Objective To explore a method for rapid and differential diagnosis of rejection after kidney transplantation through urine hyperspectral imaging technology. Methods Hyperspectral data information from urine samples of 118 recipients after kidney transplantation was collected, and a deep learning model was constructed to diagnose and classify the types of rejection. Results A deep learning diagnostic model based on the 34-layer residual network (ResNet-34) was constructed, and 118 patients were included and divided into the training set and the test set. Based on the pathological results of the transplanted kidney puncture, the urine samples of the patients were classified into five groups: the non-rejection group, the T-cell-mediated rejection group, the antibody-mediated rejection group, the mixed rejection group and the nephropathy recurrence group. The results showed that the diagnostic sensitivities of the model for the above five groups were 0.960, 0.980, 0.930, 0.940 and 0.943 respectively, and the diagnostic specificities were 0.983, 0.993, 0.997, 0.989 and 0.989 respectively. The overall diagnostic accuracy rate reached 95.7%. Conclusions The study provides a non-invasive, rapid and accurate auxiliary diagnostic method for the differential diagnosis of rejection after kidney transplantation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Objective To analyze the MRI imaging characteristics of brain metastases in non-small cell lung cancer(NSCLC)with different epidermal growth factor receptor(EGFR)mutation types and programmed cell death-ligand 1(PD-L1)expression,and to provide imaging diagnostic support for patients who can't undergo genetic and immunohistochemical testing.Methods A retrospec-tive selection was performed in 88 patients diagnosed with brain metastases of NSCLC,all patients were divided into EGFR mutation group and wild group according to the results of genetic testing,and patients with EGFR mutation group were divided into EGFR mutation with PD-L1 expression positive group and EGFR mutation with PD-L1 expression negative group according to whether the expression of PD-L1 was≥1％.The clinical data and MR image characteristics of brain metastases were compared in EGFR mutation group and wild group,as well as in EGFR mutation with PD-L1 expression positive group and EGFR mutation with PD-L1 expres-sion negative group.Results There were statistically significant differences in smoking history and intracranial symptoms between EGFR mutation group and wild group(P＜0.05).The edema diameter,edema index and enhancement ratio of EGFR mutation group and wild group were(0.67±1.10)cm,0.39±0.54,0.32±0.17 and(1.57±2.04)cm,1.05±1.21,0.53±0.27,respectively,and the differences were statistically significant(P＜0.05).There were 43 cases and 23 cases in EGFR mutation group and wild group with ≥2 metastases,respectively,and the difference was statistically significant(P＜0.05).Compared with＞60 years old,there were 15 patients(75％)of EGFR mutation with PD-L1 expres-sion positive in≤60 years old(P＜0.05).Conclusion Compared with EGFR wild patients,patients with EGFR mutation have more brain metastases(≥2),milder enhancement,less peritumoral edema,and fewer intracranial symptoms at initial diagnosis,and patients with EGFR mutation aged≤60 years are more likely to have PD-L1 expression positive.

To construct a recombinant fowl adenovirus 4(FAdV-4)expressing the Cap protein of goose astrovirus genotype 2(GoAstV-2),the expression cassette of Cap gene was inserted into the natural 1 966 bp deletion region of the FAdV-4 genome in the infectious clone p15A-cm-FAdV4-HNJZ.The resulted recombinant plasmid p15A-cm-FAdV4-HNJZ-Cap/GoAstV-2 was linearized with restriction enzyme and transfected into chicken hepatoma cell line(LMH)to rescue the recombinant FAdV-4 expressing the Cap protein of GoAstV-2,rF Ad V4-Cap/GoAstV-2.After 15 passages in LMH cells,the recombinant rFAdV4-Cap/GoAstV-2 was identified by PCR using primers flanking the insertion site of the Cap gene expression cassette and using viral genome DNA extracted from rFAdV4-Cap/GoAstV-2 infected LMH cells as template.LMH cells were in-fected with 15th passage rFAdV4-Cap/GoAstV-2 and indirect immunofluorescence was performed with a polyclonal antibody against Cap protein as the primary antibody.Western blot was carried out with lysates of rFAdV4-Cap/GoAstV-2 infected LMH cells.The in vitro replication dynamic of the 15th passage of the rFAdV4-Cap/GoAstV-2 was also investigated in LMH cells.The results demonstrated that the Cap gene of GoAstV-2 was presented in the genome of the recombinant vi-rus rF AdV4-Cap/Go Ast V-2,and could be expressed stably.The prepared recombinant virus in this study will lay a foundation for developing inactivated bivalent vaccine candidate against co-in-fection of FAdV-4 and GoAstV-2 in goose.

