The novel Fe-N co-doped ordered mesoporous carbon with high catalytic activity in m-cresol removal was prepared by urea-assisted impregnation and simple pyrolysis method.During the preparation of the Fe-NC catalyst,th...The novel Fe-N co-doped ordered mesoporous carbon with high catalytic activity in m-cresol removal was prepared by urea-assisted impregnation and simple pyrolysis method.During the preparation of the Fe-NC catalyst,the complexation of N elements in urea could anchor Fe,and the formation of C3N4during urea pyrolysis could also prevent migration and aggregation of Fe species,which jointly improve the dispersion and stability of Fe.The FeN4sites and highly dispersed Fe nanoparticles synergistically trigger the dual-site peroxymonosulfate (PMS) activation for highly efficient m-cresol degradation,while the ordered mesoporous structure of the catalyst could improve the mass transfer rate of the catalytic process,which together promote catalytic degradation of m-cresol by PMS activation.Reactive oxygen species (ROS) analytic experiments demonstrate that the system degrades m-cresol by free radical pathway mainly based on SO_(4)^(-)·and·OH,and partially based on·OH as the active components,and a possible PMS activation mechanism by 5Fe-50 for m-cresol degradation was proposed.This study can provide theoretical guidance for the preparation of efficient and stable catalysts for the degradation of organic pollutants by activated PMS.展开更多
BACKGROUND Neutrophil-lymphocyte ratio(NLR),fibrosis index based on four factors(Fib4),aspartate aminotransferase-to-platelet ratio index(APRI)can be used for prognostic evaluation of hepatocellular carcinoma.However,...BACKGROUND Neutrophil-lymphocyte ratio(NLR),fibrosis index based on four factors(Fib4),aspartate aminotransferase-to-platelet ratio index(APRI)can be used for prognostic evaluation of hepatocellular carcinoma.However,no study has established an individualized prediction model for the prognosis of hepatocellular carcinoma based on these factors.AIM To screen the factors that affect the prognosis of hepatocellular carcinoma and establish a nomogram model that predicts postoperative liver failure after hepatic resection in patients with hepatocellular carcinoma.METHODS In total,220 patients with hepatocellular carcinoma treated in our hospital from January 2022 to January 2023 were selected.They were divided into 154 participants in the modeling cohort,and 66 in the validation cohort.Comparative analysis of the changes in NLR,Fib4,and APRI levels in 154 patients with hepatocellular carcinoma before liver resection and at 3 mo,6 mo,and 12 mo postoperatively was conducted.Binary logistic regression to analyze the influencing factors on the occurrence of liver failure in hepatocellular carcinoma patients,roadmap prediction modeling,and validation,patient work characteristic curves(ROCs)to evaluate the predictive efficacy of the model,calibration curves to assess the consistency,and decision curve analysis(DCA)to evaluate the model’s validity were also conducted.RESULTS Binary logistic regression showed that Child-Pugh grading,Surgical site,NLR,Fib4,and APRI were all risk factors for liver failure after hepatic resection in patients with hepatocellular carcinoma.The modeling cohort built a column-line graph model,and the area under the ROC curve was 0.986[95%confidence in terval(CI):0.963-1.000].The patients in the validation cohort utilized the column-line graph to predict the probability of survival in the validation cohort and plotted the ROC curve with an area under the curve of the model of 0.692(95%CI:0.548-0.837).The deviation of the actual outcome curves from the calibration curves of the column-line plots generated by the modeling and validation cohorts was small,and the DCA confirmed the validity.CONCLUSION NLR,Fib4,and APRI independently influence posthepatectomy liver failure in patients with hepatocellular carcinoma.The column-line graph prediction model exhibited strong prognostic capability,with substantial concordance between predicted and actual events.展开更多
基金gratefully acknowledge the financial support of the National Natural Science Foundation of China(22108145 and 21978143)the Shandong Province Natural Science Foundation(ZR2020QB189)+1 种基金State Key Laboratory of Heavy Oil Processing(SKLHOP202203008)the Talent Foundation funded by Province and Ministry Co-construction Collaborative Innovation Center of Eco-chemical Engineering(STHGYX2201).
文摘The novel Fe-N co-doped ordered mesoporous carbon with high catalytic activity in m-cresol removal was prepared by urea-assisted impregnation and simple pyrolysis method.During the preparation of the Fe-NC catalyst,the complexation of N elements in urea could anchor Fe,and the formation of C3N4during urea pyrolysis could also prevent migration and aggregation of Fe species,which jointly improve the dispersion and stability of Fe.The FeN4sites and highly dispersed Fe nanoparticles synergistically trigger the dual-site peroxymonosulfate (PMS) activation for highly efficient m-cresol degradation,while the ordered mesoporous structure of the catalyst could improve the mass transfer rate of the catalytic process,which together promote catalytic degradation of m-cresol by PMS activation.Reactive oxygen species (ROS) analytic experiments demonstrate that the system degrades m-cresol by free radical pathway mainly based on SO_(4)^(-)·and·OH,and partially based on·OH as the active components,and a possible PMS activation mechanism by 5Fe-50 for m-cresol degradation was proposed.This study can provide theoretical guidance for the preparation of efficient and stable catalysts for the degradation of organic pollutants by activated PMS.
文摘BACKGROUND Neutrophil-lymphocyte ratio(NLR),fibrosis index based on four factors(Fib4),aspartate aminotransferase-to-platelet ratio index(APRI)can be used for prognostic evaluation of hepatocellular carcinoma.However,no study has established an individualized prediction model for the prognosis of hepatocellular carcinoma based on these factors.AIM To screen the factors that affect the prognosis of hepatocellular carcinoma and establish a nomogram model that predicts postoperative liver failure after hepatic resection in patients with hepatocellular carcinoma.METHODS In total,220 patients with hepatocellular carcinoma treated in our hospital from January 2022 to January 2023 were selected.They were divided into 154 participants in the modeling cohort,and 66 in the validation cohort.Comparative analysis of the changes in NLR,Fib4,and APRI levels in 154 patients with hepatocellular carcinoma before liver resection and at 3 mo,6 mo,and 12 mo postoperatively was conducted.Binary logistic regression to analyze the influencing factors on the occurrence of liver failure in hepatocellular carcinoma patients,roadmap prediction modeling,and validation,patient work characteristic curves(ROCs)to evaluate the predictive efficacy of the model,calibration curves to assess the consistency,and decision curve analysis(DCA)to evaluate the model’s validity were also conducted.RESULTS Binary logistic regression showed that Child-Pugh grading,Surgical site,NLR,Fib4,and APRI were all risk factors for liver failure after hepatic resection in patients with hepatocellular carcinoma.The modeling cohort built a column-line graph model,and the area under the ROC curve was 0.986[95%confidence in terval(CI):0.963-1.000].The patients in the validation cohort utilized the column-line graph to predict the probability of survival in the validation cohort and plotted the ROC curve with an area under the curve of the model of 0.692(95%CI:0.548-0.837).The deviation of the actual outcome curves from the calibration curves of the column-line plots generated by the modeling and validation cohorts was small,and the DCA confirmed the validity.CONCLUSION NLR,Fib4,and APRI independently influence posthepatectomy liver failure in patients with hepatocellular carcinoma.The column-line graph prediction model exhibited strong prognostic capability,with substantial concordance between predicted and actual events.
