Dataset for time-difference signal-based detection of Alzheimer’s disease-associated neural thread protein in urine using moving boundary electrophoresis and enzyme-linked immunosorbent assay

The data supports the accurate quantification of low-abundance disease biomarkers in complex biofluids, such as urine. The dataset is categorized into three main experimental sections.System Optimization Data: Includes data on the effects of background electrolyte (KCl) concentration (20–100 mmol/L) on the boundary meeting time (tend) and boundary contrast, as well as the distance-time migration trajectories under varying driving voltages (12–60 V).TMB+ Quantitative Model Data : Contains the distance-time migration trajectories of the colored TMB+ boundary across a concentration gradient (123–1318 μmol/L), used to establish the quantitative relationship between concentration and boundary meeting time.AD7c-NTP Analytical Performance and Clinical Validation Data: Comprises distance-time migration trajectories driven by the target biomarker AD7c-NTP at varying concentrations (200–3200 pg/mL); anti-interference evaluation data involving common urinary coexisting substances (glucose, urea, creatinine, hemoglobin, and NaCl) in artificial urine; and comparison results between the proposed method and commercial ELISA kits across 6 real human urine samples.