Objective:To identify the main components of Huanglian Jiedu Decoction(HLJDD)using ultra-high-performance liquid chromatography-quadrupole-time of flight-mass spectrometry(UPLC-Q-TOF-MS),and to explore the potential mechanism of action of HLJDD in the treatment of gouty arthritis(GA)using network pharmacology and molecular docking methods.Methods:We identi-fied the chemical components of HLJDD by combining UPLC-Q-TOF-MS data acquired in both positive and negative ion modes with reference standards,relevant literature,and database searches.We analyzed the potential therapeutic mechanism of HLJDD for GA by using network pharmacology to determine the intersection targets between the active ingredients of HLJDD and GA for further enrich-ment analysis and visual network mapping.The binding affinity of the active ingredients with the intersection targets was validated through molecular docking.Results:A total of 47 components were identified by UPLC-Q-TOF-MS;54 key components of HLJDD for GA treatment and 37 intersection targets were determined by net-work pharmacology;and the top 10 key targets by Degree value were obtained by protein-protein interaction analysis.The Gene On-tology functional enrichment analysis revealed 20 biological pro-cesses,7 cellular components,and 8 molecular functions.The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis demonstrated 96 GA-related intervention pathways,in which inflammatory signaling pathways such as interleukin-17(IL-17)and tu-mor necrosis factor(TNF)were involved.Molecular docking verified that the key components of HLJDD had high binding affinity with the core targets.Conclusion:The identified key components in HLJDD,such as phellodendrine,coptisine,wogonin,and β-sitosterol,may alleviate GA by regulating multiple core targets in the IL-17 and TNF pathways,such as PTSG2,which provides a theoretical ba-sis for future investigation into the mechanism of action of HLJDD.

OBJECTIVES: To investigate the effects of quercetin on cuproptosis and L-type calcium currents in the myocardium of diabetic rats. METHODS: Forty SD rats were randomized into control group and diabetic model groups. The rat models of diabetes mellitus (DM) induced by high-fat and high-sugar diet combined with streptozotocin (STZ) injection were further divided into DM model group, quercetin treatment group, and empagliflozin treatment group (n=10). Blood glucose and body weight were measured every other week, and cardiac function of the rats was evaluated using echocardiography. HE staining, Sirius red staining, and wheat germ agglutinin (WGA) analysis were used to observe the changes in myocardial histomorphology, and serum copper levels and myocardial FDX1 expression were detected. In cultured rat cardiomyocyte H9c2 cells with high-glucose exposure, the effects of quercetin and elesclomol, alone or in combination, on intracellular CK-MB and LDH levels and FDX1 expression were assessed, and the changes in L-type calcium currents were analyzed using patch-clamp technique. RESULTS: The diabetic rats exhibited elevated blood glucose, reduced body weight, impaired left ventricular function, increased serum copper levels and myocardial FDX1 expression, decreased L-type calcium currents, and prolonged action potential duration. Quercetin and empagliflozin treatment significantly lowered blood glucose, improved body weight, and restored cardiac function of the diabetic rats, and compared with empagliflozin, quercetin more effectively reduced serum copper levels, downregulated FDX1 expression, and enhanced myocardial L-type calcium currents in diabetic rats. In H9c2 cells, high glucose exposure significantly increased myocardial expressions of FDX1, CK-MB and LDH, which were effectively lowered by quercetin treatment; Elesclomol further elevated FDX1, CK-MB and LDH levels in the exposed cells, and these changes were not significantly affected by the application of quercetin. CONCLUSIONS Quercetin ameliorates myocardial injury in diabetic rats possibly by suppressing myocardial cuproptosis signaling and restoring L-type calcium channel activity.
Animals ; Quercetin/pharmacology* ; Calcium Channels, L-Type/metabolism* ; Diabetes Mellitus, Experimental/metabolism* ; Rats, Sprague-Dawley ; Rats ; Myocytes, Cardiac/drug effects* ; Myocardium/pathology* ; Male

