关键词: 微芯片电泳, 电泳传感, 移动反应界面, 酶联免疫吸附, 生物标志物

Abstract: Accurate quantification of disease-related biomarkers in complex biofluids holds profound significance for early clinical diagnosis. Among biofluids, urine possesses unique advantages, including non-invasive collection and prolonged accumulation of early pathological products, making it a valuable medium for early disease screening and dynamic monitoring of disease progression. Recently, ET-ELISA (electrophoretic titration-enzyme-linked immunosorbent assay) technology, developed based on moving reaction boundary (MRB) and electrophoretic titration theories, successfully transforms immunochemical signals into measurable spatial distance. This approach effectively eliminates reliance on complex optical instruments, providing a robust platform for rapid bedside testing. However, when detecting low-abundance biomarkers, subtle variations in target concentration result in minimal boundary distance differences, imposing stringent requirements on the spatial resolution of conventional reading devices.
To address this challenge, this study proposes a time-domain quantification strategy that enables precise measurement of low-abundance disease biomarkers in urine. The study's contributions are twofold: the establishment of a time-difference-based quantification model and the validation of its analytical performance. First, extending traditional spatial quantification concepts, we continuously monitor the dynamic boundary migration within a simplified microchannel, bypassing the need for an additional redox boundary. Machine vision algorithms construct an inverted “V-shaped” distance-time profile to locate the intersection between the blue TMB⁺ (3,3',5,5'-tetramethylbenzidine cation) boundary and the colorless alkaline boundary. The time at this peak (t_end) serves as the quantitative measure. This time-dependent sensing is governed by the asymmetric migration of background ions (K⁺ and Cl^-) to maintain electroneutrality. The cathodic migration of positively charged TMB⁺ accelerates the reverse Cl^- flux, inducing OH^- generation and a reverse-migrating alkaline boundary. Elevated target concentrations yield more TMB⁺ which directly advances this alkaline boundary formation and shortens the meeting time. Visually, the blue TMB⁺ boundary turns yellow and reverses its migration direction earlier. Second, we validate the analytical performance of this quantitative system using the Alzheimer's disease-associated neural thread protein (AD7c-NTP) as a clinical model. Quantitative analysis of the boundary meeting time (t_end) signal reveals a linear range of 200-3β200 pg/mL with an R² of 0.985; the limit of detection (LOD) is 150 pg/mL. In artificial urine, the average intraday and interday recoveries are 99.7% and 100.5%, with relative standard deviations (RSDs) of 4.8% and 4.2%, respectively. Further application to 6 real human urine samples yielded results highly consistent with commercial ELISA kits (r=0.987), confirming the platform's accuracy and reliability in complex matrices.
The time-difference-based detection method exhibits the following advantages: (i) This strategy transforms the direct utilization of spatial distance into sequential time tracking of the peak point of the colored boundary's movement. The boundary meeting time (t_end) serves as the readout parameter. This time-domain parameter converts subtle spatial variations into more distinguishable temporal signals, while preserving the suitability of the method for portable observation. (ii) This method achieves precise dynamic boundary tracking within a solution of more simplified composition, reducing the complexity of reagent preparation. (iii) The platform retains the advantage of classic ET-ELISA technology—requiring no large, specialized optical instruments, and the digital output format of boundary meeting time (t_end) aligns with the developmental needs of high-precision, automated instruments. Together, these advantages support the application of this quantitative detection system for non-invasive disease screening and biochemical analysis in resource-limited settings.

Key words: microchip electrophoresis, electrophoretic sensing, moving reaction boundary (MRB), enzyme-linked immunosorbent assay (ELISA), biomarkers