目的探讨PHLPP2与EGFR+TP53共突变晚期肺腺癌(LUAD)患者靶向联合化疗疗效及与铁死亡的关系。方法回顾2018年8月至2023年8月的98例行靶向联合化疗治疗EGFR+TP53共突变晚期LUAD患者资料。分析PHLPP2突变情况,根据预后分为预后不良组(n=47...目的探讨PHLPP2与EGFR+TP53共突变晚期肺腺癌(LUAD)患者靶向联合化疗疗效及与铁死亡的关系。方法回顾2018年8月至2023年8月的98例行靶向联合化疗治疗EGFR+TP53共突变晚期LUAD患者资料。分析PHLPP2突变情况,根据预后分为预后不良组(n=47)和预后良好组(n=51)。限制性立方样条(RCS)模型分析铁死亡指标与预后不良的剂量反应关系。比较不同PHLPP2突变类型下铁死亡指标水平,及其与预后不良的关系。结果PHLPP2突变率为30.61%,主要为错义突变和点突变。预后不良组血清铁(SF)、丙二醛(MDA)、活性氧(ROS)低于预后良好组(P<0.05),谷胱甘肽过氧化酶4(GPX4)、谷胱甘肽(GSH)、PHLPP2突变类型高于预后良好组(P<0.05)。预后不良风险与SF、GPX4、GSH、MDA和ROS均呈非线性剂量-反应关系(P_(for non linear)<0.05)。野生型SF、MDA、ROS高于突变型(P<0.05),GPX4、GSH低于突变型(P<0.05)。不同PHLPP2突变类型、铁死亡指标下预后不良存在差异(P<0.05)。结论PHLPP2突变影响靶向联合化疗治疗EGFR+TP53共突变晚期LUAD临床疗效,且与铁死亡存在相关性。展开更多
In educational settings,instructors often lead students through hands-on software projects,sometimes engaging two different schools or departments.How can such collaborations be made more efficient,and how can student...In educational settings,instructors often lead students through hands-on software projects,sometimes engaging two different schools or departments.How can such collaborations be made more efficient,and how can students truly experience the importance of teamwork and the impact of organizational structure on project complexity?To answer these questions,we introduce the requirement-driven organization structure(R-DOS)approach,which tightly couples software requirements with the actual development process.By extending problem-frames modeling and focusing on requirements,R-DOS allows educators and students to(1)diagnose structural flaws early,(2)prescribe role-level and communication fixes,and(3)observe-in real time-how poor structure can derail a project while good structure accelerates learning and delivery.展开更多
Methods of quantum information processing often appear in terms of specially selected states.For example,mutually unbiased bases(MUBs)and symmetric informationally complete measurements are widely applied.Finite frame...Methods of quantum information processing often appear in terms of specially selected states.For example,mutually unbiased bases(MUBs)and symmetric informationally complete measurements are widely applied.Finite frames have found use in many areas including quantum information.Due to its specific inner structure,a single equiangular tight frame(ETF)allows one to formulate criteria to detect non-classical correlations.This study aims to approach entanglement detection with the use of mutually unbiased ETFs.Such frames are an interesting generalization of widely recognized MUBs.It still uses rank-one operators,but the number of outcomes can exceed the dimensionality.Several approaches are considered including separability criteria and entanglement witnesses.Separability criteria for multipartite systems are finally obtained.展开更多
Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel da...Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel damage identification method that utilizes limited strain data points,significantly reducing installation,maintenance,and data analysis costs compared to traditional distributed sensor networks.The approach integrates finite element(FE)modeling to generate capacity curves through pushover analysis,incorporates noise-augmented datasets for Artificial Neural Network(ANN)training,and classifies structural conditions into four damage levels:Operational(OP),Immediate Occupancy(IO),Life Safety(LS),and Collapse Prevention(CP).To evaluate the method’s accuracy and efficiency,it was applied to two reinforced concrete(RC)frames;a single-story frame tested experimentally under cyclic loading and a three-story frame analyzed under various lateral load patterns.Strain data from selected beam and column ends were used as ANN inputs,while the corresponding damage classes served as outputs.Confusion matrix results demonstrated high true positive rates(>85%for the single-story and>90%for the three-story frame),even with a reduced number of sensors.The model also exhibited strong robustness to White Gaussian Noise(SNR=2.5-5 dB)and generalized effectively to nonlinear time-history analyses under scaled ground motions(PGA=0.1-1.0 g).Feature selection using the MRMR and ANOVA algorithms further enhanced computational efficiency.Overall,the proposed ANN-based framework has strong potential for real-time structural health monitoring applications.展开更多
