目的本研究旨在分析治疗前D-二聚体水平和接受PD-1/PD-L1抑制剂治疗的晚期肿瘤患者长期预后的关系。方法在中国知网、万方、维普、Pubmed、Web of Science、Cochrane Library等数据库检索截止至2024年10月20日发表的相关文献,最终纳入6...目的本研究旨在分析治疗前D-二聚体水平和接受PD-1/PD-L1抑制剂治疗的晚期肿瘤患者长期预后的关系。方法在中国知网、万方、维普、Pubmed、Web of Science、Cochrane Library等数据库检索截止至2024年10月20日发表的相关文献,最终纳入6篇文献进行分析。结果在接受PD-1/PD-L1抑制剂治疗的晚期肿瘤患者中,与正常D-二聚体水平的患者相比,高D-二聚体水平患者的无进展生存期(progression free survival,PFS)(单因素分析:HR=1.89,95%CI:1.33~2.67,P=0.0004;多因素分析:HR=1.79,95%CI:1.18~2.72,P=0.006)和总生存期(overall survival,OS)显著缩短(单因素分析:HR=2.02,95%CI:1.60~2.56,P<0.00001;多因素分析:HR=2.08,95%CI:1.63~2.65,P<0.00001)。结论D-二聚体可作为预测接受PD-1/PD-L1抑制剂治疗肿瘤患者预后的潜在生物标志物。展开更多
In order to constrain whether the Lhasa–Qiangtang collision contributed to an early crustal thickening of the central Tibetan Plateau prior to the India–Asia collision,we present zircon LA–ICP–MS U–Pb ages,wholer...In order to constrain whether the Lhasa–Qiangtang collision contributed to an early crustal thickening of the central Tibetan Plateau prior to the India–Asia collision,we present zircon LA–ICP–MS U–Pb ages,wholerock geochemistry,and zircon Hf isotopic compositions of the newly discovered rhyolitic crystal tuffs from the Chuduoqu area in the eastern Qiangtang subterrane,central Tibet.Zircon U–Pb dating suggests that the Chuduoqu rhyolitic crystal tuffs were emplaced at ca.68 Ma.The Chuoduoqu rhyolitic crystal tuffs display high SiO_(2) and K2 O,and low MgO,Cr,and Ni.Combined with their zircon Hf isotopic data,we suggest that they were derived from partial melting of the juvenile lower crust,and the magma underwent fractional crystallization and limited upper continental crustal assimilation during its evolution prior to eruption.They should be formed in a post-collisional environment related to lithospheric mantle delamination.The Chuduoqu rhyolitic crystal tuffs could provide important constraints on the Late Cretaceous crustal thickening of the central Tibetan Plateau caused by the Lhasa–Qiangtang collision.展开更多
October 5,the ninth day of the ninth lunar month,was the day of the traditional Double Ninth Festival.Sanshui District of Foshan City in Guangdong organized a 1000-old-men feast that day.More than 1000 local senior ci...October 5,the ninth day of the ninth lunar month,was the day of the traditional Double Ninth Festival.Sanshui District of Foshan City in Guangdong organized a 1000-old-men feast that day.More than 1000 local senior citizens joined a series of activities during the Cultural Festival of Longevity.During the feast,Guangdong Committee on Ageing told our reporter that Guangdong would establish the old-age allowance (OAA) system throughout the province by 2015.展开更多
目的:利用机器学习算法预测影响脑卒中患者日常生活自理能力(activities of daily living,ADL)的风险因素,为其ADL管理决策提供参考。方法:对2015年1月—2019年2月在南京医科大学附属第一医院康复医学中心治疗的423例脑卒中患者进行回...目的:利用机器学习算法预测影响脑卒中患者日常生活自理能力(activities of daily living,ADL)的风险因素,为其ADL管理决策提供参考。方法:对2015年1月—2019年2月在南京医科大学附属第一医院康复医学中心治疗的423例脑卒中患者进行回顾性分析。根据Barthel指数(Barthel index,BI)评定量表,将患者分为ADL较好组(BI≥60分)和ADL较差组(BI<60分),并进行数据预处理。采用共线性诊断及最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)筛选特征变量。选择逻辑回归、支持向量机、随机森林(random forest,RF)、极限梯度提升及K最近邻5种机器学习算法进行预测建模,十倍交叉验证后,使用受试者工作特征曲线、受试者工作特征曲线下面积(area under curve,AUC)、精确召回率曲线、精确召回率曲线下的面积(area under the precision recall curve,PRAUC)、准确率、灵敏度、特异度分别对模型进行综合评估,引入Shapley加性解释(Shapley additive explanation,SHAP)对最优机器学习模型进行可解释化处理。结果:经LASSO回归分析后,确定16个特征变量用于构建机器学习模型。RF模型具有最高的AUC(0.74)、PRAUC(0.64)、准确率(0.97)、灵敏度(0.75)和特异度(0.97)。SHAP模型解释性分析显示,对ADL贡献度前5的特征中,Brunnstrom分期(下肢)的影响最为显著,其次是Brunnstrom分期(上肢)、D-二聚体、血清白蛋白水平及年龄。结论:RF模型预测脑卒中患者ADL的效能最优,为脑卒中患者ADL管理决策提供了有价值的参考。展开更多
