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Model-controlled hydrodynamic focusing to generate multiple overlapping gradients of surface-immobilized proteins in microfluidic devices

机译:模型控制的流体动力聚焦可在微流体装置中产生表面固定蛋白的多个重叠梯度

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Historically,it has been difficult to generate accurate and reproducible protein gradients for studies of interactions between cells and extracellular matrix.Here we demonstrate a method for rapid patterning of protein gradients using computer-driven hydrodynamic focusing in a simple microfluidic device.In contrast to published work,we are moving the complexity of gradient creation from the microfluidic hardware to dynamic computer control.Using our method,switching from one gradient profile to another requires only a few hours to devise a new control file,not days or weeks to design and build a new microfluidic device.Fitting existing protein deposition models to our data,we can extract key parameters needed for controlling protein deposition.Several protein deposition models were evaluated under microfluidic flow conditions.A mathematical model for our deposition method allows us to determine the parameters for a protein adsorption model and then predict the final shape of the surface density gradient.Simple and non-monotonic single and multi-protein gradient profiles were designed and deposited using the same device.
机译:从历史上看,很难生成准确且可重现的蛋白质梯度用于研究细胞与细胞外基质之间的相互作用。在此,我们展示了一种在简单的微流控设备中使用计算机驱动的流体动力学聚焦对蛋白质梯度进行快速模式分析的方法。工作中,我们正在将梯度创建的复杂性从微流体硬件转移到动态计算机控制。使用我们的方法,从一个梯度配置文件切换到另一种梯度配置文件仅需几个小时即可设计一个新的控制文件,而无需花费几天或几周的时间来设计和构建一种新的微流体装置。将现有的蛋白质沉积模型拟合到我们的数据中,我们可以提取控制蛋白质沉积所需的关键参数。在微流体流动条件下评估了几种蛋白质沉积模型。我们沉积方法的数学模型使我们能够确定蛋白质吸附模型,然后预测表面的最终形状密度梯度:使用同一设备设计并沉积简单和非单调的单蛋白质和多蛋白质梯度曲线。

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