The quantitative detection of microRNA (miRNA) is of critical importance for the early diagnosis of cancers, particularly lung cancer, where specific miRNAs such as miRNA-21 have been identified as key biomarkers. However, the low abundance, short chain length, and high sequence homology of miRNAs present significant challenges in developing a rapid, low-cost, and concentration-sensitive detection platform. In this study, we investigate the detection of 22 nt single-stranded DNA (ssDNA), a surrogate for miRNA-21, using solid-state nanopores, and observe a saturation phenomenon in the capture rate at low concentrations, which limits the sensitivity of the detection. To elucidate this phenomenon, we propose a competition theoretical model based on Langmuir adsorption dynamics, which identifies spatial hindrance effects caused by the competitive adsorption of DNA molecules near the nanopore entrance as the primary factor limiting detection sensitivity. This hindrance effect is influenced by the physicochemical properties of DNA, the applied voltage, and the nanopore dimensions. Through numerical simulations, we further analyze the interplay of electrophoretic forces, electroosmotic flow, and electrostatic repulsion in the translocation dynamics of DNA molecules, providing a comprehensive understanding of the underlying mechanisms. To overcome these limitations, we introduce a conformational conversion strategy that transforms ssDNA into double-stranded DNA (dsDNA) through the addition of complementary strands. This strategy significantly reduces the spatial hindrance at the nanopore inlet and lowers the energy barrier for molecular translocation. Experimental results demonstrate that the conversion to dsDNA not only enhances the capture efficiency but also transforms the concentration-response relationship from nonlinear to linear, enabling more accurate quantification of low-concentration analytes. Furthermore, the conformational conversion reverses the translocation direction of the target biomarkers, improving the specificity and sensitivity of the detection process. Our findings reveal that the dsDNA-based approach achieves dual improvements in low-concentration sensitivity and voltage-dependent capture rates, providing a robust framework for the ultrasensitive detection of low-abundance biomarkers in complex biological samples. In conclusion, the conformational conversion strategy-driven solid-state nanopore platform represents a significant step forward in the rapid, low-cost, and concentration-sensitive detection of lung cancer biomarkers, addressing critical challenges in the field and offering new opportunities for early disease diagnosis and personalized medicine.
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