In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nucl...In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nuclear energy as a viable energy source.Among these processes,the separation and recovery of Pu(Ⅳ)from high-level liquid waste(HLLW)hold paramount significance in terms of safety and strategic implications.Herein,this work focused on the synthesis of two acid-and radiation-resistant pyridine-based sp^(2)c-COFs(COF-IHEP3 and COF-IHEP4),followed by the creation of two pyridine-based ionized sp^(2)c-COFs named COF-IHEP3-CH_(3)NO_(3)and COF-IHEP4-CH3NO3through post-modification.These materials have potential anion exchange capacity for the selective separation of Pu(Ⅳ)in highly acidic conditions.Notably,in 8 mol/L nitric acid solution,COF-IHEP3-CH3NO3demonstrated the capability to eliminate plutonium within 20 min in 98%removal efficiency with a Kdvalue of 2450 m L/g.Experimental and theoretical analysis suggest that the ionized sp^(2)c-COFs exhibit exceptional stability,selectivity,and prevention of secondary contamination towards Pu(Ⅳ)in the presence of multiple ions environments.In short,this work provides an appropriate anion exchange strategy to design ionic sp^(2)c-COFs as a promising platform for Pu(Ⅳ)recovery from HLLW.展开更多
BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To...BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.展开更多
目的慢性肝病患者常表现出独特的血流动力学异常与代谢紊乱,术后液体管理面临诸多挑战,尤其是术后入住重症监护室(intensive care unit,ICU)的重症患者,亟待深入探究术后液体治疗方案与预后之间的关系。方法本研究基于MIMIC-IV数据库中2...目的慢性肝病患者常表现出独特的血流动力学异常与代谢紊乱,术后液体管理面临诸多挑战,尤其是术后入住重症监护室(intensive care unit,ICU)的重症患者,亟待深入探究术后液体治疗方案与预后之间的关系。方法本研究基于MIMIC-IV数据库中2414名慢性肝病、接受手术治疗,并术后转入ICU的患者,对纳排后最终得到的2143名患者数据进行回顾性队列研究。采用多变量调整Logistic回归模型,分析术后转入ICU首日液体治疗方案与术后7天死亡风险的关联,并通过限制性立方样条(restricted cubic spline,RCS)分析剂量-反应关系。结果多因素分析指出限制性补液为独立保护因素,相较于非限制性补液组,限制性补液显著降低了术后7天死亡率(6.4%vs 12.4%,OR=0.44,95%CI:0.22~0.88,P=0.021)。减少了机械通气的使用(42.9%vs 72.3%,OR=0.29,95%CI:0.24~0.35,P<0.001)和ICU停留时长(1.86 d vs 3.47 d,OR=0.81,95%CI:0.78~0.84,P<0.001)。RCS曲线显示,术后首日液体入量与术后7天死亡风险呈现J型曲线关系,拐点为1850 mL,超过该阈值后,术后7天死亡风险随之增加。亚组分析结果表明,限制性补液的保护作用在不同年龄、合并症群体中均呈现出一致性。结论慢性肝病患者术后首日采取限制性补液方案可有效降低短期死亡风险,且液体入量与7天死亡风险呈非线性剂量效应关联,液体入量超过1850 mL时,死亡风险显著升高。展开更多
本研究探讨了无人机巡检系统与组串智能 IV 融合诊断系统在光伏电站运维中的应用及其技术优势。通过分析无人机巡检系统的飞行平台、任务设备、地面控制站和通信系统,以及组串智能 IV 诊断系统的数据采集、数据分析处理和云端数据库,揭...本研究探讨了无人机巡检系统与组串智能 IV 融合诊断系统在光伏电站运维中的应用及其技术优势。通过分析无人机巡检系统的飞行平台、任务设备、地面控制站和通信系统,以及组串智能 IV 诊断系统的数据采集、数据分析处理和云端数据库,揭示了两者融合在提高巡检效率、准确诊断故障和降低运维成本方面的显著效果。实际应用案例表明,该系统有效提升了光伏电站的运维水平,为光伏电站智能化运维提供了有力支持。展开更多
BACKGROUND Stage IV pancreatic cancer(PC)has a poor prognosis and lacks individualized prognostic tools.Current survival prediction models are limited,and there is a need for more accurate,personalized methods.The Sur...BACKGROUND Stage IV pancreatic cancer(PC)has a poor prognosis and lacks individualized prognostic tools.Current survival prediction models are limited,and there is a need for more accurate,personalized methods.The Surveillance,Epidemiology,and End Results(SEER)database offers a valuable resource for studying large patient cohorts,yet machine learning-based nomograms for stage IV PC prognosis remain underexplored.This study hypothesizes that a machine learning-based