2026-10-15T00:04:17Z https://www.scidb.cn/oai

10.57760/sciencedb.sepu.0001a 2026-09-24T15:16:41Z

2026-09-24 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 doi:10.57760/sciencedb.sepu.0001a en This dataset contains the core experimental data used to evaluate the analytical performance of a novel time-difference signal-based moving boundary electrophoresis (ET-ELISA) system. 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. Moving reaction boundary (MRB); Electrophoretic titration (ET); Time-difference signal; Alzheimer’s disease; Neural thread protein (AD7c-NTP); Enzyme-linked immunosorbent assay (ELISA) 王迩骥 张强 RESTRICTED dataset Science Data Bank