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 evaluate the influencing factors of recurrence of non-valvular atrial fibrillation（NVAF）after catheter ablation using echocardiographic myocardial work combined with clinical indicators.Methods:A total of 194 patients with NVAF who underwent catheter ablation for the first time in the Second Affiliated Hospital of Nanchang University from June 2021 to March 2023 were retrospectively collected. The clinical and echocardiographic data were collected and followed up for no less than 12 months. Univariate and multivariate Logistic regression analysis were used to determine the independent influencing factors of recurrence. ROC curve analysis was performed for the Logistic regression model established in this study and six previous recurrence scoring models.Results:Left atrial anteroposterior diameter（LAD），global constructive work（GCW），global wasted work（GWW），duration of atrial fibrillation，and type of atrial fibrillation were independent risk factors for recurrence after catheter ablation（all P<0.05）. The Logistic regression model had the best diagnostic performance compared with the previous scoring models，with an area under the curve of 0.934（95% CI=0.900-0.968），a sensitivity of 0.897，and a specificity of 0.882. Conclusions:LAD，GCW，GWW，duration of atrial fibrillation，and type of atrial fibrillation are independent influencing factors for the recurrence of atrial fibrillation. The prediction model based on myocardial work parameters and clinical indicators has good diagnostic efficiency.

Objective:To evaluate the influencing factors of recurrence of non-valvular atrial fibrillation（NVAF）after catheter ablation using echocardiographic myocardial work combined with clinical indicators.Methods:A total of 194 patients with NVAF who underwent catheter ablation for the first time in the Second Affiliated Hospital of Nanchang University from June 2021 to March 2023 were retrospectively collected. The clinical and echocardiographic data were collected and followed up for no less than 12 months. Univariate and multivariate Logistic regression analysis were used to determine the independent influencing factors of recurrence. ROC curve analysis was performed for the Logistic regression model established in this study and six previous recurrence scoring models.Results:Left atrial anteroposterior diameter（LAD），global constructive work（GCW），global wasted work（GWW），duration of atrial fibrillation，and type of atrial fibrillation were independent risk factors for recurrence after catheter ablation（all P<0.05）. The Logistic regression model had the best diagnostic performance compared with the previous scoring models，with an area under the curve of 0.934（95% CI=0.900-0.968），a sensitivity of 0.897，and a specificity of 0.882. Conclusions:LAD，GCW，GWW，duration of atrial fibrillation，and type of atrial fibrillation are independent influencing factors for the recurrence of atrial fibrillation. The prediction model based on myocardial work parameters and clinical indicators has good diagnostic efficiency.

Objective:Glioblastoma(GBM)and brain metastases(BMs)are the two most common malignant brain tumors in adults.Magnetic resonance imaging(MRI)is a commonly used method for screening and evaluating the prognosis of brain tumors,but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited.In recent years,deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system.This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases(SBMs),and to further explore the impact of multimodality data fusion on classification tasks. Methods:Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed.First,structural T1-weight,T1C-weight,and T2-weight were selected as 3 inputs to the entire model,regions of interest(ROIs)were manually delineated on the registered three modal MR images,and multimodality radiomics features were obtained,dimensions were reduced using a random forest(RF)-based feature selection method,and the importance of each feature was further analyzed.Secondly,we used the method of contrast disentangled to find the shared features and complementary features between different modal features.Finally,the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. Results:The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs.Furthermore,compared with single-modal data,the multimodal fusion models using machine learning algorithms such as support vector machine(SVM),Logistic regression,RF,adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT)achieved significant improvements,with area under the curve(AUC)values of 0.974,0.978,0.943,0.938,and 0.947,respectively;our comparative disentangled multi-modal MR fusion method performs well,and the results of AUC,accuracy(ACC),sensitivity(SEN)and specificity(SPE)in the test set were 0.985,0.984,0.900,and 0.990,respectively.Compared with other multi-modal fusion methods,AUC,ACC,and SEN in this study all achieved the best performance.In the ablation experiment to verify the effects of each module component in this study,AUC,ACC,and SEN increased by 1.6%,10.9%and 15.0%,respectively after 3 loss functions were used simultaneously. Conclusion:A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

