High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules

Abstract

Design and synthesis of degradable nanoparticles are very important in drug delivery and biosensing fields. Although accurate assessment of nanoparticle degradation rate would improve the characterization and optimization of drug delivery vehicles, current methods rely on estimating the size of the particles at discrete points over time using, for example, electron microscopy or dynamic light scattering (DLS), among other techniques, all of which have drawbacks and practical limitations. There is a significant need for a high-throughput and cost-effective technology to accurately monitor nanoparticle degradation as a function of time and using small amounts of sample. To address this need, here we present two different computational imaging-based methods for monitoring and quantification of nanoparticle degradation. The first method is suitable for discrete testing, where a computational holographic microscope is designed to track the size changes of protease-sensitive protein-core nanoparticles following degradation, by periodically sampling a subset of particles mixed with proteases. In the second method, a sandwich structure was utilized to observe, in real-time, the change in the properties of liquid nanolenses that were self-assembled around degrading nanoparticles, permitting continuous monitoring and quantification of the degradation process. These cost-effective holographic imaging based techniques enable high-throughput monitoring of the degradation of any type of nanoparticle, using an extremely small amount of sample volume that is at least 3 orders of magnitude smaller than what is required by, for example, DLS-based techniques.

Deep Learning Enables High-Throughput Analysis of Particle-Aggregation-Based Biosensors Imaged Using Holography

“…23 Here we used a micro-particle-based assay due to its inherent larger particle size and high particle scattering cross section that can be easily and rapidly detected using a single snapshot hologram captured with a simple and cost-effective lens-free on-chip microscope. However, this method can also be easily adapted for imaging and characterizing sub-micron sized particles by implementing techniques developed for lens-free on-chip microscopes such as holographic pixel super-resolution, [24][25][26] polymer nano-lenses, [27][28][29] and/or using ultraviolet (UV) illumination. 30 Another advantage of our presented method is the ability to rapidly characterize a wide range of micro-particle concentrations, even in 3D, including low concentrations, unlike the bulk-effect visual techniques which require extremely high concentrations of micro-particles.…”

Automated detection of apoptotic versus nonapoptotic cell death using label‐free computational microscopy

“…The in‐line holograms of each individual cells were recorded using the CMOS camera. Image reconstruction was performed by back‐propagating the holograms to the object plane, using the angular spectrum approach [53,56,57,96]. In this approach, the image is recovered by taking the inverse Fourier transform of the product of the transfer function and Fourier transform of the raw hologram, which is mathematically written as: [53] where, is the reconstructed complex wave field of the imaging object and , captured hologram.…”

Diagnosis of Herpes Simplex Virus: Laboratory and Point-of-Care Techniques

“…Digital Holographic Microscopy: Digital holographic microscopy (DHM) is an interferometric technique that has been extensively used for the detection and imaging of biological samples [ 36 , 74 , 75 , 76 , 77 , 78 ]. In this type of computational microscopy, the images are digitally reconstructed from holograms, which result from the interference between the scattered optical wave and the non-diffractive wave [ 79 ].…”