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