ObjectiveThis study aimed to evaluate the clinical efficacy of Ruyi Zhenbaowan（RYZBW）in the treatment of initial and early knee osteoarthritis （KOA） through a prospective multicenter，randomized，double-blind，and placebo-parallel controlled trial. MethodFrom October 13^th， 2021 to December 25^th， 2021， 240 KOA subjects meeting the acceptance criteria were enrolled in 15 sub-centers including Wangjing Hospital， Chinese Academy of Chinese Medical Sciences， and they were randomly divided into observation group and control group， with 120 cases in each group. The intervention measures for the observation group were RYZBW + health education， and the intervention measures for the control group were RYZBW placebo + health education. The intervention period in both groups was four weeks， and they were followed up for four weeks after the intervention. The primary outcome measure was the total score of Western Ontario and McMaster University Osteoarthritis Index score （WOMAC score）， and the secondary outcome measures were the response rate of visual scale （VAS） pain score， WOMAC sub item scores （joint pain， joint stiffness， and joint function）， quality of life （SF-12） score， and traditional Chinese medicine （TCM） syndrome score. Result（1） Efficacy evaluation. The marginal model results showed that the observation group was better than the control group in improving the WOMAC total score and WOMAC pain score in the treatment of KOA with RYZBW， and the difference was statistically significant （P<0.05）. There was no significant difference between the two groups in improving VAS score response rate， WOMAC function score， WOMAC stiffness score， SF12-PCS （quality of life-physical health） score， SF12-MCS （quality of life-mental health） score， and TCM syndrome score. （2） Subgroup analysis. ① In terms of VAS score response rate， the response rate of the observation group was higher than that of the control group for subjects with baseline VAS score of （4， 5］， and the difference was statistically significant （P<0.05）. ② In terms of TCM syndrome score， for subjects aged ［56， 60］ and ［61， 65］， the decrease in total TCM syndrome score in the observation group was better than that in the control group， and the difference was statistically significant （P<0.05）. ConclusionTibetan medicine RYZBW has good clinical efficacy in improving WOMAC total score， VAS score response rate， WOMAC pain score， WOMAC function score， and TCM syndrome score for patients with initial and early KOA， which can fill the lack of Tibetan medicine RYZBW in the treatment of KOA and make a demonstration study for the inheritance and development of ethnic medicine.

Objective To observe the imaging manifestations of paraganglioma of urinary bladder(PUB).Methods Data of 9 patients with single PUB confirmed by surgical pathology were retrospectively analyzed.Among 9 cases,8 cases underwent abdominal ultrasonography,6 underwent pelvic CT and 6 underwent pelvic MR examination.The imaging manifestations of PUB were observed.Results All 9 PUB lesions shaped round or ellipsoid,with wide base,clear boundary and regular shape,the diameters were 14-41 mm,with an average of(27.3±9.l)mm.Two lesions located at the left lateral wall,1 at the left anterior wall,2 at the right lateral wall and 4 at the right anterior wall of the bladder.Two dimensional ultrasound displayed hypoechoic lesions in all 8 cases(8/8,100％),and"bladder mucosa line"sign was detected in 6 cases(6/8,75.00％),while CDFI showed rich blood flow signals in 6 lesions(6/8,75.00％),spot and strip blood flow signal in 1 lesion(1/8,12.50％)but no blood flow signal in 1 case(1/8,12.50％).CT showed that all 6 lesions(6/6,100％)present as soft tissue densities,1(1/6,16.67％)with intratumoral cystic change and necrosis,while"bladder mucosa line"sign was found in 2 cases(2/6,33.33％).MRI showed all 6 lesions(6/6,100％)located under the bladder mucosa,and"bladder mucosa line"sign was clearly visible(6/6,100％).Four lesions(4/6,66.67％)present as slight hyperintensities,1(1/6,16.67％)as slight hypointensity and 1 as isointense(1/6,16.67％)on T1WI,5(5/6,83.33％)as slight hyperintensity(n=5)and 1 as isointense(1/6,16.67％)on fat suppression-T2WI,5(5/6,83.33％)as high signals but 1(1/6,16.67％)as slightly hyperintensity on diffusion weighted imaging.Significant enhancements of lesions(6/6,100％)were noticed on both enhanced CT and MRI.Conclusion The imaging manifestations of PUB had certain characteristics,which were helpful to diagnosis.

Objective Comprehensively analyzing the epilepsy-related genes by bioinformatics methods,and to explore their functions based on network and pathway analysis.Methods I Collected epilepsy-related genes through OMIM,DisGeNET,GeneCards databases and literatures deposited in PUBMED.Performed gene ontology(GO)and pathway enrichment analysis using"ClusterProfiler"R package,and the correlation between pathways was identified through pathway crosstalk analysis.Epilepsy-related genes were then mapped to human protein-protein interaction network(PPIN)to obtain epilepsy-specific PPIN,and extracted the hub and potential genes based on network topology.Results A total of 572 epilepsy-related genes were collected,642 significant GO biological process items and 80 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways,including learning,memory and cognition,were obtained by enrichment analysis.Based on PPIN analysis,10 hub genes of the epilepsy were extracted and most of them are gamma-aminobutyric acid(GABA)receptor genes.By integrating PPIN and WGCNA analysis,17 potential genes were extracted,involving heat shock protein,growth factor receptor binding protein,etc.Conclusion Epilepsy is a complex process,involving the abnormality of multiple functional genes,multiple biological processes and pathways are closely contact through multiple functional genes,and collectively lead to the occurrence of epilepsy.

