Metabolic reprogramming， as one of the core hallmarks of malignant tumors， plays a key role in the occurrence， development and treatment of breast cancer （BC）. Abnormal changes in glucose metabolism， amino acid metabolism， lipid metabolism， as well as the tricarboxylic acid （TCA） cycle and oxidative phosphorylation （OXPHOS） pathways significantly influence the pathogenesis and progression of BC. Studies have shown that various active components of traditional Chinese medicine （TCM） （such as berberine， matrine， quercetin， curcumin， etc.） and their compound formulations （e.g. Xihuang pill， Danzhi xiaoyao powder， Yanghe decoction， etc.） can inhibit the proliferation and migration of BC cells and induce apoptosis by regulating key metabolic pathways such as glycolysis， lipid synthesis， and amino acid metabolism. TCM demonstrates multi-target and holistic regulatory advantages in intervening in BC metabolic reprogramming， showing significant potential in modulating key molecules like hypoxia inducible factor-1α， hexokinase-2， pyruvate kinase M2， lactate dehydrogenase A， glucose transporter-1， fatty acid synthase， and signaling pathways such as AKT/mTOR. However， current researches still focus predominantly on glucose metabolism， with insufficient mechanistic studies on lipid metabolism， amino acid metabolism， the TCA cycle， and OXPHOS. The precise targets， molecular mechanisms， and clinical translation value of these interventions require further validation and clarification through more high-quality experimental studies and clinical trials.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective:To establish three machine learning prediction models based on CT imaging characteristics of papillary thyroid carcinoma (PTC) , and use SHAP (shapley additive explanations) analysis to investigate the contribution of each CT image features in the best model.Methods:CT imaging features in 426 cases of 440 PTCs confirmed pathologically from Jan. 2016 to Jan. 2021 at the affiliated Hangzhou First People’s Hospital of Westlake University Medical School were retrospectively analyzed. compared with 467 cases of 528 nodular goiter (NG) , evaluating the distribution of four CT characteristics: cookie bite sign, enhanced range of narrowing/blur (ERNB) , microcalcifications, and irregular shape. We split the data into 8∶2 ratio for training and testing sets, then constructed three machine learning models using XGBoost, RF, and SVM. Based on AUC, accuracy, F1 score, and other metrics, we selected the best model. Lastly, we used SHAP values to assess each CT feature’s contribution and positive/negative effects on the model.Results:Among 440 PTC and 528 NG nodules, CT features like cookie bite sign, ERNB, microcalcifications, and irregular shape occurred in 326 and 30 ( χ 2=483.05, P<0.001) , 363 and 106 ( χ 2=374.45, P<0.001) , 158 and 53 ( χ 2=94.24, P<0.001) , and 354 and 52 ( χ 2=491.34, P<0.001) nodules, respectively. The machine learning models built using XGBoost, RF, and SVM had AUC, accuracy, and F1 scores ranging from 0.884~0.925, 0.867~0.873, and 0.844~0.854 respectively on the training set. On the test set, the scores ranged from 0.869~0.923, 0.845~0.871, and 0.803~0.845. Among them, the XGBoost model demonstrated the highest diagnostic performance on the test set. Among the four CT features, irregular shape had the highest absolute SHAP value, positively contributing to PTC diagnosis. Conclusion:XGBoost model showed the highest PTC diagnostic performance. Irregular shape had the greatest positive impact on PTC diagnosis.

Objective To observe the value of non-contrast CT radiomics extreme gradient boosting(XGBoost)model based on SHAP method for predicting acute necrotic collection(ANC)around acute pancreatitis(AP).Methods A total of 307 patients with initially clinically diagnosed AP were retrospectively enrolled.The optimal radiomics features of peripheral pancreatic tissue volume of interest(VOI)were extracted and screened based on automatic segmentation on the first non-contrast CT,and the evaluation results of modified CT severity index(MCTSI)score of AP severity based on first enhanced CT were recorded.The patients were divided into peripancreatic ANC group(ANC group)and acute peripancreatic fluid collection(APFC)group according to follow-up abdominal CT.XGBoost method was used to construct radiomics model,MCTSI model and combined model for predicting AP ANC based on the optimal radiomics features,MCTSI and their combination,respectively.The diagnostic efficacy of each model was evaluated using 5-fold cross-validation method,and the contribution of each variable to combined model was analyzed with SHAP method.Results Among 307 cases,there were 134 cases in ANC group and 173 in APFC group.Totally 6 optimal radiomics features were screened based on the first non-contrast CT.The area under the receiver operating characteristic curve(AUC)of radiomics model,MCTSI model and combined model was 0.936,0.693 and 0.917,respectively.The AUC of MCTSI model was lower than that of radiomics model and combined model(Z=-3.485,-2.824,both P＜0.01),while no significant difference of AUC was found between radiomics model and combined model(Z=-0.817,P=0.415).The contribution of optimal radiomics features to combined model were all higher than that of MCTSI score.Conclusion Non-contrast CT radiomics XGBoost model could effectively predict AP ANC.

