Miniaturized and portable device for Noninvasive, ultrasensitive and point-of-care diagnosis by engineered Metal-Carbide-based field effect transistor

Designing a non-invasive, portable, and ultrasensitive detection strategy is crucial for the clinical point-of-care diagnosis of liver cancer, particularly given the low abundance of liver cancer biomarkers in complex fluid samples. Field-effect transistors provide an efficient detection method that can be miniaturized and integrated. Additionally, exosomal microRNAs in urine offer a promising approach for minimally invasive detection of biological fluids. However, developing a strategy that meets the requirements of portability, non-invasiveness, and ultra-sensitivity remains a significant challenge. In this study, an interdigitated field-effect transistor that incorporates metal carbide@carbon nanotubes (MC@CNT-iFETs) as the semiconductor material is introduced, specifically designed for the efficient detection of exosomal microRNA-122. The unique two-dimensional structure of the metal carbide significantly enhances sensitivity, while the inclusion of carbon nanotubes improves the electrical conductivity and transconductance of the semiconductor by 0.83-fold and 0.42-fold, respectively. The MC@CNT-iFETs demonstrate a limit of detection for microRNA-122, as low as 0.12 fM. Furthermore, these devices exhibit high specificity, reproducibility, and stability. Clinically, MC@CNT-iFETs demonstrates a strong correlation with q-PCR results, effectively distinguishing between 25 healthy individuals and 25 patients with liver cancer (R 2  = 0.8977). Statistical analyses reveal significant differentiation between controls and patients with liver cancer. Receiver operating characteristic curve analysis yields an area under the curve of 0.9776. These findings highlight the potential of MC@CNT-iFETs for ultra-sensitive, non-invasive detection of liver cancer in complex biofluids, particularly by providing ultrasensitivity, portability, and non-invasive diagnosis capabilities in personalized diagnostics and medicine.