Quantitative Fluorescence Sensing Through Highly Autofluorescent, Scattering, and Absorbing Media Using Mobile Microscopy

Zoltán Göröcs, Yair Rivenson, Hatice Ceylan Koydemir, Derek Tseng, Tamara L. Troy, Vasiliki Demas, Aydogan Ozcan

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Compact and cost-effective systems for in vivo fluorescence and near-infrared imaging in combination with activatable reporters embedded inside the skin to sample interstitial fluid or blood can enable a variety of biomedical applications. However, the strong autofluorescence of human skin creates an obstacle for fluorescence-based sensing. Here we introduce a method for quantitative fluorescence sensing through highly autofluorescent, scattering, and absorbing media. For this, we created a compact and cost-effective fluorescence microscope weighing
Original languageEnglish (US)
Pages (from-to)8989-8999
Number of pages11
JournalACS Nano
Volume10
Issue number9
DOIs
StatePublished - Sep 19 2016
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This project has been supported by Verily Life Sciences, LLC (formerly known as Google Life Sciences). The Ozcan Research Group at UCLA also acknowledges the support of the Presidential Early Career Award for Scientists and Engineers (PECASE), the Army Research Office (ARO; W911NF-13-1-0419 and W911NF-13-1-0197), the ARO Life Sciences Division, the National Science Foundation (NSF) CBET Division Biophotonics Program, the NSF Emerging Frontiers in Research and Innovation (EFRI) Award, the NSF EAGER Award, NSF INSPIRE Award, NSF Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Program, Office of Naval Research (ONR), the National Institutes of Health (NIH), the Howard Hughes Medical Institute (HHMI), Vodafone Americas Foundation, and KAUST. This work is based upon research performed in a laboratory renovated by the National Science Foundation under grant no. 0963183, which is an award funded under the American Recovery and Reinvestment Act of 2009 (ARRA). Furthermore, Y.R. is supported by the European Union’s Horizon 2020 research and innovation program under grant agreement no. H2020-MSCA-IF-2014-659595 (MCMQCT).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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