2017
DOI: 10.1109/jstqe.2016.2639824
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Robust Visualization and Discrimination of Nanoparticles by Interferometric Imaging

Abstract: Single-molecule and single-nanoparticle biosensors are a growing frontier in diagnostics. Digital biosensors are those which enumerate all specifically immobilized biomolecules or biological nanoparticles, and thereby achieve limits of detection usually beyond the reach of ensemble measurements. Here we review modern optical techniques for single nanoparticle detection and describe the single-particle interferometric reflectance imaging sensor (SP-IRIS). We present challenges associated with reliably detecting… Show more

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Cited by 33 publications
(35 citation statements)
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“…The conjugated GNRs were diluted to a range of concentrations between 100 attomolar and 100 picomolar, then incubated with the DNA chips for 4 hours, then finally washed and dried. A total of 70 spots were imaged with instrument using both the 10x and 50x objective, and images were analyzed using custom particle analysis software described previously 29 . As anticipated, the 10x objective system accurately enumerated immobilized GNRs when they were few (i.e., 60 GNR per spot of fewer), but systematically under-counted as their number increased (Figure 2d).…”
Section: Resultsmentioning
confidence: 99%
“…The conjugated GNRs were diluted to a range of concentrations between 100 attomolar and 100 picomolar, then incubated with the DNA chips for 4 hours, then finally washed and dried. A total of 70 spots were imaged with instrument using both the 10x and 50x objective, and images were analyzed using custom particle analysis software described previously 29 . As anticipated, the 10x objective system accurately enumerated immobilized GNRs when they were few (i.e., 60 GNR per spot of fewer), but systematically under-counted as their number increased (Figure 2d).…”
Section: Resultsmentioning
confidence: 99%
“…GNRs in each region and timepoint were detected independently. The particle detection method described here is a refinement of methods described earlier (21,28), and has three steps: preprocessing, key point detection and key point filtering. First, a sparse pseudo-median filter is applied to each frame of the z-stack (made available online by others at http://imagejdocu.tudor.lu/doku.php?id=plugin:filte r:fast_filters:start) to estimate the image background.…”
Section: Image Processing and Particle Detectionmentioning
confidence: 99%
“…Single biological nanoparticles result in small, diffraction-limited perturbations in the reflected field, between 0.5% (around 60-nm diameter) and 10% (around 150-nm diameter). The excellent flatness and smoothness of the Si-SiO 2 substrate is a critical component for SP-IRIS, because it enables the detection of diffraction-limited spots that are only 0.5% dimmer (or brighter, depending on the objective's plane of focus [24]) than the reference field even in the absence of dynamic measurements. This in turn allows the stage to be scanned, which enables a region of interest much larger than a single field of view.…”
Section: Application Of Interference Reflectance Imaging To Bnp Detecmentioning
confidence: 99%
“…In later studies, a high numerical aperture objective was used to detect the faint interference signal from individual virions. Calculating the size of a particle from the brightness of the resulting spot was nontrivial, because increasing the particle size increases the position of its centroid above the reflecting surface, thereby slightly increasing the optical path length difference between forward-and back-scattered light [24]. Once the substrate film thickness and surface morphology were optimized, individual BNPs ranging from 50 nm to 200 nm were detected by affinitybased capture in various complex media with SP-IRIS [88].…”
Section: Importance Of Surface Morphology In Single Particle Optical mentioning
confidence: 99%
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