Objective To investigate the clinical significance of the expression of antioxidant 1 copper chaperone protein(ATOX1)in hepatocellular carcinoma(HCC)and its relationship with tumor proliferation,migration and invasion.Methods The expression of ATOX1 mRNA in HCC cancer tissue and normal liver tissue was analyzed using the Human Genome Atlas database.Immunohistochemical experiment was used to detect the expression of ATOX1 in 15 cases of HCC cancer tissue and adjacent tissue.Human HCC cell lines Hep3B and HepG2 were divided into the control group(NC),the ATOX1 knockdown group 1(si-ATOX1#1)and the ATOX1 knockdown group 2(si-ATOX1#2).The effects of ATOX1 knockdown on the malignant biological behavior of HCC cells were observed through CCK-8 cell proliferation experiment,scratch experiment and Transwell invasion experiments.A nude mouse xenograft tumor model was constructed to analyze the effect of ATOX1 knockdown on the quality and volume of transplanted tumors.Western blot assay was used to detect the relationship between ATOX1 and JAK2/STAT3 pathway protein expression.Results Bioinformatics analysis showed that expression of ATOX1 mRNA in HCC cancer tissue was higher than that in adjacent normal tissue(P＜0.05).The immunohistochemical staining results showed that the positive rate of ATOX1 protein was higher in HCC cancer tissue than that in adjacent tissue(93.33%vs.13.33%,P＜0.01).In vitro experimental results showed that siRNA knockdown of ATOX1 protein expression in Hep3B and HepG2 cells significantly reduced the proliferation,migration and invasion abilities of cancer cells(P＜0.05).In vivo experiments in mice showed that the volume and weight of subcutaneous xenograft tumors were significantly smaller in the sh-ATOX1 group than those in the sh-con group(P＜0.05).The expression levels of JAK2/STAT3 pathway-related proteins p-JAK2,p-STAT3,CyclinD1 and MMP2 were significantly lower in the subcutaneous transplanted tumor tissue of the sh-ATOX1 group than that of the sh-con group(P＜0.05).Conclusion ATOX1 can promote the proliferation,migration and invasion of HCC through JAK2/STAT3 pathway,which can potentially become a potential tumor marker and therapeutic target.

Objective To provide pharmaceutical care for patients with hepatitis B cirrhosis by using the medication therapy management(MTM)model combined with Pharmaceutical Care Network Europe(PCNE),and to analyze the effectiveness of pharmaceutical care from clinical efficacy,safety,humanistic effect and drug-related problems(DRPs).Methods Patients with hepatitis B cirrhosis were randomly divided into the pharmaceutical care group and the control group who received only conventional treatment.Clinical pharmacists used MTM combined with PCNE to provide pharmaceutical care in the pharmaceutical care group.Economic effects,clinical indicators,safety,medication compliance and quality of life were compared between the two groups during the treatment and follow-up period.DRPs were analyzed in the pharmaceutical care group.Results The cost-utility ratio and clinical indicators in the pharmaceutical care group were better than those in the control group,and the adverse drug reactions of the former were statistically significant compared with the latter at the three months follow-up,and medication compliance and quality of life were statistically significant after intervention and during follow-up(P＜0.05).There were 52 DRPs in the pharmaceutical care group,mainly in the category of poor treatment outcome.The main reasons were poor drug selection and excessive usage and dosage.There were 46 DRPs accepted by intervention,and 45 DRPs were completely and partially solved.Conclusion The pharmaceutical care model of MTM combined with PCNE classification system for patients with hepatitis B cirrhosis played a positive role in the treatment and follow-up period.

