Towards clinical application: Emerging strategies for ultrasensitive and selective miRNA detection

MicroRNAs (miRNAs), crucial post-transcriptional regulators, are closely linked to numerous diseases and are emerging as vitally significant biomarkers for ultra-early clinical diagnosis. Driven by advances in precision machining, nanomaterials, and artificial intelligence (AI), miRNA detection is transcending its former limitations to clinical application. This review covers innovative methods developed over the past five years, with a systematic analysis of the enhancement mechanisms, including signal amplification strategies, nanotechnology, clustered regularly interspaced short palindromic repeats and CRISPR-Cas systems, and integrated biosensors. Additionally, integrating advanced technologies such as machine learning, intelligent data processing and algorithms promise to enable more efficient and accurate miRNA detection. The innovative design of these next-generation methodologies effectively surmounts the limitations of conventional assays, achieving remarkable performance benchmarks including ultra-high sensitivity (extending to the attomolar level), exceptional specificity (capable of single-base discrimination), user-friendliness compatible with point-of-care testing (POCT), and even wearability, thereby promoting early diagnosis and personalized medicine.