Automated Antithrombin Activity Detection with Whole Capillary Blood Based on Digital Microfluidic Platform

Abstract

Antithrombin (AT) plays a crucial role in the human anticoagulant system and has extensive clinical applications. However, traditional detection methods often require large sample volumes, complex procedures, and lengthy processing times.

Methods: We integrated digital microfluidics technology with AT detection to develop a point-of-care testing (POCT) device that is user-friendly and fully automated for real-time AT testing.

Results: This device allows for automation and enhanced adaptability to various settings, requiring only a minimal sample volume (whole capillary blood), thereby omitting steps such as plasma separation to save time and improve clinical testing efficiency. Comparisons with conventional AT activity detection methods demonstrate a high degree of consistency in the results obtained with this device.

Conclusion: The AT detection system we developed exhibits significant effectiveness and holds substantial research potential, positioning it to evolve into a clinically impactful POCT solution for AT assessment.

Keywords: AT; in vitro diagnostics; microfluidics; optical biosensors; point-of-care testing.

Figure 1

Schematic diagram of the AT detection method.

Figure 2

Schematic diagrams of the system’s components and detection principles are presented. (a) Schematic representation of the principle of absorbance change detection. (b) Illustration of the detection process on the chip. Step 1: following the separation of plasma outside the chip, a factor diluent is introduced as the sample for analysis. Step 2: the prepared sample is applied to the surface of the chip. Step 3: the sample is mixed with Factor Xa to activate the components. Step 4: the resultant mixture is reacted with a chromogenic substrate, and absorbance changes are monitored using an absorbance detection system. (c) Schematic diagram of the absorbance detection system’s structure.

Figure 3

Schematic and actual images of the chip’s reaction when plasma is used as the test sample: (i and v) droplet generation, (ii and vi) reacting with Factor Xa, (iii and vii) moving to the next reaction area, and (iv and viii) mixing with chromogenic substrate.

Figure 4

Optimization of detection method conditions and quantitative performance based on changes in absorbance. (a) The influence of different power supply voltages on the variation in photon counts per minute. (b) The relationship between the vertical distance between the detection module lens and the microfluidic chip and the changes in photon count per minute. (c) Measurement of the device’s dark current showed an average photon count of 384,460.71 ± 559.22. (d) In the absence of loaded droplets, the system’s average photon count was found to be 24,429,585.36 nm, with a coefficient of variation of 0.103%.

Figure 5

Qualitative detection of chip performance with clinical samples. (a) Variability measurements of photon count from plasma at three different activity levels (100%, 75%, and 50%) across eight replicate experiments, resulting in coefficients of variation of 3.64%, 2.97%, and 3.21%, respectively. (b) Reconstitution of lyophilized calibration standards, validating the feasibility of four concentrations: 100%, 75%, 50%, and 25%. (c) Relationship between activity levels and absorbance changes in 30 clinical samples (using plasma as the test sample), with the central yellow region indicating normal activity levels. (d) Visualization of blood and reagents at varying dilution concentrations; from left to right, the dilution factors are 1, 2, 5, 10, and 20. (e) Results of absorbance changes with different dilution factors. (f) Relationship between activity levels and absorbance changes in 20 clinical samples (using diluted venous whole blood as the test sample), with the central yellow region representing normal activity levels.