Researchers at the University of Tokyo have introduced a groundbreaking analytical technique called voltage-matrix nanopore profiling, which enhances the ability to analyze protein mixtures. This innovative method integrates multivoltage solid-state nanopore signals with machine learning, enabling precise classification of proteins based solely on their intrinsic electrical signatures, without needing labels or modifications. Published in Chemical Science, the study showcases its potential to identify “molecular individuality,” particularly in complex mixtures such as cancer biomarkers. By systematically varying voltage conditions and capturing voltage-dependent signal patterns, the researchers created a voltage matrix that distinguishes proteins more effectively than traditional methods like ELISA or mass spectrometry. They demonstrated the technique’s practicality by analyzing mouse serum samples, successfully identifying compositional differences. This advancement paves the way for real-time molecular profiling in biomedical diagnostics, offering promising applications for disease detection and environmental monitoring.
