Dataset for SERS-Based EV Detection of Hepatotoxicity

This dataset supports our study on the label-free detection of drug-induced liver injury (hepatotoxicity) using <b>surface-enhanced Raman spectroscopy (SERS) of extracellular vesicles (EVs)</b>. Our platform enables rapid and sensitive analysis of EV molecular content, requiring only <b>1.3 microliters</b> of sample and providing results in under <b>ten minutes</b>. Using hepatic cell cultures exposed to <b>acetaminophen</b>, we captured distinct and reproducible <b>EV spectral signatures</b> that correlate strongly with conventional hepatotoxicity biomarkers.The dataset includes:<b>Raw and processed Raman spectra</b> of EVs under different conditions<b>Code for spectral preprocessing, feature selection, and regression analysis</b><b>Figures illustrating spectral differences, statistical analysis, and model performance</b><b>Supplementary data, including control experiments and validation results</b>Our findings demonstrate the potential of <b>EV-based SERS for dynamic monitoring of drug responses</b>, offering a non-invasive and scalable tool for hepatotoxicity assessment.<b>Folder Structure</b>📂 <b>Fig 1 - Fig 5</b> <i>(Each contains associated data, code, and figures)</i><br>📂 <b>Supplementary</b> <i>(Additional validation and extended data figures: FigS1, FigS2, FigS3)</i><b>Data Availability &amp; Reuse</b><b>License:</b> <i>CC BY 4.0</i> (Attribution Required)Further information is available from the corresponding author upon request.This dataset enables further exploration of <b>Raman-based EV sensing</b>, hepatotoxicity assessment, and spectral analysis methodologies. For questions or collaboration inquiries, please contact <b>[e-mail] / [e-mail] / [e-mail]</b>.