Back to Journals » International Journal of Nanomedicine » Volume 14

Optical fiber-based sensing method for nanoparticle detection through supervised back-scattering analysis: a potential contributor for biomedicine

Authors Paiva JS, Jorge PAS, Ribeiro RSR, Sampaio P, Rosa CC, Cunha JPS

Received 11 October 2018

Accepted for publication 10 January 2019

Published 2 April 2019 Volume 2019:14 Pages 2349—2369

DOI https://doi.org/10.2147/IJN.S174358

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Cristina Weinberg

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Anderson Oliveira Lobo


Joana S Paiva,1–3 Pedro AS Jorge,1,2 Rita SR Ribeiro,1 Paula Sampaio,4 Carla C Rosa,1,2 João PS Cunha1,3

1INESC Technology and Science, Porto, Portugal; 2Physics and Astronomy Department, Faculty of Sciences, University of Porto, Porto, Portugal; 3Faculty of Engineering, University of Porto, Porto, Portugal; 4Institute for Molecular and Cell Biology, i3S – Institute for Innovation and Research in Health, Porto, Portugal

Background: In view of the growing importance of nanotechnologies, the detection/identification of nanoparticles type has been considered of utmost importance. Although the characterization of synthetic/organic nanoparticles is currently considered a priority (eg, drug delivery devices, nanotextiles, theranostic nanoparticles), there are many examples of “naturally” generated nanostructures – for example, extracellular vesicles (EVs), lipoproteins, and virus – that provide useful information about human physiology or clinical conditions. For example, the detection of tumor-related exosomes, a specific type of EVs, in circulating fluids has been contributing to the diagnosis of cancer in an early stage. However, scientists have struggled to find a simple, fast, and low-cost method to accurately detect/identify these nanoparticles, since the majority of them have diameters between 100 and 150 nm, thus being far below the diffraction limit.
Methods: This study investigated if, by projecting the information provided from short-term portions of the back-scattered laser light signal collected by a polymeric lensed optical fiber tip dipped into a solution of synthetic nanoparticles into a lower features dimensional space, a discriminant function is able to correctly detect the presence of 100 nm synthetic nanoparticles in distilled water, in different concentration values.
Results and discussion: This technique ensured an optimal performance (100% accuracy) in detecting nanoparticles for a concentration above or equal to 3.89 µg/mL (8.74E+10 particles/mL), and a performance of 90% for concentrations below this value and higher than 1.22E03 µg/mL (2.74E+07 particles/mL), values that are compatible with human plasmatic levels of tumor-derived and other types of EVs, as well as lipoproteins currently used as potential biomarkers of cardiovascular diseases.
Conclusion: The proposed technique is able to detect synthetic nanoparticles whose dimensions are similar to EVs and other “clinically” relevant nanostructures, and in concentrations equivalent to the majority of cell-derived, platelet-derived EVs and lipoproteins physiological levels. This study can, therefore, provide valuable insights towards the future development of a device for EVs and other biological nanoparticles detection with innovative characteristics.

Keywords: optical fiber sensors, light scattering effects, nanoparticles detection, extracellular vesicles (EVs) detection, lipoproteins detection, virus detection, nanoparticles, Brownian motion, diffusive analysis


Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]  View Full Text [HTML][Machine readable]