文摘目的探讨PHLPP2与EGFR+TP53共突变晚期肺腺癌(LUAD)患者靶向联合化疗疗效及与铁死亡的关系。方法回顾2018年8月至2023年8月的98例行靶向联合化疗治疗EGFR+TP53共突变晚期LUAD患者资料。分析PHLPP2突变情况,根据预后分为预后不良组(n=47)和预后良好组(n=51)。限制性立方样条(RCS)模型分析铁死亡指标与预后不良的剂量反应关系。比较不同PHLPP2突变类型下铁死亡指标水平,及其与预后不良的关系。结果PHLPP2突变率为30.61%,主要为错义突变和点突变。预后不良组血清铁(SF)、丙二醛(MDA)、活性氧(ROS)低于预后良好组(P<0.05),谷胱甘肽过氧化酶4(GPX4)、谷胱甘肽(GSH)、PHLPP2突变类型高于预后良好组(P<0.05)。预后不良风险与SF、GPX4、GSH、MDA和ROS均呈非线性剂量-反应关系(P_(for non linear)<0.05)。野生型SF、MDA、ROS高于突变型(P<0.05),GPX4、GSH低于突变型(P<0.05)。不同PHLPP2突变类型、铁死亡指标下预后不良存在差异(P<0.05)。结论PHLPP2突变影响靶向联合化疗治疗EGFR+TP53共突变晚期LUAD临床疗效,且与铁死亡存在相关性。
基金supported by the National Natural Science Foundation of China(No.62362006)Guangxi Science and Technology Project(Key Research&Development)(No.GuiKeAB24010343)+1 种基金Guangxi“Bagui Scholar”Teams for Innovation and Research,Innovation Project of Guangxi Graduate Education(No.YCSW2025193)Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing.
文摘In educational settings,instructors often lead students through hands-on software projects,sometimes engaging two different schools or departments.How can such collaborations be made more efficient,and how can students truly experience the importance of teamwork and the impact of organizational structure on project complexity?To answer these questions,we introduce the requirement-driven organization structure(R-DOS)approach,which tightly couples software requirements with the actual development process.By extending problem-frames modeling and focusing on requirements,R-DOS allows educators and students to(1)diagnose structural flaws early,(2)prescribe role-level and communication fixes,and(3)observe-in real time-how poor structure can derail a project while good structure accelerates learning and delivery.
文摘Methods of quantum information processing often appear in terms of specially selected states.For example,mutually unbiased bases(MUBs)and symmetric informationally complete measurements are widely applied.Finite frames have found use in many areas including quantum information.Due to its specific inner structure,a single equiangular tight frame(ETF)allows one to formulate criteria to detect non-classical correlations.This study aims to approach entanglement detection with the use of mutually unbiased ETFs.Such frames are an interesting generalization of widely recognized MUBs.It still uses rank-one operators,but the number of outcomes can exceed the dimensionality.Several approaches are considered including separability criteria and entanglement witnesses.Separability criteria for multipartite systems are finally obtained.
基金funded by UTM Fundamental Research Grant(PY/2024/01221,Cost centre no.:Q.J130000.3822.23H73)HiCoE Grant Scheme(Cost centre no.:R.J130000.7822.4J738)。
文摘Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel damage identification method that utilizes limited strain data points,significantly reducing installation,maintenance,and data analysis costs compared to traditional distributed sensor networks.The approach integrates finite element(FE)modeling to generate capacity curves through pushover analysis,incorporates noise-augmented datasets for Artificial Neural Network(ANN)training,and classifies structural conditions into four damage levels:Operational(OP),Immediate Occupancy(IO),Life Safety(LS),and Collapse Prevention(CP).To evaluate the method’s accuracy and efficiency,it was applied to two reinforced concrete(RC)frames;a single-story frame tested experimentally under cyclic loading and a three-story frame analyzed under various lateral load patterns.Strain data from selected beam and column ends were used as ANN inputs,while the corresponding damage classes served as outputs.Confusion matrix results demonstrated high true positive rates(>85%for the single-story and>90%for the three-story frame),even with a reduced number of sensors.The model also exhibited strong robustness to White Gaussian Noise(SNR=2.5-5 dB)and generalized effectively to nonlinear time-history analyses under scaled ground motions(PGA=0.1-1.0 g).Feature selection using the MRMR and ANOVA algorithms further enhanced computational efficiency.Overall,the proposed ANN-based framework has strong potential for real-time structural health monitoring applications.
