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From Molecular Recognition to Clinical Readout: Design Principles for Functional Nucleic Acid–Material Biosensors in Medical Diagnostics

Sep 2026 · Molecules · Vol 31, pp. 3358 · 0 citations · 68 references
Medicine

TL;DR

Across the literature, reliable performance depends on selective recognition before high-gain reactions, compatibility between amplification products and interfaces, explicit controls for inhibition and leakage, and validation across independent lots and representative clinical populations.

Abstract

Functional nucleic acids can connect molecular recognition with chemical signal generation, but their diagnostic value depends on the performance of the complete sample-to-answer pathway. This critical narrative review examines representative studies published through 31 July 2026, with emphasis on recognition, amplification, material interfaces, sample preparation, readout and clinical interpretation under realistic conditions. Hybridization and ligation probes, aptamers, DNAzymes, DNA nanostructures and CRISPR-associated systems are compared by specificity, kinetics, leakage and matrix compatibility. Rolling circle amplification, hybridization chain reaction, catalytic hairpin assembly and enzymatic isothermal amplification are evaluated as reaction networks whose products must remain accessible to the selected interface. Functional materials are classified by their actual analytical role, including transduction, signal amplification, capture/enrichment, spatial organization and reagent storage. Evidence is distinguished between mechanistic studies, spiked matrices, clinical specimens, manufactured-format reproducibility and demonstrated clinical utility. We further integrate sample-to-answer workflow, assay time, complexity, regulatory considerations and clinically relevant decision thresholds. Across the literature, reliable performance depends on selective recognition before high-gain reactions, compatibility between amplification products and interfaces, explicit controls for inhibition and leakage, and validation across independent lots and representative clinical populations. These principles define a path from analytical proof of concept to reproducible and clinically interpretable diagnostic testing.

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