nomogram can predict cancer-specific survival(CSS)and overall survival(OS)with high accuracy in stage IV PC patients.AIM To construct and validate a machine learning-based nomogram for predicting survival in stage IV PC patients using real-world data.METHODS Clinical data from stage IV PC patients diagnosed via pathology from 2000 to 2019 INTRODUCTION Pancreatic cancer(PC)is a significant human health issue and,by 2025,is projected to surpass breast cancer as the third leading cause of cancer-related deaths[1].In the United States,an estimated 66440 new cases and 51750 deaths due to PC were reported in 2024.PC is often asymptomatic in its early stages,with more than half of patients presenting with distant organ metastasis at the time of initial diagnosis[2].Consequently,the prognosis is very poor,with a 5-year relative survival rate of only 12.8%[2]In clinical practice,considerable heterogeneity in survival outcomes has been observed among patients with stage IV PC,highlighting the need for an individualized survival prediction tool for this population.Nomograms,which are visual tools incorporating multiple prognostic factors to predict patient survival,aid in person-alized treatment planning and clinical decision-making and are widely used in cancer prognosis evaluation[3-6].Machine learning,a core technique within artificial intelligence,employs algorithms to analyze data,learn from patterns,and predict real-world events with high accuracy,and is increasingly applied in health assessment,medical decision-making,prognosis,and personalized treatment[7-9].This study leverages the large sample size and comprehensive clinical data from the United State Surveillance,Epidemiology,and End Results(SEER)database to develop a prognostic nomogram for stage IV PC patients using machine learning,with the aim of providing individualized prognostic assessments to improve clinical decision-making.展开更多
BACKGROUND Radial head fractures constitute approximately one-third of all elbow fractures,significantly impacting the young and active population.While open reduction and internal fixation is the preferred treatment ...BACKGROUND Radial head fractures constitute approximately one-third of all elbow fractures,significantly impacting the young and active population.While open reduction and internal fixation is the preferred treatment for displaced fractures,its high complication rate in comminuted fractures has led to the increasing use of radial head arthroplasty(RHA).RHA provides improved functional outcomes with fewer complications,yet its long-term efficacy remains a topic of debate.AIM To evaluate the functional outcomes of patients undergoing RHA with a modular metallic prosthesis for comminuted Mason type III and IV radial head fractures.METHODS A prospective and retrospective hospital-based study was conducted at Dayanand Medical College and Hospital,Ludhiana over 32 months(January 2021-August 2023).A total of 26 patients with Mason type III and IV fractures were included,with six retrospective and 20 prospective cases.Functional outcomes were assessed using the Mayo Elbow Performance Score(MEPS),elbow range of motion,pain via Visual Analog Scale,and activities