1：Experimental Design and Method Selection:

The study employed immuno-SERS (iSERS) microscopy using SERS-labelled antibodies against alpha-smooth muscle actin (SMA) for imaging SMCs in atherosclerotic plaques. Both direct (labelled primary antibody) and indirect (unlabelled primary and labelled secondary antibody) staining techniques were used, with comparisons made to wide-field immunofluorescence (IF) images. Confocal Raman microscopy with point mapping was utilized for iSERS imaging, and IF images were collected using an inverted fluorescence microscope.

2：Sample Selection and Data Sources:

Brachiocephalic artery cross-sections from six-month-old ApoE/LDLR?/? mice with established atherosclerosis were used. Samples were fixed in paraformaldehyde, embedded in paraffin, and sectioned into 5 μm-thick slices mounted on salinized glass slides. Deparaffinization and heat-induced epitope retrieval were performed before staining.

3：List of Experimental Equipment and Materials:

Instruments included a confocal Raman microscope (WITec Alpha 300), inverted fluorescence microscope (Axio Observer D.1), UV/Vis absorption spectrometer (Perkin-Elmer Lambda 950), TEM (Zeiss EM 910), and autostainer (Leica ST5010 Autostainer XL). Reagents included gold nanoparticles, antibodies (anti-SMA, secondary antibodies), SERS nanotags (Au nanostars functionalized with 4-NTB and SH-PEG-COOH), and various chemicals for synthesis and staining.

4：Experimental Procedures and Operational Workflow:

Synthesis of Au nanostars and SERS-labelled antibodies was performed, followed by preparation of artery cross-sections. Staining involved incubation with primary and/or secondary antibodies (SERS-labelled or fluorophore-labelled), with negative controls using BSA/PBS. Raman and IF images were collected, with laser power adjusted and step sizes varied for imaging. Data analysis included spectral preprocessing, cluster analysis (k-means), and segmentation using software tools.

5：Data Analysis Methods:

Raman spectra were preprocessed for cosmic rays removal and baseline correction. Cluster analysis (k-means with Manhattan distance) was used to classify pixels based on SERS signals. IF images were segmented using Ilastic software for object classification, and quantification of SMA-positive areas was performed with ImageJ software.