ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

Objective:To assess the cytotoxicity of self-adhesive resin cement RelyXTM U200 on human periodontal ligament fibro-blasts(HPDLFs)under different light treatment modes.Methods:The self-adhesive resin cement RelyXTM U200 was cured by immediate light(A),intermittent light(B),delayed light(C)and no light(D)treatment respectively.The HPDLFs were cultured with the specimen extracts under different light modes.The proliferation ability and apoptosis level of the cells in the groups were detected by CCK-8 test and flow cytometry apoptosis test.SPSS 20.0 software was used to analyze the cytotoxicity of specimens to HPDLFs.Results:At 24 h after light treatment the cytoxicity(grade)of group A,B,C and D was 1,2,3 and 4,at 72 h 1,2,2 and 3,respectively.At 72 h,the apoptosis index(％)of the cells in A,B,C and D groups was 6.38％±0.94％,16.34％±1.67％,24.13％±1.43％and 38.34％±2.75％respecitvely.Conclusion:The cytotoxicity of self-adhesive resin cement is the greatest under no light treatment mode and the least under immediate light treatment mode.

Objective:To explore the predictive value of ultrasonic shear wave elastography (SWE) parameters and pathological characteristics on the status of human epidermal growth factor receptor 2 (HER2), which is difficult to be determined by immunohistochemistry (IHC) in breast cancer, and to construct a nomogram model.Methods:A retrospective case-control study was conducted. One hundred and fifteen cases of breast cancer diagnosed and treated in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from September 2018 to April 2022 were selected, and their HER2 was evaluated as IHC 2+; the HER2 expression status was determined by fluorescence in situ hybridization (FISH) detection, including 23 HER2 positive cases and 92 HER2 negative cases. The ultrasound SWE parameters [including maximum shear wave velocity (V max), mean shear wave velocity (V mean), median shear wave velocity (V median), minimum shear wave velocity (V min)] and clinicopathological characteristics between HER2 positive and negative groups were compared. The variables with statistically significant differences ( P < 0.05) between groups were included in a multivariate logistic regression model, the independent risk factors for HER2 positivity were screened, and a nomogram model was constructed based on these independent risk factors. With the FISH test results as the gold standard, the efficacy of nomogram in judging HER2 positivity in breast cancer which was difficult to be identified by IHC was evaluated with the receiver operating characteristic (ROC) curve; the accuracy and clinical net benefit of the nomogram model were evaluated using calibration curve and decision curve analysis (DCA), respectively. Results:The patients were all female, aged (56±13) years, ranging from 30 to 88 years old. V max [ M ( Q1, Q3)] [8.54 (7.38, 9.47) m/s vs. 6.46 (5.07, 8.42) m/s], V mean [(5.41±0.78) m/s vs. (4.53±1.22) m/s], V median [5.06 (4.48, 5.52) m/s vs. 4.35 (3.42, 4.96) m/s], V min [3.35 (2.68, 3.88) m/s vs. 2.59 (2.11, 3.34) m/s], the proportion of patients with axillary lymph node metastasis [56.5% (13/23) vs. 22.8% (21/92)], and the Ki-67 positivity index [35% (30%, 55%) vs. 25% (15%, 35%)] in the HER2 positive group were higher than those in the HER2 negative group, and the differences were statistically significant (all P < 0.05); There was no statistically significant difference in age, lesion location, pathological type, vascular invasion, nerve invasion and long diameter, short diameter, echo, regular shape, clear boundary, posterior echo, calcification, blood flow grading, Breast Imaging Report and Data System (BI-RADS) classification detected by ultrasound between the two groups (all P > 0.05). Multivariate logistic regression analysis showed that increased ultrasound V max ( OR = 1.786, 95% CI: 1.283-2.485, P = 0.001) and axillary lymph node metastasis ( OR = 4.185, 95% CI: 1.327-13.197, P = 0.015) and elevated Ki-67 positivity index ( OR = 1.042, 95% CI: 1.014-1.071, P = 0.003) were independent risk factors for HER2 positivity. ROC curve analysis showed that