Abstract：
BACKGROUND: As promising biomarkers of diabetes, α-glucosidase (α-Glu) and β-glucosidase (β-Glu) play a crucial role in the diagnosis and management of diseases. However, there is a scarcity of techniques available for simultaneously and sensitively detecting both enzymes. What\'s more, most of the approaches for detecting α-Glu and β-Glu rely on a single-mode readout, which can be affected by multiple factors leading to inaccurate results. Hence, the simultaneous detection of the activity levels of both enzymes in a single sample utilizing multiple-readout sensing approaches is highly attractive.
RESULTS: In this work, we constructed a facile sensing platform for the simultaneous determination of α-Glu and β-Glu by utilizing a luminescent covalent organic framework (COF) as a fluorescent indicator. The enzymatic hydrolysis product common to both enzymes, p-nitrophenol (PNP), was found to affect the fluorometric signal through an inner filter effect on COF, enhance the colorimetric response by intensifying the absorption peak at 400 nm, and induce changes in RGB values when analyzed using a smartphone-based color recognition application. By combining fluorometric/colorimetric measurements with smartphone-assisted RGB mode, we achieved sensitive and accurate quantification of α-Glu and β-Glu. The limits of detection for α-Glu were determined to be 0.8, 1.22, and 1.85 U/L, respectively. Similarly, the limits of detection for β-Glu were 0.16, 0.42, and 0.53 U/L, respectively.
CONCLUSIONS: Application of the proposed sensing platform to clinical serum samples revealed significant differences in the two enzymes between healthy people and diabetic patients. Additionally, the proposed sensing method was successfully applied for the screening of α-Glu inhibitors and β-Glu inhibitors, demonstrating its viability and prospective applications in the clinical management of diabetes as well as the discovery of antidiabetic medications.
RESULTS: In this work, we constructed a facile sensing platform for the simultaneous determination of α-Glu and β-Glu by utilizing a luminescent covalent organic framework (COF) as a fluorescent indicator. The enzymatic hydrolysis product common to both enzymes, p-nitrophenol (PNP), was found to affect the fluorometric signal through an inner filter effect on COF, enhance the colorimetric response by intensifying the absorption peak at 400 nm, and induce changes in RGB values when analyzed using a smartphone-based color recognition application. By combining fluorometric/colorimetric measurements with smartphone-assisted RGB mode, we achieved sensitive and accurate quantification of α-Glu and β-Glu. The limits of detection for α-Glu were determined to be 0.8, 1.22, and 1.85 U/L, respectively. Similarly, the limits of detection for β-Glu were 0.16, 0.42, and 0.53 U/L, respectively.
CONCLUSIONS: Application of the proposed sensing platform to clinical serum samples revealed significant differences in the two enzymes between healthy people and diabetic patients. Additionally, the proposed sensing method was successfully applied for the screening of α-Glu inhibitors and β-Glu inhibitors, demonstrating its viability and prospective applications in the clinical management of diabetes as well as the discovery of antidiabetic medications.
摘要：
背景：作为糖尿病的有希望的生物标志物，α-葡萄糖苷酶(α-Glu)和β-葡萄糖苷酶(β-Glu)在疾病的诊断和治疗中起着至关重要的作用。然而,缺乏可用于同时和灵敏检测两种酶的技术。更重要的是，大多数检测α-Glu和β-Glu的方法都依赖于单模读出，这可能会受到多种因素的影响，导致结果不准确。因此，利用多读出传感方法同时检测单个样品中两种酶的活性水平是非常有吸引力的。
结果：在这项工作中，我们利用发光共价有机框架（COF）作为荧光指示剂，构建了一个简单的传感平台，用于同时测定α-Glu和β-Glu。两种酶共同的酶水解产物，对硝基苯酚(PNP),被发现通过内部过滤器对COF的影响来影响荧光信号，通过增强400nm处的吸收峰来增强比色响应，并在使用基于智能手机的颜色识别应用程序进行分析时引起RGB值的变化。通过将荧光/比色测量与智能手机辅助的RGB模式相结合，我们实现了α-Glu和β-Glu的灵敏和准确的定量。α-Glu的检出限分别为0.8、1.22和1.85U/L,分别。同样，β-Glu的检出限分别为0.16、0.42和0.53U/L，分别。
结论：将所提出的传感平台应用于临床血清样本，揭示了健康人和糖尿病患者之间两种酶的显著差异。此外,所提出的传感方法已成功应用于α-Glu抑制剂和β-Glu抑制剂的筛选，证明了其在糖尿病临床管理中的可行性和前瞻性应用，以及抗糖尿病药物的发现。
结果：在这项工作中，我们利用发光共价有机框架（COF）作为荧光指示剂，构建了一个简单的传感平台，用于同时测定α-Glu和β-Glu。两种酶共同的酶水解产物，对硝基苯酚(PNP),被发现通过内部过滤器对COF的影响来影响荧光信号，通过增强400nm处的吸收峰来增强比色响应，并在使用基于智能手机的颜色识别应用程序进行分析时引起RGB值的变化。通过将荧光/比色测量与智能手机辅助的RGB模式相结合，我们实现了α-Glu和β-Glu的灵敏和准确的定量。α-Glu的检出限分别为0.8、1.22和1.85U/L,分别。同样，β-Glu的检出限分别为0.16、0.42和0.53U/L，分别。
结论：将所提出的传感平台应用于临床血清样本，揭示了健康人和糖尿病患者之间两种酶的显著差异。此外,所提出的传感方法已成功应用于α-Glu抑制剂和β-Glu抑制剂的筛选，证明了其在糖尿病临床管理中的可行性和前瞻性应用，以及抗糖尿病药物的发现。
