摘要
目的探讨ELISA检测乙型脑炎减毒活疫苗中庆大霉素残留量的数据拟合模型,以验证和优化定量检测系统。方法采用商品化庆大霉素残留酶联免疫检测试剂盒对乙型脑炎减毒活疫苗进行庆大霉素残留量检测,通过二次多项式模型、对数线性模型和四参数logistic模型对实验数据进行拟合处理,分析比较各模型的决定系数(R2)、实验点分布、回收率等指标。结果二次多项式模型、对数线性模型和四参数logistic模型的变量显著性检验均有统计学意义(P<0.05),R2均值分别为0.9970、0.9944、0.9993,二次多项式模型和四参数logistic模型拟合优度较好;各拟合模型的标准品实验点在标准曲线两侧的分布都较为均匀,四参数logistic模型最佳,尤其是在中、低浓度范围(0.1~0.9 ng/ml);各拟合模型在0.1~8.1 ng/ml浓度范围的标准品回收率均达到中国药典要求,且差异无统计学意义。结论二次多项式模型、对数线性模型和四参数logistic模型均适用于ELISA检测庆大霉素残留量的数据分析,其中二次多项式模型和四参数logistic模型拟合较好,这对持续优化该项定量检测具有重要指导意义。
Objective To investigate the data fitting model of ELISA for determination of gentamicin residues in attenuated Japanese encephalitis vaccine(JEV),so as to validate and optimize the quantitative detection system.Methods The JEVs were tested for gentamicin residue using commercial gentamicin residue ELISA kit,and the test data were fitted respectively through quadratic polynomial model,log-linear model and four-parameter logistic model.Then the indicators including the coefficient of determination(R2),experimental point distribution and recovery rate were analyzed and compared.Results The variables tests of quadratic polynomial model,log-linear model and four-parameter logistic model were all of statistical significance(P<0.05),and the mean values of R2 were 0.9970,0.9944 and 0.9993,respectively,among which the quadratic polynomial model and four-parameter logistic model presented the best fitting.The distribution of standard points on both sides of the standard curve was uniform for all models,and the four-parameter logistic model was the best,especially in the range of medium and low concentrations(0.1-0.9 ng/ml).The recoveries of standard substances in the concentration range of 0.1-8.1 ng/ml of each fitting model met the requirements of Chinese pharmacopoeia,and the differences were not statistically significant.Conclusions Quadratic polynomial model,log-linear model and four-parameter logistic model are all suitable for the data analysis of ELISA for gentamicin residues,but quadratic polynomial and four-parameter logistic models fit well,which has important guiding significance for continuous optimization of this quantitative determination.
作者
江莉
吕冰凌
陈守彬
罗静
罗珊
曾昭萍
袁良玉
刘菊
Jiang Li;Lyu Bingling;Chen Shoubin;Luo Jing;Luo Shan;Zeng Zhaoping;Yuan Liangyu;Liu Ju(Department of Quality Control,Chengdu Institute of Biological Products Co.,Ltd.,Sichuan Vaccine Engineering Technology Research Center,Chengdu 610023,China;Department of Quality Operation,Chengdu Institute of Biological Products Co.,Ltd.,Chengdu 610023,China;Department of Quality Assurance,Chengdu Institute of Biological Products Co.,Ltd.,Chengdu 610023,China)
出处
《国际生物制品学杂志》
CAS
2022年第4期217-221,共5页
International Journal of Biologicals