of daily living at immediate postoperative,three-month,and six-month follow-ups.RESULTS MEPS at 6 months follow up for 4 cases(15.38%)had good scores,and 22 cases(84.62%)had excellent scores,with a mean±SD of 97.31±6.67.Comparisons showed significant improvement from immediate post-operative to 3 months(P<0.0001),from immediate post-operative to 6 months(P<0.0001),and between 3 months and 6 months(P<0.0001).None of the patients had elbow instability after radial head replacement and 22 cases(84.62%)had no complications,while 3 cases(11.54%)had a stiff elbow,and 1 case(3.85%)had heterotopic ossification.CONCLUSION RHA is an effective treatment for comminuted radial head fractures,providing stable elbow function with minimal complications.展开更多
目的:鉴于脓毒症的高发病率和高病死率,早期识别高风险患者并及时干预至关重要,而现有死亡风险预测模型在操作、适用性和预测长期预后等方面均存在不足。本研究旨在探讨脓毒症患者死亡的危险因素,构建近期和远期死亡风险预测模型。方法...目的:鉴于脓毒症的高发病率和高病死率,早期识别高风险患者并及时干预至关重要,而现有死亡风险预测模型在操作、适用性和预测长期预后等方面均存在不足。本研究旨在探讨脓毒症患者死亡的危险因素,构建近期和远期死亡风险预测模型。方法:从美国重症监护医学信息数据库IV(Medical Information Mart for Intensive Care-IV,MIMIC-IV)中选取符合脓毒症3.0诊断标准的人群,按7?3的比例随机分为建模组和验证组,分析患者的基线资料。采用单因素Cox回归分析和全子集回归确定脓毒症患者死亡的危险因素并筛选出构建预测模型的变量。分别用时间依赖性曲线下面积(area under the curve,AUC)、校准曲线和决策曲线评估模型的区分度、校准度和临床实用性。结果:共纳入14240例脓毒症患者,28 d和1年病死率分别为21.45%(3054例)和36.50%(5198例)。高龄、女性、高感染相关器官衰竭评分(sepsis-related organ failure assessment,SOFA)、高简明急性生理学评分(simplified acute physiology score II,SAPS II)、心率快、呼吸频率快、脓毒症休克、充血性心力衰竭、慢性阻塞性肺疾病、肝脏疾病、肾脏疾病、糖尿病、恶性肿瘤、高白细胞计数(white blood cell count,WBC)、长凝血酶原时间(prothrombin time,PT)、高血肌酐(serum creatinine,SCr)水平均为脓毒症死亡的危险因素(均P<0.05)。由PT、呼吸频率、体温、合并恶性肿瘤、合并肝脏疾病、脓毒症休克、SAPS II及年龄8个变量构建的模型,其28 d和1年生存的AUC分别为0.717(95%CI 0.710~0.724)和0.716(95%CI 0.707~0.725)。校准曲线和决策曲线表明该模型具有良好的校准度及较好的临床应用价值。结论:基于MIMIC-IV建立的脓毒症患者近期和远期死亡风险预测模型有较好的识别能力,对患者预后风险评估及干预治疗具有一定的临床参考意义。展开更多
基金supported by the National Natural Science Foundation of China(Nos.U2067212,22176191)the National Science Fund for Distinguished Young Scholars(No.21925603)。
文摘In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nuclear energy as a viable energy source.Among these processes,the separation and recovery of Pu(Ⅳ)from high-level liquid waste(HLLW)hold paramount significance in terms of safety and strategic implications.Herein,this work focused on the synthesis of two acid-and radiation-resistant pyridine-based sp^(2)c-COFs(COF-IHEP3 and COF-IHEP4),followed by the creation of two pyridine-based ionized sp^(2)c-COFs named COF-IHEP3-CH_(3)NO_(3)and COF-IHEP4-CH3NO3through post-modification.These materials have potential anion exchange capacity for the selective separation of Pu(Ⅳ)in highly acidic conditions.Notably,in 8 mol/L nitric acid solution,COF-IHEP3-CH3NO3demonstrated the capability to eliminate plutonium within 20 min in 98%removal efficiency with a Kdvalue of 2450 m L/g.Experimental and theoretical analysis suggest that the ionized sp^(2)c-COFs exhibit exceptional stability,selectivity,and prevention of secondary contamination towards Pu(Ⅳ)in the presence of multiple ions environments.In short,this work provides an appropriate anion exchange strategy to design ionic sp^(2)c-COFs as a promising platform for Pu(Ⅳ)recovery from HLLW.
文摘BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.
