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Optimization of a Concanavalin A-based glucose sensor using fluorescence anisotropy

机译:使用荧光各向异性优化基于伴刀豆球蛋白A的葡萄糖传感器

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摘要

To date, the dependent nature of the recognition and transduction mechanisms in optical glucose sensors based upon Concanavalin A (ConA) has tended to prevent the sensors’ full potential from being realized. In this paper, these mechanisms are independently optimized for a given assay configuration in order to decrease the predictive error of a ConA-based glucose sensor and to give a more accurate demonstration of its potential. To this end, we used fluorescence anisotropy as the transduction mechanism to determine the binding of ConA to 4 kDa FITC-dextran by measuring the change in the rotational correlation lifetime between the bound and unbound populations. By tracking the fluorescence anisotropy of this ligand, the ranges of ConA and 4 kDa FITC-dextran concentrations capable of being explored were not limited by the transduction mechanism. Using predetermined association constants, the binding responses to physiological glucose concentrations were predicted for different assay configurations, and experimentally collected fluorescence anisotropy data displayed the predicted trends for these assay configurations. From the experimental results, a calibration fit was generated for the optimized assay configuration to predict the glucose concentrations using the fluorescence anisotropy. This optimized assay displayed a mean standard error of prediction of 7.5 mg/dL (0–300 mg/dL), and 100% of the data points fell within clinically acceptable zones (A and B) upon the Clarke Error Grid Analysis. This indicates that, by independently optimizing the recognition and transduction mechanisms for the final assay configuration, the sensitivity of a competitive binding chemistry using ConA can be appropriately configured for continuous glucose monitoring applications.
机译:迄今为止,在基于伴刀豆球蛋白A(ConA)的光学葡萄糖传感器中,识别和转导机制的依赖性已经倾向于阻止传感器的全部潜能得以实现。在本文中,针对给定的测定配置对这些机制进行了独立优化,以减少基于ConA的葡萄糖传感器的预测误差并更准确地展示其潜力。为此,我们使用荧光各向异性作为转导机制,通过测量结合和未结合群体之间旋转相关寿命的变化,确定ConA与4 kDa FITC-葡聚糖的结合。通过追踪该配体的荧光各向异性,可以探究的ConA和4 kDa FITC-葡聚糖浓度范围不受转导机制的限制。使用预定的缔合常数,可以预测不同测定配置对生理葡萄糖浓度的结合反应,并且实验收集的荧光各向异性数据显示了这些测定配置的预测趋势。从实验结果中,生成了针对最佳化验配置的校准拟合,以使用荧光各向异性来预测葡萄糖浓度。这种优化的测定显示出7.5 mg / dL(0–300 mg / dL)的平均预测标准误差,克拉克误差网格分析后100%的数据点落在临床可接受的区域(A和B)内。这表明,通过针对最终分析配置独立地优化识别和转导机制,可以适当地配置使用ConA的竞争性结合化学的灵敏度,以进行连续的葡萄糖监测应用。

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