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非线性模型在蛋白质薄膜厚度测定中的应用
APPLICATION OF NONLINEAR REGRESSION MODEL TO DETECTTHE THICKNESS OF PROTEIN LAYER
【摘要】 为了通过测定蛋白质薄膜厚度变化而定量地研究生物分子间的相互作用 ,探讨了基于光学干涉法的薄膜厚度的测量方法。借助于在玻璃基底表面沉积的聚苯乙烯薄膜对噪声的抑制 ,使用非线性回归模型对生物传感器的检测信号进行了分析。通过反射干涉光谱法测定到乙型肝炎表面抗原在聚苯乙烯 -玻璃表面的吸附使薄膜厚度增加了3.3nm。随着5μg/ml,10μg/ml,20μg/ml,30μg/ml和50μg/ml浓度的乙型肝炎表面抗体的加入 ,薄膜厚度分别增加了3.7nm,4.3nm,5.3nm ,6.3nm和7.5nm。通过与经典的干涉测量技术和酶标记法相对照 ,证明了测量结果具有较高的可信度。
【Abstract】 The thickness of protein layer was studied by applying nonlinear regression model to fit the reflection spectrum.To reduce the influence of systematic noise, a polystyrene film was spread on the slide surface. The reflection spectrum was normalized to that of bare glass slide substrate to eliminate the light source influence. The results were compared with that of the classical interferometry and enzyme labeled antigen-antibody interactions. Good agreements among these results suggested the proposed method is authentic.
【Key words】 Thin film; Nonlinear regression model; Antigen-Antibody interaction; White light interference biosensor;
- 【文献出处】 生物物理学报 ,ACTA BIOPHYSICA SINICA , 编辑部邮箱 ,2000年01期
- 【分类号】Q617
- 【被引频次】3
- 【下载频次】68