Single-cell and extracellular nano-vesicles biosensing through phase spectral analysis of optical fiber tweezers back-scattering signals

Diagnosis of health disorders relies heavily on detecting biological data and accurately observing pathological changes. A significant challenge lies in detecting targeted biological signals and developing reliable sensing technology for clinically relevant results. The combination of data analytics with the sensing abilities of Optical Fiber Tweezers (OFT) provides a high-capability, multifunctional biosensing approach for biophotonic tools. In this work, we introduced phase as a new domain to obtain light patterns in OFT back-scattering signals. By applying a multivariate data analysis procedure, we extract phase spectral information for discriminating micro and nano (bio)particles. A newly proposed method—Hilbert Phase Slope—presented high suitability for differentiation problems, providing features able to discriminate with statistical significance two optically trapped human tumoral cells (MKN45 gastric cell line) and two classes of non-trapped cancer-derived extracellular nanovesicles – an important outcome in view of the current challenges of label-free bio-detection for multifunctional single-molecule analytic tools. The light patterns in backscattering signals of Optical Fiber Tweezers (OFT) has been demonstrated able to discriminate a wide range of microparticles. Barros and Cunha take this a step further by extracting the phase spectral information from OFT backscattering signals. This approach allows for the detection and identification of tumoral cell and extracellular nanovesicle features in complex biological media.