the area under the curve (AUC) of HER2 positive breast cancer which was difficult to be determined by IHC was 0.816 (95% CI: 0.732-0.883), that was higher than 0.712 (95% CI: 0.620-0.794) of V max, 0.601 (95% CI: 0.504-0.692) of axillary lymph node metastasis and 0.706 (95% CI: 0.613-0.788) of Ki-67 positivity index based on the nomogram constructed by the above independent risk factors, with statistically significant differences (all P < 0.05). The calibration curve showed that the predicted probability of the nomogram model was close to the actual probability, and DCA indicated that the clinical net benefit of the model was good. Conclusions:The nomogram constructed based on ultrasonic SWE parameter V max, axillary lymph node metastasis and Ki-67 positivity index has a good predictive effect on HER2 status of breast cancer which is difficult to be determined by IHC.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective:To assess the cytotoxicity of self-adhesive resin cement RelyXTM U200 on human periodontal ligament fibro-blasts(HPDLFs)under different light treatment modes.Methods:The self-adhesive resin cement RelyXTM U200 was cured by immediate light(A),intermittent light(B),delayed light(C)and no light(D)treatment respectively.The HPDLFs were cultured with the specimen extracts under different light modes.The proliferation ability and apoptosis level of the cells in the groups were detected by CCK-8 test and flow cytometry apoptosis test.SPSS 20.0 software was used to analyze the cytotoxicity of specimens to HPDLFs.Results:At 24 h after light treatment the cytoxicity(grade)of group A,B,C and D was 1,2,3 and 4,at 72 h 1,2,2 and 3,respectively.At 72 h,the apoptosis index(％)of the cells in A,B,C and D groups was 6.38％±0.94％,16.34％±1.67％,24.13％±1.43％and 38.34％±2.75％respecitvely.Conclusion:The cytotoxicity of self-adhesive resin cement is the greatest under no light treatment mode and the least under immediate light treatment mode.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective:To explore the predictive value of ultrasonic shear wave elastography (SWE) parameters and pathological characteristics on the status of human epidermal growth factor receptor 2 (HER2), which is difficult to be determined by immunohistochemistry (IHC) in breast cancer, and to construct a nomogram model.Methods:A retrospective case-control study was conducted. One hundred and fifteen cases of breast cancer diagnosed and treated in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from September 2018 to April 2022 were selected, and their HER2 was evaluated as IHC 2+; the HER2 expression status was determined by fluorescence in situ hybridization (FISH) detection, including 23 HER2 positive cases and 92 HER2 negative cases. The ultrasound SWE parameters [including maximum shear wave velocity (V max), mean shear wave velocity (V mean), median shear wave velocity (V median), minimum shear wave velocity (V min)] and clinicopathological characteristics between HER2 positive and negative groups were compared. The variables with statistically significant differences ( P < 0.05) between groups were included in a multivariate logistic regression model, the independent risk factors for HER2 positivity were screened, and a nomogram model was constructed based on these independent risk factors. With the FISH test results as the gold standard, the efficacy of nomogram in judging HER2 positivity in breast cancer which was difficult to be identified by IHC was evaluated with the receiver operating characteristic (ROC) curve; the accuracy and clinical net benefit of the nomogram model were evaluated using calibration curve and decision curve analysis (DCA), respectively. Results:The patients were all female, aged (56±13) years, ranging from 30 to 88 years old. V max [ M ( Q1, Q3)] [8.54 (7.38, 9.47) m/s vs. 6.46 (5.07, 8.42) m/s], V mean [(5.41±0.78) m/s vs. (4.53±1.22) m/s], V median [5.06 (4.48, 5.52) m/s vs. 4.35 (3.42, 4.96) m/s], V min [3.35 (2.68, 3.88) m/s vs. 2.59 (2.11, 3.34) m/s], the proportion of patients with axillary lymph node metastasis [56.5% (13/23) vs. 22.8% (21/92)], and the Ki-67 positivity index [35% (30%, 