Parthasarathy P, Vivekanandan S
School of Electrical Engineering, VIT University, Vellore, Tamilnadu India.
Health Inf Sci Syst. 2018 Apr 23;6(1):5. doi: 10.1007/s13755-018-0043-3. eCollection 2018 Dec.
Uric acid biosensors for arthritis disease has been developed for the specific selection of uricase enzyme film thickness coated over the TiO-CeO nano-composite matrix is modelled mathematically. This model is purely based on R-diffusion conditions with irreversible first-order catalytic reactions. By arithmetical method, the impact of the thickness of enzyme layer on the current response of the biosensor was explored. This article displays a structure for choice of the enzyme layer thickness, guaranteeing the adequately stable sensitivity of a biosensor in a required extent of the maximal enzymatic rate. The numerical outcomes showed subjective and sensible quantitative information for oxidation current due to uric acid also shows the maximum change in the biosensor current response due to the change in membrane thickness, which will be more suitable for uric acid biosensor for the application of arthritis disease diagnosis.
针对关节炎疾病的尿酸生物传感器已被开发出来,用于对涂覆在TiO-CeO纳米复合基质上的尿酸酶薄膜厚度进行特定选择,并进行了数学建模。该模型完全基于具有不可逆一级催化反应的R扩散条件。通过算术方法,探讨了酶层厚度对生物传感器电流响应的影响。本文展示了一种选择酶层厚度的结构,确保生物传感器在所需的最大酶促反应速率范围内具有足够稳定的灵敏度。数值结果显示了尿酸氧化电流的主观和合理的定量信息,也显示了由于膜厚度变化导致的生物传感器电流响应的最大变化,这将更适合用于关节炎疾病诊断的尿酸生物传感器。