Mathematical modelling of a magnetic immunoassay
Mathematical modelling of a magnetic immunoassay
复制标题
磁免疫分析的数学模型
DOI：
10.1093/imamat/hxx034
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发表时间：
2017
影响因子：
1.2
通讯作者：
Roberts L
中科院分区：
文献类型：
--
作者：
Roberts L
开发了一种数学模型来描述一种新型流体生物传感器的作用，该传感器使用预先涂有目标特异性抗体的顺磁颗粒（PMP）。在初始阶段，将颗粒引入含有靶标的样品溶液中，然后靶标通过抗原抗体反应与颗粒结合。在测试阶段，使用磁铁将 PMP 吸引到同样涂有特定抗体的传感器表面。在此过程中，抗原形成交联，从而将 PMP 结合到传感器表面。去除磁场后，记录传感器表面下方的电感器上的电压变化，这被认为取决于已结合到传感器表面的磁性颗粒的数量。解决的基本问题是解释实验观察到的剂量反应曲线的范围，以及它如何取决于问题的各种参数。特别是，观察结果显示了上升和下降的剂量反应曲线，以及具有局部最大值的“钩状”剂量反应曲线。最初建立了一个粒子动力学计算模型来确定所涉及的关键过程的时间尺度，但事实证明无法产生不同形状的剂量反应曲线。计算模型表明时空效应并不重要，因此为免疫测定过程的每个关键阶段开发了均质速率方程模型。结合率取决于与 PMP 直径和传感器表面尺寸相关的各种几何因素。剂量反应被证明主要取决于每个阶段的各种饱和效应，并且在某些情况下可以分析得出三种定性不同曲线类型中的每一种的条件。此外，无量纲化揭示了 5 个关键的无量纲参数，并揭示了这些曲线形状对每个参数的依赖性。结果指出了未来传感器设计和校准的定量方法。
A mathematical model is developed to describe the action of a novel form of fluidic biosensor that uses paramagnetic particles (PMPs) that have been pre-coated with target-specific antibodies. In an initial phase the particles are introduced to a sample solution containing the target which then binds to the particles via antigen–antibody reactions. During the test phase a magnet is used to draw the PMPs to the sensor surface which is similarly coated with specific antibodies. During this process, cross-links are formed by the antigens thereby binding the PMPs to the sensor surface. After the magnetic field is removed, a voltage change across an inductor below the sensor surface is recorded, which is deemed to depend on the number of magnetic particles that have been bound to the sensor surface. The fundamental question addressed is to explain the range of experimentally observed dose–response curves, and how this depends on the various parameters of the problem. In particular, observations have shown both rising and falling dose–response curves, as well as ‘hooked’ dose–response curves possessing local maxima. Initially a particle-dynamics computational model is produced to determine the time scales of the key processes involved, but is shown to be unable to produce differently shaped dose–response curves. The computational model suggests spatio-temporal effects are unimportant, therefore a homogenized rate-equation model is developed for each of the key phases of the immunoassay process. Binding rates are shown to depend on various geometric factors related to the diameter of the PMPs and the size of the sensor surface. The dose–response is shown to depend crucially on various saturation effects during each phase, and conditions can be derived, in some cases analytically, for each of the three qualitatively different curve types. Furthermore, non-dimensionalization reveals 5 key dimensionless parameters and the dependence of these curve shapes on each is revealed. The results point to future quantitative approaches to sensor design and calibration.
模拟随机抗体吸附和免疫测定活性。
DOI：
--
发表时间：
2016
期刊：
Mathematical biosciences and engineering : MBE
影响因子：
--
作者：
D. Mackey;Eilís Kelly;R. Nooney
通讯作者：
R. Nooney
影响因子：
12.6
作者：
Richardson, J;Hill, A;Hawkins, P
通讯作者：
Hawkins, P