Objective:To investigate the predictive value of radiomics features derived from dynamic contrast-enhanced MRI (DCE-MRI) based on habitat imaging technology for pathological complete response after neoadjuvant therapy (NAT) for breast cancer.Methods:All patients were female, aged 25-67 years. Patients were stratified into training ( n=83) and validation ( n=36) sets via stratified random sampling (7∶3 ratio). Pathological complete remission (pCR) and non-pathological complete remission (non-pCR) were defined using the Miller-Payne grading system. All patients underwent DCE-MRI before NAT. ITK-Snap software was used to outline the region of interest (ROI), the imaging histological features of the entire tumor region were extracted and screened, a traditional imaging histological model for predicting post-NAT pCR (ROI overall model) was constructed; the tumor region was divided into three subregions using habitat imaging technology, and the imaging histological features within ROI subregion 1, ROI subregion 2, and ROI subregion 3 were extracted and screened, and the habitat imaging model for predicting post-NAT pCR were constructed (ROI subregion 1 model, ROI subregion 2 model, ROI subregion 3 model). Univariate logistic regression identified clinical predictors of pCR for clinical model construction. Combined models integrating clinical predictors and habitat imaging features were established. The efficacy of each model in predicting pCR after NAT in breast cancer was evaluated using receiver operating characteristic curves and area under the curve (AUC), and the efficacy of clinical application of the models was evaluated using decision curve analysis (DCA). Results:Of the 119 patients, 74 were pCR patients, with 52 in the training set and 22 in the validation set, and 45 were non-pCR patients, with 31 in the training set and 14 in the validation set. Logistic regression analysis showed that human epidermal growth factor receptor 2 status ( OR=0.254, 95% CI 0.093-0.697, P=0.008) was an independent predictor of pCR after NAT, and this was used to construct a clinical prediction model. The predictive efficacy of ROI subregion 1 model and ROI subregion 2 model in the habitat model was higher than that of the traditional imaging histology model (ROI overall model), with AUCs of 0.805, 0.748,0.728 for the training set and 0.776,0.718,0.708 for the validation set, respectively. The combined clinical prediction model for predicting pCR after NAT in breast cancer had AUCs of 0.877 and 0.818 for the training and validation sets, respectively. DCA showed a higher net benefit for the combined model than for the traditional imaging histology model and the habitat imaging histology model. Conclusion:Compared with the traditional method of extracting the entire tumor region, extracting radiomics features from DCE-MRI subregions based on habitat imaging technology can improve the predictive performance of NAT efficacy in breast cancer.

Objective To investigate the clinical value of baseline 18F-fluorodeoxyglucose(18F-FDG)PET/CT metabolic parame-ters and certain clinical indicators in predicting the prognosis of patients with diffuse large B-cell lymphoma(DLBCL).Methods A retrospec-tive analysis was conducted on the baseline 18 F-FDG PET/CT data of 73 DLBCL patients who received R-CHOP treatment.Patients were divided into progression group(24 cases)and non-progression group(49 cases)based on disease progression within 2 years post-treatment.The lesion maximum standardized uptake value(SUVmax),tumour-to-liver blood pool SUVmax ratio(LLR)and tumour-to-mediastinal blood pool SUVmax ratio(L-BPR)were analyzed using receiver operating characteristic(ROC)curves.Kaplan-Meier(K-M)survival curves analysis were performed based on the optimal thresholds of SUVmax,LLR and L-BPR.x2 tests were used to analyze and compare the relationship between each parameter and disease progression.Indicators that were significant in the x2 tests were included in the multivariate Cox regression analysis.Results The area under the curve(AUC)for LLR,L-BPR,and SUVmax were 0.920,0.914,and 0.848,respectively,with optimal thresholds of 7.41,10.67,and 14.70.Based on these thresholds,K-M survival curves analysis showed that the 2-year progression-free survival(PFS)rates for DLBCL patients were 79.2％vs 30.8％(P＜0.001),74.3％vs 22.0％(P=0.009),and 79.5％vs 51.6％(P=0.002),respectively.Significant differences were observed between the progression and non-progression groups in terms of LLR,L-BPR,SUVmax,extranodal involvement,international prognostic index(IPI)score,lactate dehydrogenase(LDH)level,Eastern Cooperative Oncology Group(ECOG)score,and β2-microglobulin(β2-MG)levels(P＜0.05).Multivariate Cox regression analysis revealed that the IPI score and LLR were independent predictors affecting the 2-year PFS of DLBCL patients(P＜0.05).Conclusion Baseline 18F-FDG PET/CT metabolic parameter LLR and IPI score are inde-pendent factors for predicting the prognosis of DLBCL patients.

