Real-time, automated, standardized, and transparent analysis of microfluidic nanoparticle data with RPSPASS
Year: 2026
Type: preprint
Abstract: ABSTRACT Extracellular vesicles (EVs) are lipid spheres released from cells. Research utilizing EVs has met several hurdles owing to the small size of the majority of EVs and other nanoparticles (<150 nm) and the lack of detection technologies capable of providing high-throughput single particle measurements at this scale. The use of high-throughput single particle measurements is critical for the assessment of EV heterogeneity and abundance which are features often used to assess the development of isolation protocols or particle characterization. The Coulter principle, known in the field as resistive pulse sensing (RPS), has been used for several decades to size and count cells. More recently, this technology has evolved to accommodate nanoparticle analysis. In the last decade a platform utilizing microfluidic resistive pulse sensing (MRPS) has been demonstrated for nanoparticles, offering ergonomic characterization of nanoparticles along with utilizing open format data. To date, assessment of MRPS accuracy and reporting standards have not been assessed. With the aim of increasing data accuracy, ergonomics, and reporting transparency, we developed a microfluidic resistive pulse sensing post-acquisition analysis software (RPSPASS) application for automated cohort calibration, population gating, statistical output, QC plot generation, alternative data file outputs, and standardized reporting templates.
Institutions: National Institutes of Health, National Institute of Neurological Disorders and Stroke, National Cancer Institute, Center for Cancer Research, National Institutes of Health Clinical Center, Ghent University, Cancer Research Institute Ghent, Baylor College of Medicine, Beth Israel Deaconess Medical Center, Harvard University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: G2948557063, G363592231, Integrative, multi-parametric characterization of the EV surface protein and nucleic acid landscape by nano-flow and sorting cytometry, DATA MANAGEMENT AND RESOURCE REPOSITORY FOR THE exRNA ATLAS PHASE II, Discovery of Tumor, Treatment Response, and Systems-based EVP Signatures, Biophysical Characterization of EVPs and other Macromolecular Nanoparticles
OpenAlex ID: W7147658247