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      Label-free detection of nanoparticles using depth scanning correlation interferometric microscopy

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          Abstract

          Single particle level visualization of biological nanoparticles such as viruses and exosomes is challenging due to their small size and low dielectric contrast. Fluorescence based methods are highly preferred, however they require labelling which may perturb the functionality of the particle of interest. On the other hand, wide-field interferometric microscopy can be used to detect sub-diffraction limited nanoparticles without using any labels. Here we demonstrate that utilization of defocused images enhances the visibility of nanoparticles in interferometric microscopy and thus improves the detectable size limit. With the proposed method termed as Depth Scanning Correlation (DSC) Interferometric Microscopy, we experimentally demonstrate the detection of sub-35nm dielectric particles without using any labels. Furthermore, we demonstrate direct detection of single exosomes. This label-free and high throughput nanoparticle detection technique can be used to sense and characterize biological particles over a range between a few tens to a few hundred nanometers, where conventional methods are insufficient.

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          Most cited references24

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          Far-field optical nanoscopy.

          In 1873, Ernst Abbe discovered what was to become a well-known paradigm: the inability of a lens-based optical microscope to discern details that are closer together than half of the wavelength of light. However, for its most popular imaging mode, fluorescence microscopy, the diffraction barrier is crumbling. Here, I discuss the physical concepts that have pushed fluorescence microscopy to the nanoscale, once the prerogative of electron and scanning probe microscopes. Initial applications indicate that emergent far-field optical nanoscopy will have a strong impact in the life sciences and in other areas benefiting from nanoscale visualization.
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            Direct stochastic optical reconstruction microscopy with standard fluorescent probes.

            Direct stochastic optical reconstruction microscopy (dSTORM) uses conventional fluorescent probes such as labeled antibodies or chemical tags for subdiffraction resolution fluorescence imaging with a lateral resolution of ∼20 nm. In contrast to photoactivated localization microscopy (PALM) with photoactivatable fluorescent proteins, dSTORM experiments start with bright fluorescent samples in which the fluorophores have to be transferred to a stable and reversible OFF state. The OFF state has a lifetime in the range of 100 milliseconds to several seconds after irradiation with light intensities low enough to ensure minimal photodestruction. Either spontaneously or photoinduced on irradiation with a second laser wavelength, a sparse subset of fluorophores is reactivated and their positions are precisely determined. Repetitive activation, localization and deactivation allow a temporal separation of spatially unresolved structures in a reconstructed image. Here we present a step-by-step protocol for dSTORM imaging in fixed and living cells on a wide-field fluorescence microscope, with standard fluorescent probes focusing especially on the photoinduced fine adjustment of the ratio of fluorophores residing in the ON and OFF states. Furthermore, we discuss labeling strategies, acquisition parameters, and temporal and spatial resolution. The ultimate step of data acquisition and data processing can be performed in seconds to minutes.
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              STED microscopy reveals crystal colour centres with nanometric resolution

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                Author and article information

                Contributors
                aozkumur@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 June 2019
                21 June 2019
                2019
                : 9
                : 9012
                Affiliations
                [1 ]ISNI 0000000106887552, GRID grid.15876.3d, Department of Electrical and Electronics Engineering, , Koç University, ; Istanbul, Turkey
                [2 ]ISNI 0000000106887552, GRID grid.15876.3d, Research Center for Translational Medicine (KUTTAM), , Koç University, ; Istanbul, Turkey
                [3 ]ISNI 0000 0001 2331 4764, GRID grid.10359.3e, Department of Electrical and Electronics Engineering, , Bahçeşehir University, ; Istanbul, Turkey
                [4 ]ISNI 0000 0004 1936 7558, GRID grid.189504.1, Department of Electrical and Computer Engineering, , Boston University, ; Boston, Massachusetts USA
                Author information
                http://orcid.org/0000-0003-2044-5026
                Article
                45439
                10.1038/s41598-019-45439-x
                6588623
                31227754
                1c383ca1-d982-4873-b815-3f4f61651a95
                © The Author(s) 2019

                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/.

                History
                : 3 December 2018
                : 14 May 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004410, Türkiye Bilimsel ve Teknolojik Araştirma Kurumu (Scientific and Technological Research Council of Turkey);
                Award ID: 115E260
                Award Recipient :
                Categories
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                © The Author(s) 2019

                Uncategorized
                imaging and sensing,interference microscopy
                Uncategorized
                imaging and sensing, interference microscopy

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