Presentation Information
[9p-N304-6]Sensitive and Single-Nanoparticle Profiling of Biofluids Using Deep Nanometry
〇Sadao Ota1, Yuichiro Iwamoto1 (1.RCAST)
Keywords:
Bioparticle analysis,Representation Learning Cytometry
Deep Nanometry is an optical nanoparticle analysis platform that combines high-throughput scattering detection with unsupervised deep-learning-based denoising. By learning instrument-specific background noise and recovering weak particle signals, the method enables sensitive and scalable detection of nanoscale particles. In this talk, I will introduce the principle of Deep Nanometry, its validation using low-SNR nanoparticle signals, and its performance in detecting particles down to approximately 30 nm at throughput exceeding 100,000 events per second. I will also discuss its application to extracellular vesicle analysis, including rare CD9/CD147 double-positive EV detection in serum and profiling of colorectal cancer-associated EVs, highlighting its potential as a platform for liquid biopsy and large-scale biofluid nanoparticle profiling.