Objective To explore the correlation between stroke etiology and clinical and imaging features in patients with acute ischemic stroke(AIS)due to large vessel occlusion treated by intravascular thrombectomy.Methods A total of 213 patients with AIS and endovascular embolectomy in our hospital from Oct.2016 to Jun.2018 were enrolled retrospectively.According to the etiological classification criteria of Trial of Org 10172 in Acute Stroke Treatment(TOAST),there were 116 cases of cardioembolism and 97 cases of non-cardioembolism.Multivariate logistic regression analysis was used to screen the clinical and imaging characteristics for identifying cardioembolism and non-cardioembolism.Results Compared with non-cardioembolism AIS,cardioembolism AIS was associated with higher NIHSS scores(adjusted odds ratio[OR]=1.09,95%confidence interval[95%CI]1.01-1.18,P=0.02),atrial fibrillation(adjusted OR=76.46,95%CI 26.75-218.51,P＜0.01),absence of hypertension(adjusted OR=0.32,95%CI 0.12-0.84,P=0.02),antiplatelet drug use(adjusted OR=5.03,95%CI 1.22-20.63,P=0.03),shorter onset-to-puncture time(adjusted OR=0.998,95%CI 0.996-1.000,P=0.04),and presence of hyperdense artery sign(HAS)(adjusted OR=4.45,95%CI 1.47-13.49,P=0.01).Conclusion There are some differences in clinical and imaging characteristics between patients with cardioembolism and non-cardioembolism AIS.The occurrence of HAS suggests a higher probability of cardioembolism in AIS patients.

Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.

Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma（TFE3-rRCC）.Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma（RCC）patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023，including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC（comprising clear cell RCC，papillary RCC，and chromophobe RCC）. Among them，627 were male and 238 were female，with a mean age of（54.1 ± 12.7）years（range：14?82 years）. The median maximum tumor diameter was 4.0（2.6，6.0）cm. Based on the chronological order of CT examinations，the patients were divided into training（ n=478），validation（ n=206），and test（ n=181）sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images，we extracted peritumoral imaging features，habitat features，3D radiomic features，and 2.5D deep learning radiomic features. A deep learning radiomics score（DLR-SCORE）prediction model was constructed using least absolute shrinkage and selection operator（LASSO）regression. The diagnostic performance of the model was evaluated by receiver operating characteristic（ROC）curve analysis，with the area under the curve（AUC）as the primary metric. Additionally，sensitivity，specificity，and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images，from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%（471/478）in the training set，81.6%（168/206）in the validation set，and 86.2%（156/181）in the test set. The AUC of ROC curve was 0.98（95% CI 0.96?1.00）in the training set，0.83（95% CI 0.71?0.94）in the validation set，and 0.88（95% CI 0.76?1.00）in the test set. In the test set，the DLR-SCORE model achieved a sensitivity of 88.9%（16/18）and a specificity of 85.9%（140/163）for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC，offering a promising noninvasive tool to assist preoperative diagnosis.

Objective To evaluates the effects of cross-balance training on knee function,dynamic balance,and rectus femoris(RF)activation in patients after anterior cruciate ligament reconstruction(ACLR).Methods Forty ACLR patients at 5th-6th week after operation were randomly divided into experimental group and control group.The experimental group received the cross-balance training on the basis of standard rehabilitation,while the control group received only standard rehabilitation.Knee function was assessed with the Lysholm score,dynamic balance,and root mean square(RMS)of RF surface electromyography.The correlation between RMS and dynamic balance was also examined.Results After intervention,the Lysholm score of the experimental group was significantly higher than that of the control group(P<0.01).Regarding balance function,both the gait line length and single support line length of the experimental group were significantly greater than those of the control group(P<0.01).Conversely,the mediolateral displacement of the experimental group was significantly lower than that of the control group(P<0.01).Furthermore,the RF RMS of the experimental group was significantly larger than that of the control group(P<0.01).The RF RMS was positively correlated with the gait line length and single support line length,whereas it was negatively correlated with the mediolateral displacement(P<0.05).Conclusions Cross-balance training significantly enhances knee function,dynamic balance,and RF activation in post-ACLR patients,supports the theory of cross-education.Cross-balance training has certain application values in ACL postoperative rehabilitation.

Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.

Objective To evaluates the effects of cross-balance training on knee function,dynamic balance,and rectus femoris(RF)activation in patients after anterior cruciate ligament reconstruction(ACLR).Methods Forty ACLR patients at 5th-6th week after operation were randomly divided into experimental group and control group.The experimental group received the cross-balance training on the basis of standard rehabilitation,while the control group received only standard rehabilitation.Knee function was assessed with the Lysholm score,dynamic balance,and root mean square(RMS)of RF surface electromyography.The correlation between RMS and dynamic balance was also examined.Results After intervention,the Lysholm score of the experimental group was significantly higher than that of the control group(P<0.01).Regarding balance function,both the gait line length and single support line length of the experimental group were significantly greater than those of the control group(P<0.01).Conversely,the mediolateral displacement of the experimental group was significantly lower than that of the control group(P<0.01).Furthermore,the RF RMS of the experimental group was significantly larger than that of the control group(P<0.01).The RF RMS was positively correlated with the gait line length and single support line length,whereas it was negatively correlated with the mediolateral displacement(P<0.05).Conclusions Cross-balance training significantly enhances knee function,dynamic balance,and RF activation in post-ACLR patients,supports the theory of cross-education.Cross-balance training has certain application values in ACL postoperative rehabilitation.

Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma（TFE3-rRCC）.Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma（RCC）patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023，including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC（comprising clear cell RCC，papillary RCC，and chromophobe RCC）. Among them，627 were male and 238 were female，with a mean age of（54.1 ± 12.7）years（range：14?82 years）. The median maximum tumor diameter was 4.0（2.6，6.0）cm. Based on the chronological order of CT examinations，the patients were divided into training（ n=478），validation（ n=206），and test（ n=181）sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images，we extracted peritumoral imaging features，habitat features，3D radiomic features，and 2.5D deep learning radiomic features. A deep learning radiomics score（DLR-SCORE）prediction model was constructed using least absolute shrinkage and selection operator（LASSO）regression. The diagnostic performance of the model was evaluated by receiver operating characteristic（ROC）curve analysis，with the area under the curve（AUC）as the primary metric. Additionally，sensitivity，specificity，and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images，from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%（471/478）in the training set，81.6%（168/206）in the validation set，and 86.2%（156/181）in the test set. The AUC of ROC curve was 0.98（95% CI 0.96?1.00）in the training set，0.83（95% CI 0.71?0.94）in the validation set，and 0.88（95% CI 0.76?1.00）in the test set. In the test set，the DLR-SCORE model achieved a sensitivity of 88.9%（16/18）and a specificity of 85.9%（140/163）for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC，offering a promising noninvasive tool to assist preoperative diagnosis.

Objective:An ICP-MS method was established for the determination of arsenic(As),cadmium(Cd),mercury(Hg),lead(Pb),cobalt(Co),nickel(Ni),vanadium(V),lithium(Li),antimony(Sb),copper(Cu)and other 10 elements in pharmaceutical excipients sucrose to assess their risks.Methods:The pharmaceuti-cal excipient sucrose was dissolved in 0.1％HN03 solution directly,and the contents of 75 As,111Cd,202Hg,208Pb,59 Co,60 Ni,51V,7 Li,121 Sb,and 63 Cu in sucrose were determined by the ICP-MS method with the optimized instru-mental parameters in the STD mode.Results:The results showed that the linearity of the method was great in the range of 0-100 ng·mL-1 for As,Cd,Pd,Co,Ni,V,Li,Sb and Cu(the correlation coefficient r was not less than 0.99),and the linearity of the method was good in the range of 0-2 ng·mL-1 for Hg(r=0.999 1).The average recoveries for the 10 elements were in the range of 99.8％-100.0％,and the RSDs were less than 5％(n=6).Conclusion:The method is easy to operate and has high accuracy.It can be used for the determination of 10 elemental impurities in pharmaceutical excipient sucrose.It can be seen that the content of the above ten elements in sucrose is much lower than the specified value in ICH Q3D,and the risk is small.The heavy metal item can no longer be considered separately when revising the standard.