DNA-AuNP encoders array Integrating a multi-modal coupled analysis approach for noninvasive precision screening of myocardial function injury disease in children

Limited-species serum biomarkers could only partially reflect the information on myocardial function injury disease in children, leading to some important information being inevitably lost, which affects the judgment of the whole information, resulting in a high rate of false positives and negatives. There is a critical unmet need for noninvasive precision screening for myocardial function injury disease in children. Here, we introduced a multi-modal coupled analysis of the DNA-AuNP encoders to achieve this goal. The DNA-AuNP encoders react with the serum specimen from myocardial function injury disease in children to generate the multi-modal response signal, such as the fluorescence spectrum, size distribution, and surface ζ-potential distribution. Interestingly, we used dark field microscopy to observe the interface changes between the DNA-AuNP encoder and serum at the microscopic level. Different machine learning algorithms analyze the correlation of a clinical outcome with multi-modal response signals from a target disease. As the number of modal response signals increases, our approach monotonically increases screening performance. The three-modal coupled analysis provided an average accuracy of up to 91.7% using 37 serum specimens in children from myocarditis, myocardial injury, and health. This study provides a highly generic tool for noninvasive screening using a drop of serum.