Objective:To investigate the risk factors of non-valvular paroxysmal atrial fibrillation (NVPAF) with cerebral ischemic stroke(CIS) and analyze NVPAF by using left atrial automatic imaging (AFILA). Logistic regression model was established for left atrial(LA) function parameters.Methods:A total of 205 patients with NVPAF were included in the study and divided into the NVPAF group without ischemic stroke (154 patients) and the CIS group (51 patients). The clinical baseline data, blood biochemical results and AFILA ultrasound data of all patients were collected. Univariate analysis was performed to compare the above data between the two groups of patients. The independent risk factors were obtained by multivariate logistic regression analysis. Logistic regression model was compared with CHA2DS2-VASc scoring system in terms of area under ROC curve, sensitivity and specificity.Results:There were significant differences in age, CHA2DS2-VASc score, taking anticoagulant drugs, history of hypertension, diabetes and coronary heart disease, LAEF, S_R, S_CT, WBC, NEUT, HCY, UREA, NDD, NT-proBNP, Fibrinogen(Fib), Cardiac troponin I(cTnI) and NLR between the two groups (all P<0.05). The results of multifactor analysis showed that: age, hypertension, S_ CT, UREA, NLR, Fib and cTnI were independent risk factors associated with CIS in patients with paroxysmal atrial fibrillation[ OR value: 1.608 ( P=0.003), 3.821 ( P=0.019), 1.259 ( P=0.001), 1.326( P=0.001), 1.352 ( P=0.011), 1.502 ( P=0.042), 7.651( P=0.001)]. After adjusting for the age, sex and history of hypertension included in CHA2DS2-VASc score, S_CT significantly led to NVPAF complicated with stroke[ OR value 1.259 (1.095-1.447), P=0.001]. The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring (AUC of 0.931 vs 0.717, 95% CI: 0.896-0.967 vs 0.634-0.799, sensitivity of 0.883 vs 0.755, specificity of 0.849 vs 0.713, all P<0.001). Conclusions:Age, hypertension, S_CT, UREA, NLR, fibrinogen, cTnI are independently associated risk factors for patients with combined CIS; The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring model.And the sensitivity and specificity are high.

Metabolic-associated fatty liver disease (MAFLD), which is previously known as non-alcoholic fatty liver disease (NAFLD), represents a major health concern worldwide with limited therapy. Here, we provide evidence that ferroptosis, a novel form of regulated cell death characterized by iron-driven lipid peroxidation, was comprehensively activated in liver tissues from MAFLD patients. The canonical-GPX4 (cGPX4), which is the most important negative controller of ferroptosis, is downregulated at protein but not mRNA level. Interestingly, a non-canonical GPX4 transcript-variant is induced (inducible-GPX4, iGPX4) in MAFLD condition. The high fat-fructose/sucrose diet (HFFD) and methionine/choline-deficient diet (MCD)-induced MAFLD pathologies, including hepatocellular ballooning, steatohepatitis and fibrosis, were attenuated and aggravated, respectively, in cGPX4-and iGPX4-knockin mice. cGPX4 and iGPX4 isoforms also displayed opposing effects on oxidative stress and ferroptosis in hepatocytes. Knockdown of iGPX4 by siRNA alleviated lipid stress, ferroptosis and cell injury. Mechanistically, the triggered iGPX4 interacts with cGPX4 to facilitate the transformation of cGPX4 from enzymatic-active monomer to enzymatic-inactive oligomers upon lipid stress, and thus promotes ferroptosis. Co-immunoprecipitation and nano LC-MS/MS analyses confirmed the interaction between iGPX4 and cGPX4. Our results reveal a detrimental role of non-canonical GPX4 isoform in ferroptosis, and indicate selectively targeting iGPX4 may be a promising therapeutic strategy for MAFLD.

KRAS‒PDEδ interaction is revealed as a promising target for suppressing the function of mutant KRAS. The bottleneck in clinical development of PDEδ inhibitors is the poor antitumor activity of known chemotypes. Here, we identified novel spiro-cyclic PDEδ inhibitors with potent antitumor activity both in vitro and in vivo. In particular, compound 36l (K _D = 127 ± 16 nmol/L) effectively bound to PDEδ and interfered with KRAS-PDEδ interaction. It influenced the distribution of KRAS in Mia PaCa-2 cells, downregulated the phosphorylation of t-ERK and t-AKT and promoted apoptosis of the cells. The novel inhibitor 36l exhibited significant in vivo antitumor potency in pancreatic cancer patient-derived xenograft (PDX) models. It represents a promising lead compound for investigating the druggability of KRAS‒PDEδ interaction.