Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/85865
Title: Validation of size estimation of nanoparticle tracking analysis on polydisperse macromolecule assembly
Authors: Kim, Ahram
Ng, Wei Beng
Bernt, William
Cho, Nam-Joon
Keywords: DRNTU::Engineering::Materials
Nanoscale Biophysics
Nanoparticles
Issue Date: 2019
Source: Kim, A., Ng, W. B., Bernt, W., & Cho, N.-J. (2019). Validation of size estimation of nanoparticle tracking analysis on polydisperse macromolecule assembly. Scientific Reports, 9, 2639-. doi:10.1038/s41598-019-38915-x
Series/Report no.: Scientific Reports
Abstract: As the physicochemical properties of drug delivery systems are governed not only by the material properties which they are compose of but by their size that they conform, it is crucial to determine the size and distribution of such systems with nanometer-scale precision. The standard technique used to measure the size distribution of nanometer-sized particles in suspension is dynamic light scattering (DLS). Recently, nanoparticle tracking analysis (NTA) has been introduced to measure the diffusion coefficient of particles in a sample to determine their size distribution in relation to DLS results. Because DLS and NTA use identical physical characteristics to determine particle size but differ in the weighting of the distribution, NTA can be a good verification tool for DLS and vice versa. In this study, we evaluated two NTA data analysis methods based on maximum-likelihood estimation, namely finite track length adjustment (FTLA) and an iterative method, on monodisperse polystyrene beads and polydisperse vesicles by comparing the results with DLS. The NTA results from both methods agreed well with the mean size and relative variance values from DLS for monodisperse polystyrene standards. However, for the lipid vesicles prepared in various polydispersity conditions, the iterative method resulted in a better match with DLS than the FTLA method. Further, it was found that it is better to compare the native number-weighted NTA distribution with DLS, rather than its converted distribution weighted by intensity, as the variance of the converted NTA distribution deviates significantly from the DLS results.
URI: https://hdl.handle.net/10356/85865
http://hdl.handle.net/10220/48241
DOI: http://dx.doi.org/10.1038/s41598-019-38915-x
Rights: © 2019 The Author(s) (Nature Publishing Group). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MSE Journal Articles

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.