Objective:To explore the value of amide proton transfer-weighted (APTw) imaging and intravoxel incoherent motion (IVIM) imaging for diagnosing and evaluating the pathological differentiation of cervix squamous cell carcinoma (CSCC).Methods:This study was a diagnostic trial. Totally 56 patients pathologically diagnosed with CSCC at the First Hospital of Lanzhou University from October 2021 to October 2022 were retrospectively collected, as the CSCC group. And 36 female healthy volunteers who underwent physical examinations at the First Hospital of Lanzhou University from October 2021 to October 2023 were recruited as the control group. CSCC patients were divided into well-moderately differentiated ( n=34) and poorly differentiated groups ( n=22). The region of interest was placed in the lesions of CSCC group and normal cervical stroma of control group, and the quantitative parameters for asymmetric magnetization transfer ratio (MTR asym) of APTw imaging and pure diffusion coefficient (D), false diffusion coefficient (D *) and perfusion fraction (f) for IVIM were obtained. The independent sample t test was used to compare the differences in quantitative parameters between the two groups, the logistic regression model was used to establish combined parameters for the quantitative parameters with statistical significance between the two groups. The receiver operator characteristic curve was used to evaluate the diagnostic efficacy of single quantitative parameters and combined parameters to distinguish the CSCC group from the control group, and the well-moderately differentiated group from the poorly differentiated group in CSCC patients. The area under the curve (AUC) was compared using the DeLong test. Results:There were significant differences in MTR asym, D and f between CSCC group and control group ( t=-9.79, 10.09, 11.35, P<0.001). Also, significant differences were found for MTR asym and D between the well-moderately differentiated and poorly differentiated group ( t=4.11, -3.76, P<0.001). There was no significant difference in other quantitative parameters ( P>0.05). When comparing the CSCC group and control group, the AUC (95% CI) of MTR asym, D, f and combined parameter (MTR asym+D+f) were 0.887 (0.804-0.944), 0.940 (0.871-0.979), 0.968 (0.909-0.993), 0.995 (0.950-1.000). The AUC of the combined parameter was higher than those of MTR asym and D, with statistical significance ( Z=3.07, 2.06, P=0.002, 0.040). When comparing the well-moderately differentiated and poorly differentiated group, the AUC (95% CI) of MTR asym, D, and combined parameter (MTR asym+D) were 0.789 (0.660-0.887), 0.775 (0.644-0.876), 0.852 (0.731-0.932). There was no significant difference between each two AUCs ( P>0.05). Conclusion:The quantitative parameters of APTw and IVIM imaging can be used to diagnose and preliminarily evaluate the pathological differentiation of CSCC. Joint parameters can improve the diagnostic efficiency of CSCC.

OBJECTIVE To explore the mechanisms of the flavonoids from new "Zhe Eight Flavors" Quzhou Fructus Aurantii(PTFC) against hepatocellular carcinoma based on the prediction of network pharmacology and experimental verification. METHODS From TCMSP, TCMID, ETCM, BATMAN-TCM and SwissTargetPrediction databases, the potential target proteins of PTFC, including naringin, narirutin and neohesperidin were collected. Based on the GeneCards, CTD, Disgenet, and OMIM databases, a set of target proteins for hepatocellular carcinoma was constructed. Taking the intersection of potential target proteins of PTFC and target proteins of hepatocellular carcinoma, key target proteins were obtained and a protein-protein interaction network was established. Besides, GO function and KEGG pathway enrichment analysis on the core target proteins was performed and a Compounds-Targets-Pathways-Disease network was constructed. Through proliferation, cloning, wound healing, and migration experiments, the effects of PTFC on the viability of HepG2 liver cancer cells were analyzed. Using fluorescence probe staining the impacts of PTFC on the mitochondrial membrane potential and apoptosis of HepG2 were observed. Finally, the validation of the regulatory effect of PTFC on the key predicted target PRKCA were carried out through RT-qPCR. RESULTS Based on network pharmacology, a total of 217 potential target proteins for PTFC were screened, with 59 intersecting target proteins related to diseases, including ALB, ESR1, PRKCA, and others. GO functional and KEGG pathway enrichment analysis revealed that the PTFC target proteins were involved in 193 biological processes and 13 cancer-related signaling pathways. Experimental results demonstrated that PTFC could impact the proliferation, cloning, wound healing, and migration abilities of liver cancer cells, leading to a decrease in mitochondrial membrane potential and promoting cell apoptosis. The results of RT-qPCR confirmed a significant downregulation of PRKCA expression by PTFC, validating the predictions made by network pharmacology analysis. CONCLUSION This study has revealed the potential molecular mechanism of PTFC treating hepatocellular carcinoma via the PRKCA target, laying the foundation for clinical application of PTFC.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.