Serum metabolic fingerprinting on Ag@AuNWs for traumatic brain injury diagnosis.

Abstract

Accurate and rapid diagnosis of traumatic brain injury (TBI) is very important for high quality medical services. Nonetheless, the current diagnostic platform still has challenges in the rapid and accurate analysis of clinical samples. Here, we prepared a highly stable, repeatable and sensitive gold-plated silver core-shell nanowire (Ag@AuNWs) for surface-enhanced Raman spectroscopy (SERS) metabolic fingerprint diagnosis of TBI. The core-shell structure significantly enhanced SERS intensity and enables the direct detection of 10μl serum within seconds. The principal component analysis-linear discriminant analysis (PCA-LDA) and partial least squares-DA (PLS-DA) are used to evaluate the classification effect of this technology on TBI, respectively. The diagnosis accuracy rate of PCA-LDA and PLS-DA is 73.3% and 86.7% for diagnosing TBI, respectively. Consequently, the PLS-DA model is the optimal selection for distinguishing between the TBI and sham groups. This research will facilitate the application-oriented creation of novel materials with tailored structural designs and the formulation of innovative precision medical protocols in the imminent future.