文摘目的慢性肝病患者常表现出独特的血流动力学异常与代谢紊乱,术后液体管理面临诸多挑战,尤其是术后入住重症监护室(intensive care unit,ICU)的重症患者,亟待深入探究术后液体治疗方案与预后之间的关系。方法本研究基于MIMIC-IV数据库中2414名慢性肝病、接受手术治疗,并术后转入ICU的患者,对纳排后最终得到的2143名患者数据进行回顾性队列研究。采用多变量调整Logistic回归模型,分析术后转入ICU首日液体治疗方案与术后7天死亡风险的关联,并通过限制性立方样条(restricted cubic spline,RCS)分析剂量-反应关系。结果多因素分析指出限制性补液为独立保护因素,相较于非限制性补液组,限制性补液显著降低了术后7天死亡率(6.4%vs 12.4%,OR=0.44,95%CI:0.22~0.88,P=0.021)。减少了机械通气的使用(42.9%vs 72.3%,OR=0.29,95%CI:0.24~0.35,P<0.001)和ICU停留时长(1.86 d vs 3.47 d,OR=0.81,95%CI:0.78~0.84,P<0.001)。RCS曲线显示,术后首日液体入量与术后7天死亡风险呈现J型曲线关系,拐点为1850 mL,超过该阈值后,术后7天死亡风险随之增加。亚组分析结果表明,限制性补液的保护作用在不同年龄、合并症群体中均呈现出一致性。结论慢性肝病患者术后首日采取限制性补液方案可有效降低短期死亡风险,且液体入量与7天死亡风险呈非线性剂量效应关联,液体入量超过1850 mL时,死亡风险显著升高。
文摘本研究探讨了无人机巡检系统与组串智能 IV 融合诊断系统在光伏电站运维中的应用及其技术优势。通过分析无人机巡检系统的飞行平台、任务设备、地面控制站和通信系统,以及组串智能 IV 诊断系统的数据采集、数据分析处理和云端数据库,揭示了两者融合在提高巡检效率、准确诊断故障和降低运维成本方面的显著效果。实际应用案例表明,该系统有效提升了光伏电站的运维水平,为光伏电站智能化运维提供了有力支持。
基金Supported by Mianyang Health and Health Committee 2023 Scientific Research Project,No.202309Chengdu University of Traditional Chinese Medicine University-Hospital Joint Innovation Fund,No.LH202402010Mianyang Chinese Medicine Association 2024 Traditional Chinese Medicine Inheritance and Innovation Science and Technology Project,No.MYSZYYXH-202426.
文摘BACKGROUND Stage IV pancreatic cancer(PC)has a poor prognosis and lacks individualized prognostic tools.Current survival prediction models are limited,and there is a need for more accurate,personalized methods.The Surveillance,Epidemiology,and End Results(SEER)database offers a valuable resource for studying large patient cohorts,yet machine learning-based nomograms for stage IV PC prognosis remain underexplored.This study hypothesizes that a machine learning-based nomogram can predict cancer-specific survival(CSS)and overall survival(OS)with high accuracy in stage IV PC patients.AIM To construct and validate a machine learning-based nomogram for predicting survival in stage IV PC patients using real-world data.METHODS Clinical data from stage IV PC patients diagnosed via pathology from 2000 to 2019 INTRODUCTION Pancreatic cancer(PC)is a significant human health issue and,by 2025,is projected to surpass breast cancer as the third leading cause of cancer-related deaths[1].In the United States,an estimated 66440 new cases and 51750 deaths due to PC were reported in 2024.PC is often asymptomatic in its early stages,with more than half of patients presenting with distant organ metastasis at the time of initial diagnosis[2].Consequently,the prognosis is very poor,with a 5-year relative survival rate of only 12.8%[2]In clinical practice,considerable heterogeneity in survival outcomes has been observed among patients with stage IV PC,highlighting the need for an individualized survival prediction tool for this population.Nomograms,which are visual tools incorporating multiple prognostic factors to predict patient survival,aid in person-alized treatment planning and clinical decision-making and are widely used in cancer prognosis evaluation[3-6].Machine learning,a core technique within artificial intelligence,employs algorithms to analyze data,learn from patterns,and predict real-world events with high accuracy,and is increasingly applied in health assessment,medical decision-making,prognosis,and personalized treatment[7-9].This study leverages the large sample size and comprehensive clinical data from the United State Surveillance,Epidemiology,and End Results(SEER)database to develop a prognostic nomogram for stage IV PC patients using machine learning,with the aim of providing individualized prognostic assessments to improve clinical decision-making.