Objective To investigate the impact of variations in volute cross-sectional area on the flow characteristics and hemolytic performance of centrifugal blood pumps by designing six volute structures.Methods Computational fluid dynamics and the Lagrangian method were used to analyze flow characteristics and predict hemolysis in blood pumps with different volute designs.Results The annular volute pump showed the poorest hydraulic performance,while the hydraulic performance of the S-shaped volute was the best,which was improved by 35.29％compared to that of the annular volute.Some volutes experienced stagnation zones at the helical inlet(0°-90°)and significant backflow at the outlet(270°-360°).The downward concave-shaped volute had the highest hemolysis index(HI),i.e.,9.59×10-4.Meanwhile,the HI of the annular volute was the lowest,which was 71.85％less than the concave-shaped volute.Conclusions Reducing the gradient of the area variation at the helical inlet and outlet can prevent flow stagnation and backflow.A higher HI arises due to the prolonged exposure of red blood cells to high shear stress.This study provides a theoretical basis for designing and optimizing volute structures of centrifugal blood pumps.

Objective To study the effects of different clearance conditions(equal upper and lower axial clearance,change of upper/lower axial clearance,axial displacement of blades)on efficiency and hemolysis performance of blood pump.Methods The blood pumps under three kinds of clearance conditions were numerically simulated by computational fluid dynamics.Results For efficiency,when the upper and lower axial clearance was equal,the lower axial clearance was unchanged and the upper axial clearance was reduced,the efficiency of blood pump could be improved by 0.85%,1.71%and 2.90%,respectively.While the upper shaft clearance remained unchanged,the lower shaft clearance was decreased by 1.18%.For hemolysis,the increase of the clearance could reduce the hemolysis index(HI)under the first two clearance conditions,while the axial migration of the blade wheel would increase the HI.When the upper axial clearance was unchanged and the lower axial clearance was 0.3 mm,the HI was the largest,which was 8.65×10-4.When the upper and lower axial clearance was 0.7 mm,the HI was the smallest,which was 4.51×10-4.Conclusions Improving blood pump clearance is helpful to optimize the performance of blood pump.This study can provide some references for the design and optimization of interstitial structure of blood pump.

Objective:To develop and validate CT radiomics models based on machine learning for predicting recurrence of chronic subdural hematoma (cSDH) after endoscopic treatment.Methods:A retrospective study was performed; 252 patients with cSDH who underwent endoscopic treatment in Department of Neurosurgery, the Second Affiliated Hospital of Soochow University from October 2016 to October 2024 were selected. The clinical and imaging data of these patients were collected, and these patients were divided into a training set ( n=176) and a validation set ( n=76) at a ratio of 7:3. Patients in both sets were further sub-divided into a recurrence group and a non-recurrence group based on whether they had recurrence within 3 months of discharge. (1) Radiomics features of cSDH on initial non-enhanced CT images were extracted using 3D-Slicer software. Optimal features were selected through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis; based on these optimal features, 3 machine learning algorithms (Logistic, support vector machine [SVM], and K-nearest neighbor [KNN]) were used to construct CT radiomics models. Differences in predictive performance of different radiomics models were compared by analyzing indicators such as sensitivity, specificity, and area under receiver operating characteristic (ROC) curve (AUC), and the best model was selected. (2) Based on the initial non-enhanced CT images, cSDH was classified into homogeneous type, laminar type, septated type, and trabecular type according to Nakaguchi classification system; combined these cSDH typing with clinical features (clinical Markwalder's grade and bilateral hematoma), univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors for cSDH recurrence. Based on these factors, the 3 machine learning algorithms (Logistic, SVM, KNN) were used to construct hematoma typing-clinical feature models; differences in predictive performance of different hematoma typing-clinical feature models were compared by analyzing indicators such as sensitivity, specificity, and AUC, and the best model was selected. (3) DeLong's test was used to compare the ROC curve differences between the CT radiomics model and hematoma typing-clinical feature model. Decision curve analysis was used to compare the effective scope of the CT radiomics model and hematoma typing-clinical feature model. Results:(1) Seven optimal CT radiomics features based on wavelet transform were obtained after univariate analysis and LASSO regression: one gray-level dependence matrix feature, one first-order energy feature, two gray-level co-occurrence matrix features, two gray level size zone matrix features, and one gray-level run-length matrix feature. The KNN model constructed based on these 7 optimal features had the best performance in predicting cSDH recurrence, with an AUC of 0.845, a sensitivity of 0.833, a specificity of 0.857, a recall rate of 0.833, and an F1 score of 0.476 in patients from the validation set. (2) Three independent risk factors for cSDH recurrence were screened out through univariate analysis and multivariate Logistic regression analysis: hematoma Nakaguchi classification, Markwalder's grade, and bilateral hematoma. Logistic model constructed based on these 3 factors had the best performance in predicting cSDH recurrence, with an AUC of 0.675, a sensitivity of 0.609, a specificity of 0.654, a recall rate of 0.609, and an F1 score of 0.311 in patients from the validation set. (3) DeLong's test showed that the AUC of the CT radiomics model was significantly greater than that of the hematoma typing-clinical feature model in patients from the training set and validation set ( P=0.027 and P=0.035). Decision curve analysis showed that in the CT radiomics model, the net benefit of the model was >0 when the risk threshold was 0.05-0.95; in the hematoma typing-clinical feature model, the net benefit of the model was >0 when the risk threshold was 0.05-0.55. Conclusion:The KNN model based on 7 CT radiomics features in this study can effectively predict the cSDH recurrence in patients after endoscopic treatment, and its performance is obviously better than that of hematoma typing-clinical feature model constructed in this study.

