Rapid and sensitive detection of heart-type fatty acid binding protein using aggregation-induced emission nanoparticles on digital microfluidics workstation.

Early and rapid diagnostic of acute myocardial infarction (AMI) during its developing stage is crucial due to its high fatality rate. Heart-type fatty acid binding protein (h-FABP) is an ideal biomarker for the quantitative diagnosis of AMI, surpassing traditional markers such as myoglobin, creatine phosphokinase-MB, and troponin in terms of sensitivity, specificity, and prognostic value. To obtain diagnostic and prognostic information, a precise and fully quantitative measurement of h-FABP is essential, typically achieved through an immunosorbent assay like the enzyme-linked immunosorbent assay. Nevertheless, this method has several limitations, including extended detection time, complex assay procedures, the necessity for skilled technicians, and challenges in implementing automated detection. This research introduces a novel biosensor, utilizing aggregation-induced emission nanoparticles (AIENPs) and integrated with a digital microfluidic (DMF) workstation, designed for the sensitive, rapid, and automated detection of h-FABP in low-volume serum samples. AIENPs and magnetic beads in nanoscale were served as the capture particles and the fluorescent probe, which were linked covalently to anti-h-FABP antibodies respectively. The approach was based on a sandwich immunoassay and performed on a fully automated DMF workstation with assay time by 15 min. We demonstrated the determination of h-FABP in serum samples with detection limit of 0.14 ng/mL using this biosensor under optimal condition. Furthermore, excellent correlations (R = 0.9536, n = 50) were obtained between utilizing this biosensor and commercialized ELISA kits in clinical serum detecting. These results demonstrate that our flexible and reliable biosensor is suitable for direct integration into clinical diagnostics, and it is expected to be promising diagnostic tool for early detection and screening tests as well as prognosis evaluation for AMI patients.