We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between e...We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between existing measurements and evaluations of this cross-section.Using an unfolding iteration method,^(63)Cu(γ,n)data were obtained with an uncertainty of less than 4%,and the inconsistencies between the available experimental data were discussed.Theγ-ray strength function of^(63)Cu(γ,n)was successfully extracted as an experimental constraint.We further calculated the cross-section of the radiative neutron capture reaction^(62)Cu(n,γ)using the TALYS code.Our calculation method enables the extraction of(n,γ)cross-sections for unstable nuclides.展开更多
目的探讨H3.3G34W、p63及SATB2在骨巨细胞瘤(giant cell tumor of bone,GCTB)中的表达情况及其联合应用对GCTB的诊断作用和价值。方法收集西安交通大学附属红会医院病理科2020年至2022年诊断的54例GCTB、83例非骨巨细胞瘤(non-giant cel...目的探讨H3.3G34W、p63及SATB2在骨巨细胞瘤(giant cell tumor of bone,GCTB)中的表达情况及其联合应用对GCTB的诊断作用和价值。方法收集西安交通大学附属红会医院病理科2020年至2022年诊断的54例GCTB、83例非骨巨细胞瘤(non-giant cell tumor of bone,NGCTB)(包含14例动脉瘤样骨囊肿、16例软骨母细胞瘤和53例非骨化性纤维瘤)患者的样本和病历资料,采用免疫组织化学EliVision法检测H3.3G34W、p63及SATB2的表达情况。通过χ^(2)检验判断H3.3G34W、p63及SATB2的阳性率在各组间是否存在统计学差异;通过Logistic回归分析建立包括H3.3G34W、p63及SATB2的联合诊断模型,通过受试者工作特征(ROC)曲线分析评价模型的诊断价值。结果H3.3G34W、p63及SATB2在GCTB组中阳性率分别为81.5%、90.7%、92.6%;在NGCTB组中阳性率分别为2.4%、28.9%、62.7%。与NGCTB组相比,GCTB组患者年龄显著较大[(41.222±14.849)vs.(16.566±9.439);P<0.001],女性比男性患病率更高(51.9%vs.48.1%,P<0.001)。与NGCTB组相比,GCTB组中H3.3G34W(81.5%vs.2.4%,P<0.001);p63(90.7%vs.28.9%,P<0.001)和SATB2(92.6%vs.62.7%,P<0.001)的阳性率更高。单因素Logistic回归分析构建单因素预测模型,同时行ROC曲线分析,表明年龄(AUC=92.9%,P<0.001)、性别(AUC=64.5%,P=0.004)、H3.3G34W阳性率(AUC=89.5%,P<0.001)、p63阳性率(AUC=80.9%,P<0.001)、SATB2阳性率(AUC=65.0%,P=0.003)是GCTB诊断的独立预测因素。进一步的多因素Logistic回归分析构建混合预测模型,并行ROC曲线分析,发现混合模型展现出比单因素模型更好的预测价值(AUC=98.4%,P<0.001)。结论H3.3G34W、p63及SATB2是有效诊断GCTB的分子标记物,且三者联合应用更能提高GCTB的诊断预测效能。展开更多
基金supported by the National Key Research and Development Program(Nos.2023YFA1606901 and 2022YFA1602400)National Natural Science Foundation of China(Nos.U2230133,12275338,and 12388102)Open Fund of the CIAE Key Laboratory of Nuclear Data(No.JCKY2022201C152).
文摘We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between existing measurements and evaluations of this cross-section.Using an unfolding iteration method,^(63)Cu(γ,n)data were obtained with an uncertainty of less than 4%,and the inconsistencies between the available experimental data were discussed.Theγ-ray strength function of^(63)Cu(γ,n)was successfully extracted as an experimental constraint.We further calculated the cross-section of the radiative neutron capture reaction^(62)Cu(n,γ)using the TALYS code.Our calculation method enables the extraction of(n,γ)cross-sections for unstable nuclides.
文摘目的探讨H3.3G34W、p63及SATB2在骨巨细胞瘤(giant cell tumor of bone,GCTB)中的表达情况及其联合应用对GCTB的诊断作用和价值。方法收集西安交通大学附属红会医院病理科2020年至2022年诊断的54例GCTB、83例非骨巨细胞瘤(non-giant cell tumor of bone,NGCTB)(包含14例动脉瘤样骨囊肿、16例软骨母细胞瘤和53例非骨化性纤维瘤)患者的样本和病历资料,采用免疫组织化学EliVision法检测H3.3G34W、p63及SATB2的表达情况。通过χ^(2)检验判断H3.3G34W、p63及SATB2的阳性率在各组间是否存在统计学差异;通过Logistic回归分析建立包括H3.3G34W、p63及SATB2的联合诊断模型,通过受试者工作特征(ROC)曲线分析评价模型的诊断价值。结果H3.3G34W、p63及SATB2在GCTB组中阳性率分别为81.5%、90.7%、92.6%;在NGCTB组中阳性率分别为2.4%、28.9%、62.7%。与NGCTB组相比,GCTB组患者年龄显著较大[(41.222±14.849)vs.(16.566±9.439);P<0.001],女性比男性患病率更高(51.9%vs.48.1%,P<0.001)。与NGCTB组相比,GCTB组中H3.3G34W(81.5%vs.2.4%,P<0.001);p63(90.7%vs.28.9%,P<0.001)和SATB2(92.6%vs.62.7%,P<0.001)的阳性率更高。单因素Logistic回归分析构建单因素预测模型,同时行ROC曲线分析,表明年龄(AUC=92.9%,P<0.001)、性别(AUC=64.5%,P=0.004)、H3.3G34W阳性率(AUC=89.5%,P<0.001)、p63阳性率(AUC=80.9%,P<0.001)、SATB2阳性率(AUC=65.0%,P=0.003)是GCTB诊断的独立预测因素。进一步的多因素Logistic回归分析构建混合预测模型,并行ROC曲线分析,发现混合模型展现出比单因素模型更好的预测价值(AUC=98.4%,P<0.001)。结论H3.3G34W、p63及SATB2是有效诊断GCTB的分子标记物,且三者联合应用更能提高GCTB的诊断预测效能。
