Silent-region SERS detection of fatigue biomarkers based on Au@PB core-shell nanoprobes

Au@PB core-shell nanoprobes exploit the Raman silent region (2150 cm −1 ). • Signal-off SERS evades biological-matrix background in complex serum. • GOx/LOx cascades let one Au@PB reporter assay H 2 O 2 , glucose, lactate. • Detection limits reach 4.2 × 10 −10 to 1.17 × 10 −8  M for three analytes. • 91.4–106.6% serum recovery supports exercise-fatigue biomarker monitoring. Assaying exercise-related biochemical markers is important for elucidating the mechanisms of exercise metabolism and fatigue. However, conventional surface-enhanced Raman scattering (SERS) techniques are often limited by biological matrix background interference and fingerprint-region spectral overlap in complex biological fluids. To overcome these limitations, this study constructs a signal-off-type parallel SERS detection platform based on Au@PB core-shell nanostructures. The core design of the platform leverages the characteristic peak of the Prussian blue (PB) shell located in the Raman silent region (2150 cm −1 , C N stretching vibration) to avoid biological matrix background interference, and employs a signal-off mechanism in which hydrogen peroxide (H 2 O 2 ) triggers the quantitative attenuation of the PB silent-region peak intensity, enabling the same PB shell to function as both a SERS reporting unit and an H 2 O 2 -responsive unit. On this basis, H 2 O 2 , glucose (Glu), and lactate (LA) share a single signal-off-type Au@PB reporting molecule: H 2 O 2 directly triggers this attenuation, whereas Glu and LA are in situ converted into H 2 O 2 through enzymatic cascades of glucose oxidase (GOx) and lactate oxidase (LOx), respectively, which then triggers the same attenuation, thereby enabling three-target parallel analysis from a single reporter. Under optimized conditions, the platform exhibits good linearity and high sensitivity for H 2 O 2 (R 2  = 0.9953, LOD = 4.2 × 10 −10  M), Glu (R 2  = 0.9968, LOD = 3.76 × 10 −9  M), and LA (R 2  = 0.9977, LOD = 1.17 × 10 −8  M). The relative standard deviation (RSD) across 20 parallel samples is 2.8%–4.4%, and the spiked recoveries in real serum samples remain stable at 91.4%–106.6%. This anti-interference parallel analysis strategy provides a methodological basis for monitoring fatigue-related biochemical changes in real serum and demonstrates the distinctive advantages of silent-region SERS in complex biological matrix sensing. Download: Download high-res image (141KB) Download: Download full-size image