文摘BACKGROUND Radial head fractures constitute approximately one-third of all elbow fractures,significantly impacting the young and active population.While open reduction and internal fixation is the preferred treatment for displaced fractures,its high complication rate in comminuted fractures has led to the increasing use of radial head arthroplasty(RHA).RHA provides improved functional outcomes with fewer complications,yet its long-term efficacy remains a topic of debate.AIM To evaluate the functional outcomes of patients undergoing RHA with a modular metallic prosthesis for comminuted Mason type III and IV radial head fractures.METHODS A prospective and retrospective hospital-based study was conducted at Dayanand Medical College and Hospital,Ludhiana over 32 months(January 2021-August 2023).A total of 26 patients with Mason type III and IV fractures were included,with six retrospective and 20 prospective cases.Functional outcomes were assessed using the Mayo Elbow Performance Score(MEPS),elbow range of motion,pain via Visual Analog Scale,and activities of daily living at immediate postoperative,three-month,and six-month follow-ups.RESULTS MEPS at 6 months follow up for 4 cases(15.38%)had good scores,and 22 cases(84.62%)had excellent scores,with a mean±SD of 97.31±6.67.Comparisons showed significant improvement from immediate post-operative to 3 months(P<0.0001),from immediate post-operative to 6 months(P<0.0001),and between 3 months and 6 months(P<0.0001).None of the patients had elbow instability after radial head replacement and 22 cases(84.62%)had no complications,while 3 cases(11.54%)had a stiff elbow,and 1 case(3.85%)had heterotopic ossification.CONCLUSION RHA is an effective treatment for comminuted radial head fractures,providing stable elbow function with minimal complications.
文摘目的:鉴于脓毒症的高发病率和高病死率,早期识别高风险患者并及时干预至关重要,而现有死亡风险预测模型在操作、适用性和预测长期预后等方面均存在不足。本研究旨在探讨脓毒症患者死亡的危险因素,构建近期和远期死亡风险预测模型。方法:从美国重症监护医学信息数据库IV(Medical Information Mart for Intensive Care-IV,MIMIC-IV)中选取符合脓毒症3.0诊断标准的人群,按7?3的比例随机分为建模组和验证组,分析患者的基线资料。采用单因素Cox回归分析和全子集回归确定脓毒症患者死亡的危险因素并筛选出构建预测模型的变量。分别用时间依赖性曲线下面积(area under the curve,AUC)、校准曲线和决策曲线评估模型的区分度、校准度和临床实用性。结果:共纳入14240例脓毒症患者,28 d和1年病死率分别为21.45%(3054例)和36.50%(5198例)。高龄、女性、高感染相关器官衰竭评分(sepsis-related organ failure assessment,SOFA)、高简明急性生理学评分(simplified acute physiology score II,SAPS II)、心率快、呼吸频率快、脓毒症休克、充血性心力衰竭、慢性阻塞性肺疾病、肝脏疾病、肾脏疾病、糖尿病、恶性肿瘤、高白细胞计数(white blood cell count,WBC)、长凝血酶原时间(prothrombin time,PT)、高血肌酐(serum creatinine,SCr)水平均为脓毒症死亡的危险因素(均P<0.05)。由PT、呼吸频率、体温、合并恶性肿瘤、合并肝脏疾病、脓毒症休克、SAPS II及年龄8个变量构建的模型,其28 d和1年生存的AUC分别为0.717(95%CI 0.710~0.724)和0.716(95%CI 0.707~0.725)。校准曲线和决策曲线表明该模型具有良好的校准度及较好的临床应用价值。结论:基于MIMIC-IV建立的脓毒症患者近期和远期死亡风险预测模型有较好的识别能力,对患者预后风险评估及干预治疗具有一定的临床参考意义。
