of ROS and the secretion of IL-6 and IL-1β were significantly reduced compared with control group(P＜0.01).(4)The administration of rhIL-37 before PM2.5 exposure led to decreased levels of Wnt5a,fibronectin and Nrf2 compared with PM2.5 group(P＜0.05).Furthermore,rhIL-37 treatment reduced the ROS production and the secretion of IL-6 and IL-1β(P＜0.05).CONCLUSION:In vitro cell models demonstrate that PM2.5 can induce extracellular matrix deposition in bronchial epithelial cells,potentially through the modulation of inflammatory response and oxidative stress influenced by Wnt5a.Additionally,rhIL-37 appears to mitigate inflammatory response and oxidative stress by down-regulating Wnt5a.