55%) vs. 25% (15%, 35%)] in the HER2 positive group were higher than those in the HER2 negative group, and the differences were statistically significant (all P < 0.05); There was no statistically significant difference in age, lesion location, pathological type, vascular invasion, nerve invasion and long diameter, short diameter, echo, regular shape, clear boundary, posterior echo, calcification, blood flow grading, Breast Imaging Report and Data System (BI-RADS) classification detected by ultrasound between the two groups (all P > 0.05). Multivariate logistic regression analysis showed that increased ultrasound V max ( OR = 1.786, 95% CI: 1.283-2.485, P = 0.001) and axillary lymph node metastasis ( OR = 4.185, 95% CI: 1.327-13.197, P = 0.015) and elevated Ki-67 positivity index ( OR = 1.042, 95% CI: 1.014-1.071, P = 0.003) were independent risk factors for HER2 positivity. ROC curve analysis showed that the area under the curve (AUC) of HER2 positive breast cancer which was difficult to be determined by IHC was 0.816 (95% CI: 0.732-0.883), that was higher than 0.712 (95% CI: 0.620-0.794) of V max, 0.601 (95% CI: 0.504-0.692) of axillary lymph node metastasis and 0.706 (95% CI: 0.613-0.788) of Ki-67 positivity index based on the nomogram constructed by the above independent risk factors, with statistically significant differences (all P < 0.05). The calibration curve showed that the predicted probability of the nomogram model was close to the actual probability, and DCA indicated that the clinical net benefit of the model was good. Conclusions:The nomogram constructed based on ultrasonic SWE parameter V max, axillary lymph node metastasis and Ki-67 positivity index has a good predictive effect on HER2 status of breast cancer which is difficult to be determined by IHC.

ObjectiveTo investigate the induction of ferroptosis by polyphyllin Ⅱ （PPⅡ） in hepatocellular carcinoma HepG2 cells and its underlying mechanism. MethodThe effect of PPⅡ （0， 1.5， 3.0， 4.5， 6.0， 9.0， 18.0 mg·L^-1） on the in vitro proliferation of HepG2 cells was assessed using the methyl thiazolyl tetrazolium （MTT） assay. Colony formation ability of HepG2 cells was evaluated through a colony formation assay. Cell migration ability was assessed via a scratch assay. Lactate dehydrogenase （LDH） content in HepG2 cells was measured using a kit. Reactive oxygen species （ROS） levels in HepG2 cells were observed using a fluorescence inverted microscope. Malondialdehyde （MDA）， glutathione （GSH）， and free Fe²⁺ content in HepG2 cells were detected using respective kits. The mitochondrial ultrastructure in HepG2 cells was observed by transmission electron microscopy. The expression of ferroptosis-related proteins p53， solute carrier family 7 member 11 （SLC7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， and transferrin receptor 1 （TFR1） in HepG2 cells was detected using Western blot. ResultCompared with the control group， the PPⅡ treatment groups showed significantly decreased survival rate of HepG2 cells in a dose-dependent manner （P<0.01）， significantly reduced number of cell colonies （P<0.01）， significantly shortened scratch healing distance， inverse correlation of the migration distance with drug concentration （P<0.01）， significantly increased LDH leakage in cells （P<0.01）， significantly enhanced relative fluorescence intensity of intracellular ROS， and significantly increased accumulation of lipid peroxide MDA （P<0.01）， decreased intracellular GSH content with increasing drug concentration （P<0.01）， and significantly enhanced fluorescence intensity of FeRhoNox-1 in cells （P<0.01）. Moreover， cells exhibited vacuolation， and mitochondria showed significant shrinkage with reduced or even disappeared cristae. Compared with the results in the control group， the expression of p53， ACSL4， and TFR1 proteins significantly increased， while the expression of SLC7A11 and GPX4 proteins significantly decreased in the PPⅡ treatment groups （P<0.05）. ConclusionIn summary， PPⅡ induces ferroptosis in HepG2 cells by regulating the p53/SLC7A11/GPX4 signaling axis， promoting ACSL4 expression and Fe³⁺ uptake， leading to an imbalance in the antioxidant system.