Fluidic Lipid-Bilayer-Enhanced Iontronic Nanopore: Machine-Learning-Driven Ultrasensitive MicroRNA Detection in Cancer Diagnostics.

Ultrasensitive detection of microRNA (miRNA) is critical for precision diagnostics. However, conventional surface-based DNA walkers are intrinsically limited by slow kinetics arising from the static nature of solid-state substrates. Here, we report a dynamic DNA walker operating on a fluidic supported lipid bilayer (SLB) integrated with an anodic aluminum oxide (AAO) nanopore. Fluorescence recovery after photobleaching (FRAP) confirms the lateral mobility of lipid-anchored probes with a diffusion coefficient D ≈ 1.2 μm2/s. This fluidity enables the active replenishment of local reactants. This fundamentally shifts the system from a diffusion-controlled to a reaction-controlled regime (Damköhler number, Da <1), allowing the walker to operate at its intrinsic catalytic efficiency and reach equilibrium in 30 min. Signal transduction is governed by a synergistic regulation of the effective pore diameter (deff) and surface charge density (σ), triggering a hydrophobicity-modulated conductance switch. This platform achieves a limit of detection of 25 aM for microRNA-21 (miR-21) and enables clinical sample classification with >98% accuracy using an interpretable decision-stump model, confirming that the dominant diagnostic information is captured by a single high signal-to-noise current feature. This work establishes substrate fluidity as a core design principle for next-generation iontronic sensors.