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            Free, publicly-accessible full text available May 5, 2026
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            Guha, Avirup; Sadeghi, Seyed Amirhossein; Kunhiraman, Harikrishnan Hyma; Fang, Fei; Wang, Qianyi; Rafieioskouei, Arshia; Grumelot, Shaun; Gharibi, Hassan; Saei, Amir Ata; Sayadi, Maryam; et al (, Chemical Engineering Journal)Free, publicly-accessible full text available April 1, 2026
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            Ashkarran, Ali Akbar; Gharibi, Hassan; Voke, Elizabeth; Landry, Markita P.; Saei, Amir Ata; Mahmoudi, Morteza (, Nature Communications)Abstract Robust characterization of the protein corona—the layer of proteins that spontaneously forms on the surface of nanoparticles immersed in biological fluids—is vital for prediction of the safety, biodistribution, and diagnostic/therapeutic efficacy of nanomedicines. Protein corona identity and abundance characterization is entirely dependent on liquid chromatography coupled to mass spectroscopy (LC-MS/MS), though the variability of this technique for the purpose of protein corona characterization remains poorly understood. Here we investigate the variability of LC-MS/MS workflows in analysis of identical aliquots of protein coronas by sending them to different proteomics core-facilities and analyzing the retrieved datasets. While the shared data between the cores correlate well, there is considerable heterogeneity in the data retrieved from different cores. Specifically, out of 4022 identified unique proteins, only 73 (1.8%) are shared across the core facilities providing semiquantitative analysis. These findings suggest that protein corona datasets cannot be easily compared across independent studies and more broadly compromise the interpretation of protein corona research, with implications in biomarker discovery as well as the safety and efficacy of our nanoscale biotechnologies.more » « less
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