Objective To investigate the impact of variations in volute cross-sectional area on the flow characteristics and hemolytic performance of centrifugal blood pumps by designing six volute structures.Methods Computational fluid dynamics and the Lagrangian method were used to analyze flow characteristics and predict hemolysis in blood pumps with different volute designs.Results The annular volute pump showed the poorest hydraulic performance,while the hydraulic performance of the S-shaped volute was the best,which was improved by 35.29％compared to that of the annular volute.Some volutes experienced stagnation zones at the helical inlet(0°-90°)and significant backflow at the outlet(270°-360°).The downward concave-shaped volute had the highest hemolysis index(HI),i.e.,9.59×10-4.Meanwhile,the HI of the annular volute was the lowest,which was 71.85％less than the concave-shaped volute.Conclusions Reducing the gradient of the area variation at the helical inlet and outlet can prevent flow stagnation and backflow.A higher HI arises due to the prolonged exposure of red blood cells to high shear stress.This study provides a theoretical basis for designing and optimizing volute structures of centrifugal blood pumps.

Objective To analyze the MRI imaging characteristics of brain metastases in non-small cell lung cancer(NSCLC)with different epidermal growth factor receptor(EGFR)mutation types and programmed cell death-ligand 1(PD-L1)expression,and to provide imaging diagnostic support for patients who can't undergo genetic and immunohistochemical testing.Methods A retrospec-tive selection was performed in 88 patients diagnosed with brain metastases of NSCLC,all patients were divided into EGFR mutation group and wild group according to the results of genetic testing,and patients with EGFR mutation group were divided into EGFR mutation with PD-L1 expression positive group and EGFR mutation with PD-L1 expression negative group according to whether the expression of PD-L1 was≥1％.The clinical data and MR image characteristics of brain metastases were compared in EGFR mutation group and wild group,as well as in EGFR mutation with PD-L1 expression positive group and EGFR mutation with PD-L1 expres-sion negative group.Results There were statistically significant differences in smoking history and intracranial symptoms between EGFR mutation group and wild group(P＜0.05).The edema diameter,edema index and enhancement ratio of EGFR mutation group and wild group were(0.67±1.10)cm,0.39±0.54,0.32±0.17 and(1.57±2.04)cm,1.05±1.21,0.53±0.27,respectively,and the differences were statistically significant(P＜0.05).There were 43 cases and 23 cases in EGFR mutation group and wild group with ≥2 metastases,respectively,and the difference was statistically significant(P＜0.05).Compared with＞60 years old,there were 15 patients(75％)of EGFR mutation with PD-L1 expres-sion positive in≤60 years old(P＜0.05).Conclusion Compared with EGFR wild patients,patients with EGFR mutation have more brain metastases(≥2),milder enhancement,less peritumoral edema,and fewer intracranial symptoms at initial diagnosis,and patients with EGFR mutation aged≤60 years are more likely to have PD-L1 expression positive.