基金funded by the National Natural Science Foundation of China(41272093)the Geological Survey Project(12120114080901)of China Geological Survey+4 种基金the Self-determined Foundation of Key Laboratory of Mineral Resources Evaluation in Northeast Asia,Ministry of Natural Resources(DBY-ZZ-19-04)the Shandong Provincial Natural Science Foundation of China(No.ZR2019PD017)the Natural Science Foundation of Liaoning Province(2020-BS-258)the Department of Education of Liaoning Province(LJ2020JCL010)a Discipline Innovation Team Project of Liaoning Technical University(LNTU20TD-14)。
文摘In order to constrain whether the Lhasa–Qiangtang collision contributed to an early crustal thickening of the central Tibetan Plateau prior to the India–Asia collision,we present zircon LA–ICP–MS U–Pb ages,wholerock geochemistry,and zircon Hf isotopic compositions of the newly discovered rhyolitic crystal tuffs from the Chuduoqu area in the eastern Qiangtang subterrane,central Tibet.Zircon U–Pb dating suggests that the Chuduoqu rhyolitic crystal tuffs were emplaced at ca.68 Ma.The Chuoduoqu rhyolitic crystal tuffs display high SiO_(2) and K2 O,and low MgO,Cr,and Ni.Combined with their zircon Hf isotopic data,we suggest that they were derived from partial melting of the juvenile lower crust,and the magma underwent fractional crystallization and limited upper continental crustal assimilation during its evolution prior to eruption.They should be formed in a post-collisional environment related to lithospheric mantle delamination.The Chuduoqu rhyolitic crystal tuffs could provide important constraints on the Late Cretaceous crustal thickening of the central Tibetan Plateau caused by the Lhasa–Qiangtang collision.
文摘October 5,the ninth day of the ninth lunar month,was the day of the traditional Double Ninth Festival.Sanshui District of Foshan City in Guangdong organized a 1000-old-men feast that day.More than 1000 local senior citizens joined a series of activities during the Cultural Festival of Longevity.During the feast,Guangdong Committee on Ageing told our reporter that Guangdong would establish the old-age allowance (OAA) system throughout the province by 2015.
文摘目的:利用机器学习算法预测影响脑卒中患者日常生活自理能力(activities of daily living,ADL)的风险因素,为其ADL管理决策提供参考。方法:对2015年1月—2019年2月在南京医科大学附属第一医院康复医学中心治疗的423例脑卒中患者进行回顾性分析。根据Barthel指数(Barthel index,BI)评定量表,将患者分为ADL较好组(BI≥60分)和ADL较差组(BI<60分),并进行数据预处理。采用共线性诊断及最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)筛选特征变量。选择逻辑回归、支持向量机、随机森林(random forest,RF)、极限梯度提升及K最近邻5种机器学习算法进行预测建模,十倍交叉验证后,使用受试者工作特征曲线、受试者工作特征曲线下面积(area under curve,AUC)、精确召回率曲线、精确召回率曲线下的面积(area under the precision recall curve,PRAUC)、准确率、灵敏度、特异度分别对模型进行综合评估,引入Shapley加性解释(Shapley additive explanation,SHAP)对最优机器学习模型进行可解释化处理。结果:经LASSO回归分析后,确定16个特征变量用于构建机器学习模型。RF模型具有最高的AUC(0.74)、PRAUC(0.64)、准确率(0.97)、灵敏度(0.75)和特异度(0.97)。SHAP模型解释性分析显示,对ADL贡献度前5的特征中,Brunnstrom分期(下肢)的影响最为显著,其次是Brunnstrom分期(上肢)、D-二聚体、血清白蛋白水平及年龄。结论:RF模型预测脑卒中患者ADL的效能最优,为脑卒中患者ADL管理决策提供了有价值的参考。