Objective To investigate the clinical value of baseline 18F-fluorodeoxyglucose(18F-FDG)PET/CT metabolic parame-ters and certain clinical indicators in predicting the prognosis of patients with diffuse large B-cell lymphoma(DLBCL).Methods A retrospec-tive analysis was conducted on the baseline 18 F-FDG PET/CT data of 73 DLBCL patients who received R-CHOP treatment.Patients were divided into progression group(24 cases)and non-progression group(49 cases)based on disease progression within 2 years post-treatment.The lesion maximum standardized uptake value(SUVmax),tumour-to-liver blood pool SUVmax ratio(LLR)and tumour-to-mediastinal blood pool SUVmax ratio(L-BPR)were analyzed using receiver operating characteristic(ROC)curves.Kaplan-Meier(K-M)survival curves analysis were performed based on the optimal thresholds of SUVmax,LLR and L-BPR.x2 tests were used to analyze and compare the relationship between each parameter and disease progression.Indicators that were significant in the x2 tests were included in the multivariate Cox regression analysis.Results The area under the curve(AUC)for LLR,L-BPR,and SUVmax were 0.920,0.914,and 0.848,respectively,with optimal thresholds of 7.41,10.67,and 14.70.Based on these thresholds,K-M survival curves analysis showed that the 2-year progression-free survival(PFS)rates for DLBCL patients were 79.2％vs 30.8％(P＜0.001),74.3％vs 22.0％(P=0.009),and 79.5％vs 51.6％(P=0.002),respectively.Significant differences were observed between the progression and non-progression groups in terms of LLR,L-BPR,SUVmax,extranodal involvement,international prognostic index(IPI)score,lactate dehydrogenase(LDH)level,Eastern Cooperative Oncology Group(ECOG)score,and β2-microglobulin(β2-MG)levels(P＜0.05).Multivariate Cox regression analysis revealed that the IPI score and LLR were independent predictors affecting the 2-year PFS of DLBCL patients(P＜0.05).Conclusion Baseline 18F-FDG PET/CT metabolic parameter LLR and IPI score are inde-pendent factors for predicting the prognosis of DLBCL patients.