Paclitaxel(PTX)is a first-line chemotherapy drug for breast cancer,but its resistance issues significantly impact clinical treatment efficacy.Fucosylation,especially core fucosylation,is closely related to tumor chemoresistance,resulting in poor chemotherapy responses and poor prognosis in patients.In this study,we investigated the effect and mechanism of the fucosylation inhibitor 2-fluorofucose(2-F-Fuc)on the chemosensitivity of paclitaxel-resistant breast cancer MCF-7/PTX cells.The drug resistanceindex(RI)of MCF-7/PTX cells was 8.49 by MTT assays.Western blotting,real-time PCR,enzyme-linked immu-nosorbent assay(ELISA)and Lens Culinaris Agglutinin(LCA)lectin imprinting showed that compared with MCF-7 cells,the expression of FUT8,MDR1and core fucosylation in MCF-7/PTX cells was high.Western blotting showed that 2-F-Fuc had a significant inhibitory effect on the growth of MCF-7/PTX cells,and the expression levels of FUT8 and MDR1 were significantly down-regulated after 2-F-Fuc treatment,and the down-regulation was more pronounced in the PTX and 2-F-Fuc combination group(P＜0.05).Compared to the control,expression of PCNA in MCF-7/PTX cells in the PTX and the 2-F-Fuc group were down-regulated,and the apoptosis-related proteins,such as cleaved caspase-3 and Bax/Bcl-2 were in-creased.The level of p-PI3K and p-AKT were down-regulated,and the changes in the combination of 2-F-Fuc and PTX were more robust(P＜0.05).The above results showed that the core fucosylation level of MCF-7/PTX cells was significantly increased,and 2-F-Fuc could reduce the core fucosylation level of MCF-7/PTX cells by inhibiting the expression of FUT8,and enhance the sensitivity of drug-resistant cells to PTX,which may correlate with the downregulation of PI3K/AKT signaling pathway proteins.

Objective To develop and validate a nomogram prediction model for residual stone risk after flexible ureteroscopic lithotripsy(FURL)in patients with 2-3 cm renal calculi,so as to provide reference for treatment options.Methods Clinical data of 342 patients with renal calculi measuring 2-3 cm undergoing FURL in our hospital during Jun.2017 and Apr.2024 were retrospectively collected.At a 3∶1 randomization ratio,patients were allocated to the training cohort(n=257)and validation cohort(n=85).Patients in the training cohort were stratified into two subgroups based on postoperative stone-free status:residual stone group(n=63)and stone-free group(n=194).Logistic regression analysis was employed to identify factors influencing stone retention and construct the nomogram prediction model.Bootstrapped resampling was applied to validate the model internally,model performance was assessed with calibration curves,Hosmer-Lemeshow test was used to test the degree of fitting,receiver operating characteristic(ROC)curve was plotted to evaluate the predictive accuracy,and decision curve analysis was used to determine the clinical net benefit.The model's generalization capability was evaluated with 10-fold cross-validation of the training set.Results Multivariate logistic regression revealed that stone size,CT value,lower calyx stones,multiple stones,renal infundibulum length(RIL),and renal infundibulum width(RIW)were independent predictors of residual stones(P＜0.05).The nomogram based on the above mentioned parameters demonstrated excellent discrimination,with Bootstrap-validated concordance indices of 0.876(training cohort)and 0.948(validation cohort).Hosmer-Lemeshow tests showed good calibration in both cohorts(P＞0.05).ROC analysis yielded the area under the curve(AUC)of 0.876 and 0.948 for the training and validation cohorts,respectively.The optimal cutoff value was 0.253,with corresponding sensitivity of 84.13％,specificity of 78.35％,and total score of nomogram of 143.The decision curve analysis showed when the threshold probability of the training cohort and verification cohort was 0-0.81 and 0-0.97,respectively,the nomogram could obtain good clinical net benefit in predicting the risk of residual stones.The average accuracy of 10-fold cross-validation was 0.814,and the average AUC was 0.865.Conclusion The nomogram model effectively predicts residual stone risk following FURL for 2-3 cm renal calculi.It is suggested that patients with a total score of ≤143 may consider undergoing FURL.

