Computational On-Chip Imaging of Nanoparticles and Biomolecules using Ultraviolet Light
Author
Daloglu, Mustafa UgurRay, Aniruddha
Gorocs, Zoltan
Xiong, Matthew
Malik, Ravinder
Bitan, Gal
McLeod, Euan
Ozcan, Aydogan
Affiliation
Univ Arizona, Coll Optic SciIssue Date
2017-03-09
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NATURE PUBLISHING GROUPCitation
Computational On-Chip Imaging of Nanoparticles and Biomolecules using Ultraviolet Light 2017, 7:44157 Scientific ReportsJournal
Scientific ReportsRights
Copyright © The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Significant progress in characterization of nanoparticles and biomolecules was enabled by the development of advanced imaging equipment with extreme spatial-resolution and sensitivity. To perform some of these analyses outside of well-resourced laboratories, it is necessary to create robust and cost-effective alternatives to existing high-end laboratory-bound imaging and sensing equipment. Towards this aim, we have designed a holographic on-chip microscope operating at an ultraviolet illumination wavelength (UV) of 266 nm. The increased forward scattering from nanoscale objects at this short wavelength has enabled us to detect individual sub-30 nm nanoparticles over a large field-of- view of > 16 mm(2) using an on-chip imaging platform, where the sample is placed at <= 0.5 mm away from the active area of an opto-electronic sensor-array, without any lenses in between. The strong absorption of this UV wavelength by biomolecules including nucleic acids and proteins has further enabled high-contrast imaging of nanoscopic aggregates of biomolecules, e.g., of enzyme Cu/Zn-superoxide dismutase, abnormal aggregation of which is linked to amyotrophic lateral sclerosis (ALS)-a fatal neurodegenerative disease. This UV-based wide-field computational imaging platform could be valuable for numerous applications in biomedical sciences and environmental monitoring, including disease diagnostics, viral load measurements as well as air-and water-quality assessment.ISSN
2045-2322PubMed ID
28276489Version
Final published versionSponsors
Army Research Office (ARO) [W911NF-13-1-0419, W911NF-13-1-0197]; ARO Life Sciences Division; National Science Foundation (NSF) CBET Division Biophotonics Program; NSF Emerging Frontiers in Research and Innovation (EFRI) Award; NSF EAGER Award; NSF INSPIRE Award; NSF Partnerships for Innovation; Building Innovation Capacity (PFI: BIC) Program; Office of Naval Research (ONR); National Institutes of Health (NIH); Howard Hughes Medical Institute (HHMI); Vodafone Americas Foundation; Vodafone Americas Foundation, the Mary Kay Foundation; Steven & Alexandra Cohen Foundation; KAUST; RGK Foundation [20143057]; National Science Foundation [0963183]; American Recovery and Reinvestment Act of 2009 (ARRA)Additional Links
http://www.nature.com/articles/srep44157ae974a485f413a2113503eed53cd6c53
10.1038/srep44157
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License.
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