Objective:To investigate the predictive value of radiomics features derived from dynamic contrast-enhanced MRI (DCE-MRI) based on habitat imaging technology for pathological complete response after neoadjuvant therapy (NAT) for breast cancer.Methods:All patients were female, aged 25-67 years. Patients were stratified into training ( n=83) and validation ( n=36) sets via stratified random sampling (7∶3 ratio). Pathological complete remission (pCR) and non-pathological complete remission (non-pCR) were defined using the Miller-Payne grading system. All patients underwent DCE-MRI before NAT. ITK-Snap software was used to outline the region of interest (ROI), the imaging histological features of the entire tumor region were extracted and screened, a traditional imaging histological model for predicting post-NAT pCR (ROI overall model) was constructed; the tumor region was divided into three subregions using habitat imaging technology, and the imaging histological features within ROI subregion 1, ROI subregion 2, and ROI subregion 3 were extracted and screened, and the habitat imaging model for predicting post-NAT pCR were constructed (ROI subregion 1 model, ROI subregion 2 model, ROI subregion 3 model). Univariate logistic regression identified clinical predictors of pCR for clinical model construction. Combined models integrating clinical predictors and habitat imaging features were established. The efficacy of each model in predicting pCR after NAT in breast cancer was evaluated using receiver operating characteristic curves and area under the curve (AUC), and the efficacy of clinical application of the models was evaluated using decision curve analysis (DCA). Results:Of the 119 patients, 74 were pCR patients, with 52 in the training set and 22 in the validation set, and 45 were non-pCR patients, with 31 in the training set and 14 in the validation set. Logistic regression analysis showed that human epidermal growth factor receptor 2 status ( OR=0.254, 95% CI 0.093-0.697, P=0.008) was an independent predictor of pCR after NAT, and this was used to construct a clinical prediction model. The predictive efficacy of ROI subregion 1 model and ROI subregion 2 model in the habitat model was higher than that of the traditional imaging histology model (ROI overall model), with AUCs of 0.805, 0.748,0.728 for the training set and 0.776,0.718,0.708 for the validation set, respectively. The combined clinical prediction model for predicting pCR after NAT in breast cancer had AUCs of 0.877 and 0.818 for the training and validation sets, respectively. DCA showed a higher net benefit for the combined model than for the traditional imaging histology model and the habitat imaging histology model. Conclusion:Compared with the traditional method of extracting the entire tumor region, extracting radiomics features from DCE-MRI subregions based on habitat imaging technology can improve the predictive performance of NAT efficacy in breast cancer.

Objective To investigate the protective effect of PF-562271,a FAK inhibitor,against aging platelet-induced injury in human umbilical vein endothelial cells(HUVECs).Methods Cultured HUVECs were treated with vehicle,lipopolysaccharide(LPS),LPS+aging platelets,or LPS+aging platelets+PF-562271.The changes in protein expressions of FAK,pFAK and PECAM-1 in the treated cells were detected using Western blotting and immunofluorescence assay,and the level of reactive oxygen species(ROS)was detected with flow cytometry.The changes of barrier function of the cells were assessed with cell permeability test and transendothelial cell resistance test.RT-qPCR was used to analyze mRNA expressions of inflammatory factors,and pro-inflammatory cytokine levels in the culture supernatants was determined with enzyme-linked immunosorbent assay.Immunofluorescence assay was used to examine the effect of the ROS inhibitor vitamin C on PECAM-1 expression in the cells with different treatments.Results Treatment of HUVECs with LPS and aging platelets significantly increased cellular protein expressions of FAK,pFAK and PECAM-1,which were effectively lowered by addition of PF-562271(P<0.05).LPS and aged platelets obviously enhanced ROS production in the cells,which was inhibited by the addition of PF-562271(P<0.001).PF-562271 significantly alleviated the damage of endothelial cell barrier function of the cells caused by LPS and aging platelets(P<0.01).The expressions of TNF-α,IL-6 and IL-8 in HUVECs increased significantly after exposure to LPS and aging platelets,and were obviously lowered after treatment with PF-562271(P<0.05).Treatment with vitamin C significantly decreased the expression of PECAM-1 protein in the cells(P<0.01).Conclusion The FAK inhibitor PF-562271 alleviates endothelial cell damage induced by LPS and aging platelets by lowering cellular oxidative stress levels and reducing inflammatory responses.