Objective:To establish three machine learning prediction models based on CT imaging characteristics of papillary thyroid carcinoma (PTC) , and use SHAP (shapley additive explanations) analysis to investigate the contribution of each CT image features in the best model.Methods:CT imaging features in 426 cases of 440 PTCs confirmed pathologically from Jan. 2016 to Jan. 2021 at the affiliated Hangzhou First People’s Hospital of Westlake University Medical School were retrospectively analyzed. compared with 467 cases of 528 nodular goiter (NG) , evaluating the distribution of four CT characteristics: cookie bite sign, enhanced range of narrowing/blur (ERNB) , microcalcifications, and irregular shape. We split the data into 8∶2 ratio for training and testing sets, then constructed three machine learning models using XGBoost, RF, and SVM. Based on AUC, accuracy, F1 score, and other metrics, we selected the best model. Lastly, we used SHAP values to assess each CT feature’s contribution and positive/negative effects on the model.Results:Among 440 PTC and 528 NG nodules, CT features like cookie bite sign, ERNB, microcalcifications, and irregular shape occurred in 326 and 30 ( χ 2=483.05, P<0.001) , 363 and 106 ( χ 2=374.45, P<0.001) , 158 and 53 ( χ 2=94.24, P<0.001) , and 354 and 52 ( χ 2=491.34, P<0.001) nodules, respectively. The machine learning models built using XGBoost, RF, and SVM had AUC, accuracy, and F1 scores ranging from 0.884~0.925, 0.867~0.873, and 0.844~0.854 respectively on the training set. On the test set, the scores ranged from 0.869~0.923, 0.845~0.871, and 0.803~0.845. Among them, the XGBoost model demonstrated the highest diagnostic performance on the test set. Among the four CT features, irregular shape had the highest absolute SHAP value, positively contributing to PTC diagnosis. Conclusion:XGBoost model showed the highest PTC diagnostic performance. Irregular shape had the greatest positive impact on PTC diagnosis.

Objective:To explore the clinical efficacy of Wenshen Chushi Decoction combined with low intensity pulsed ultra-sound(LIPUS)on erectile dysfunction(ED)caused by renal deficiency and phlegm-dampness syndrome.Methods:One hundred and twenty ED patients were included from the Department of Andrology in the First Hospital of Hunan University of Traditional Chinese Medicine.The patients in control group were treated with Wenshen Chushi Decoction.While the patients in observation group were trea-ted with Wenshen Chushi Decoction combined with LIPUS for 8 consecutive weeks.After the treatment,the efficacy was evaluated using the International Index of Erectile Function-5(IIEF-5)score,Penile Flow Index(PFI),Traditional Chinese Medicine Syndrome Score,Self-Rating Depression Scale(SDS)score,and Self-Rating Anxiety Scale(SAS)score.Safety was also observed.And the ef-ficacy was followed up 4 weeks after the end of treatment.Results:Fifty-seven cases were enrolled into control group finally with 55 cases in the treatment group.After the treatment,all the patients in both of groups showed an improvement in IIEF-5 scores(P＜0.01).Compared with the control group(19.09±2.22),the IIEF-5 score in observation group(20.42±2.39)increased signifi-cantly(P＜0.01).After the treatment,the scores of PFI,TCM syndrome and SDS in both groups decreased(P＜0.01,P＜0.05,P＜0.01).Compared with the control group([3.77±1.21],[9.91±1.71]and[39.88±2.63]points),the observation group([2.92±1.08],[4.78±1.45],and[34.51±2.09]points)showed a more significant decrease(P＜0.01).There was no significant difference in total effective rate between the two groups(P＞0.05).During follow-up,the IIEF-5 scores of both groups of patients were higher than those before(P＜0.05,P＜0.01),and the observation group score was higher than that in the control group([17.15±3.37]vs[13.63±1.96],P＜0.01).No adverse reaction and abnormality of indicators occurred in both of two groups.Conclusion:Wenshen Chushi Decoction has a significant therapeutic effect on ED caused by renal deficiency and phlegm-dampness syndrome.It can not only improve the quality of erection,but also improve the physical and mental symptoms associated with ED,which makes therapeutic effect lasting longer.

Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]