## 3 Results and Discussion
### Microfluidic-Sensing Studies for Amyloid-Beta Analysis
#### 3.2.3 Optimizing Binding Studies of CRANAD-2 with Amyloid-Beta in a Microfluidic Device
The microfluidic experiment within the same concentration range (100-1000 nM) yielded an even higher \(R^{2}\) value of 0.998, confirming the robustness of the fluorescence response in this range. However, in the extended microfluidic dataset (5-100 nM), the \(R^{2}\) value decreased to 0.925, likely due to increased background noise and detection limitations at lower concentrations. Statistical validation of these correlations was assessed using p-values, confirming the significance of the fluorescence intensity response across all experimental setups. The macroscale setup (100-1000 nM) exhibited the highest statistical confidence (\(p\) = 2.51\(\times\)10\({}^{-8}\)), reflecting minimal variability in fluorescence measurements. The microscale setup within the same range (100-1000 nM) yielded a slightly higher \(p\)-value (\(p\) = 3.72 \(\times\) 10\({}^{-4}\)), consistent with the expected increase in experimental noise due to microfluidic constraints. At lower concentrations (5-100 nM), the microscale platform showed greater signal variability, resulting in a higher yet still significant \(p\)-value (\(p\) = 0.0315). These results confirm that fluorescence intensity remains a reliable indicator of A\(\beta\) concentration across both macroscale and microfluidic conditions, despite increased variability at lower concentrations due to optical and fluidic factors. Despite the attenuated fluorescence signals in the microfluidic-sensing system, the proportional intensity ratio of fibrillar A\(\beta\) remains consistent with macroscale trends (Figure 4b,d). Both platforms demonstrated CRANAD-2's strong specificity for fibrillar A\(\beta\), which consistently generated higher fluorescence signals due to its aggregated  
Figure 6: The linear relationship between fibrillar A\(\beta\) protein concentrations and fluorescence intensities at 590 nm excitation, in the presence of 25 uM CRANAD-2 (n = 3 for each concentration), measured at the emission peak wavelength of 736 nm. The data shown reflect the performance of the system under both macroscale and microfluidic conditions: (**a**) macroscale experiments with concentrations ranging from 100 nM to 1000 nM; (**b**) microscale experiments with concentrations ranging from 100 nM to 1000 nM; (**c**) microscale experiments with concentrations ranging from 5 nM to 100 nM. Data are shown as mean \(\pm\) standard deviation. Statistical test: \(p\) < 0.05.  
structure and enhanced binding affinity. A population-based study conducted by [PERSON] et al. provided clearer benchmarks for plasma A\(\beta\) levels in relation to neurodegeneration and dementia risk. Concentrations of A\(\beta_{1-40}\) were reported at 43.0 nM and A\(\beta_{1-42}\) at 12.5 nM, offering critical insights into the clinical relevance of these biomarkers, with variations as low as 8.3 nM and 1.4 nM [36]. These values provide critical insights into the clinical relevance of these biomarkers. Notably, these concentrations align closely with the lower detection limits of our system, highlighting its capability to accurately detect both normal and pathological shifts in A\(\beta\) levels. Hence, the transition to microfluidic systems offers several practical advantages. The microfluidic platform requires significantly smaller sample volumes, reducing reagent consumption by approximately 92.5%. Furthermore, the flow conditions in microfluidics enable precise control over reaction parameters, improving specificity and facilitating integration into automated systems. Notably, even at reduced fluorescence intensities, the microfluidic system demonstrated the ability to detect A\(\beta\) fibrils at concentrations as low as 5 nM, highlighting its sensitivity and the feasibility of using it as a tool for AD detection. The system's capability to quantify A\(\beta\) concentrations reliably, with minimal error, aligns well with established clinical values, further validating its potential use for early biomarker detection in preclinical settings.