Objective To investigate the protective effect of PF-562271,a FAK inhibitor,against aging platelet-induced injury in human umbilical vein endothelial cells(HUVECs).Methods Cultured HUVECs were treated with vehicle,lipopolysaccharide(LPS),LPS+aging platelets,or LPS+aging platelets+PF-562271.The changes in protein expressions of FAK,pFAK and PECAM-1 in the treated cells were detected using Western blotting and immunofluorescence assay,and the level of reactive oxygen species(ROS)was detected with flow cytometry.The changes of barrier function of the cells were assessed with cell permeability test and transendothelial cell resistance test.RT-qPCR was used to analyze mRNA expressions of inflammatory factors,and pro-inflammatory cytokine levels in the culture supernatants was determined with enzyme-linked immunosorbent assay.Immunofluorescence assay was used to examine the effect of the ROS inhibitor vitamin C on PECAM-1 expression in the cells with different treatments.Results Treatment of HUVECs with LPS and aging platelets significantly increased cellular protein expressions of FAK,pFAK and PECAM-1,which were effectively lowered by addition of PF-562271(P<0.05).LPS and aged platelets obviously enhanced ROS production in the cells,which was inhibited by the addition of PF-562271(P<0.001).PF-562271 significantly alleviated the damage of endothelial cell barrier function of the cells caused by LPS and aging platelets(P<0.01).The expressions of TNF-α,IL-6 and IL-8 in HUVECs increased significantly after exposure to LPS and aging platelets,and were obviously lowered after treatment with PF-562271(P<0.05).Treatment with vitamin C significantly decreased the expression of PECAM-1 protein in the cells(P<0.01).Conclusion The FAK inhibitor PF-562271 alleviates endothelial cell damage induced by LPS and aging platelets by lowering cellular oxidative stress levels and reducing inflammatory responses.

Objective Taking typical cases of Western medicine as an example,this paper explores the connection between Chinese and Western medicine on the understanding of tongue elephants.Methods After collecting the literature with tongue diagram attached to the clinical imaging column published in NEJM magazine,extracting the symptoms,signs and Western medicine disease information recorded in the literature,the tongue diagram was diagnosed from three aspects:tongue quality,tongue moss and sublingual meridians,and whether the symptoms and signs of tongue correspond to a certain diagnosis result,and the results were analyzed.Results A total of 48 articles were included,including 6 literature on abnormal tongue dynamics,which could correspond to abnormal tongue morphology in traditional Chinese medicine.Thirty-four cases of abnormal tongue shape were found.Among them,12 cases could be diagnosed with corresponding TCM tongue diagnosis,including 7 cases of abnormal tongue shape and 5 cases of abnormal coating.The remaining 22 cases were secondary changes in tongue structure.There were 8 articles on abnormal tongue color,including 1 abnormal tongue color,1 abnormal sublingual chord,and 6 abnormal lichen color.Conclusion Starting from the form and function,explore the connection between Chinese medicine and Western medicine in their understanding of tongue diagnosis,and promote the objectification and standardization of Chinese medicine tongue diagnosis.

Objective To establish a lumbar radiography image quality control model by using the deep learning algorithm and evaluate clinical images in real time and retrospectively based on the developed model.Methods The anteroposterior,lateral and oblique lumbar radiographs of 1389 patients collected between January 2018 to February 2021 at the The First Affiliated Hospital of Wenzhou Medical University were analyzed.The anatomical structures in the lumbar X-ray images were segmented using a full convolutional neural network based on U-Net,and the segmentation algorithm was utilized to establish an automatic evaluation model to detect substandard images.Dice similarity coefficient(DSC)was used to evaluate the performance of the model,and the lumbar radiography images were statistically evaluated after the application of the model.Results The accuracy of the model on the validation set was 0.971-0.990(0.98±0.10),the sensitivity was 0.714-0.933(0.86±0.13),and the specificity was 0.995-1.000(0.99±0.12).The quality control model had an excellent rate of 28.8%,an intermediate rate of 54.8%,and a failure rate of 16.4%for lumbar spine radiography in 2022.Conclusion The lumbar spine X-ray image quality control model based on artificial intelligence realizes accurate segmentation of lumbar spine anatomical structures and makes accurate evaluation of image quality,which is helpful to ensure the standardization of lumbar spine X-ray radiography operation by