Identification of extracellular vesicles from their Raman spectra via self-supervised learning.

Extracellular vesicles (EVs) released from cells attract interest for their possible role in health and diseases. The detection and characterization of EVs is challenging due to the lack of specialized methodologies. Raman spectroscopy, however, has been suggested as a novel approach for biochemical analysis of EVs.

Demonstrating low Raman background in UV-written SiO waveguides.

Raman spectroscopy can give a chemical 'fingerprint' from both inorganic and organic samples, and has become a viable method of measuring the chemical composition of single biological particles. In parallel, integration of waveguides and microfluidics allows for the creation of miniaturized optical sensors in lab-on-a-chip devices. The prospect of combining integrated optics and Raman spectroscopy for Raman-on-chip offers new opportunities for optical sensing.