DOI: 10.53941/mi.2026.100013 ISSN: 2982-2394

Breath-Based SERS Detection of Propofol Metabolites during Anesthesia Using Mesoporous Au Foam Chips

Guanghui An, Hui Zhang, Enduo Feng

Propofol anesthesia is commonly guided by hemodynamic signs, infusion parameters, and electroencephalography-derived indices, yet noninvasive molecular approaches for distinguishing anesthesia-related states remain limited. Here, we developed a mesoporous Au foam-based surface-enhanced Raman spectroscopy (SERS) chip for breath analysis of propofol metabolites signatures and anesthesia-state discrimination. The Au foam was fabricated by selective dealloying of Au-Ag alloy films, producing an interconnected ligament-pore architecture with a pore size of 55 nm and ligament width of 24 nm, which showed broad optical extinction near 785 nm, and strong SERS activity with an enhancement factor of approximately 6.84 × 105, as well as spatially uniform mapping over 30 × 30 μm2, batch-to-batch reproducibility, humidity tolerance, 30-day storage stability, and resistance to breath-like gas flow. Using propofol, 4-hydroxypropofol, propofol glucuronide, and propofol sulfate as representative targets, molecule-specific SERS fingerprints and marker peaks were identified, enabling excellent discrimination of these structurally related molecules with classification accuracy above 85% with multivariate analysis. Quantitatively, all of these selected marker peaks showed linear responses over 2–75 ppb, with detection limits down to 0.663 ppb and spike recoveries above 90% in artificial breath matrix. Finally, breath SERS fingerprints collected from awake/pre-anesthesia, propofol anesthesia, and recovery states were analyzed by spectral scoring, PCA, supervised classification, and anesthesia-probability output, which achieved an overall state-discrimination accuracy of 86.7%, demonstrating the potential of mesoporous Au foam SERS chips for noninvasive molecular assessment of propofol anesthesia-related breath states. This work offered a compact optical strategy for molecularly informed assessment of propofol anesthesia-related breath signatures.

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