An Optofluidic Platform for Cell-Counting Applications

dc.contributor.author Avcı, Meryem Beyza
dc.contributor.author Yaşar, S. Deniz
dc.contributor.author Çetin, Arif E.
dc.date.accessioned 2023-06-19T20:56:12Z
dc.date.available 2023-06-19T20:56:12Z
dc.date.issued 2023
dc.description.abstract Cell-counting is critical for a wide range of applications, e.g., life sciences, medicine, or pharmacology. Hemocytometry is a classical method that requires manual counting of cells under a microscope. This methodology is low-cost but manual counting is slow, and the test accuracy is limited by the operator experience. Accuracy and throughput of such application could be improved with the use of automated cell-counting devices. Possessing the ability of recording and processing cell images, devices employing these technologies could dramatically improve the accuracy of the counting results. However, accuracy of these devices still requires further improvement as the counting results rely only on 100-200 cells. Furthermore, the test cost of these devices increases due to the need for a counting chamber or consumables compatible with their hardware settings. Herein, in order to address these drawbacks, we introduced an optofluidic cell-counting platform that could scan more than 2000 cells, which dramatically improves the test accuracy. Our technology could yield an error rate below 1% for cell viability, and below 5% for cell concentration. The platform could deliver the count results within only similar to 1 minute, including sample loading, autofocusing, recording images, and image processing. The presented platform also benefits from a built-in fluidic component that eliminates the need for an external counting chamber, and allows fully automated sample loading and self-cleaning modality compatible with any solutions that are typically used for cell-counting tests. Providing an easy-to-use and rapid feature from sample loading to image analyses, our optofluidic platform could be a critical asset for accurate and low cost cell-counting applications. en_US
dc.description.sponsorship Scientific and Technological Research Council of Turkiye (TUBITAK) [121E620] en_US
dc.description.sponsorship A. E. C. acknowledges The Scientific and Technological Research Council of Turkiye (TUBITAK) under Project No. 121E620. en_US
dc.identifier.doi 10.1039/d3ay00344b
dc.identifier.issn 1759-9660
dc.identifier.issn 1759-9679
dc.identifier.scopus 2-s2.0-85158886880
dc.identifier.uri https://doi.org/10.1039/d3ay00344b
dc.identifier.uri https://hdl.handle.net/20.500.14365/4677
dc.language.iso en en_US
dc.publisher Royal Soc Chemistry en_US
dc.relation.ispartof Analytical Methods en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Proteomic Analysis en_US
dc.subject Assays en_US
dc.title An Optofluidic Platform for Cell-Counting Applications en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Cetin, Arif Engin/0000-0002-0788-8108
gdc.author.id Yasar, S. Deniz/0009-0004-2636-1995
gdc.author.institutional
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gdc.author.scopusid 58243036500
gdc.author.scopusid 35291427500
gdc.author.wosid Cetin, Arif Engin/ABI-4321-2020
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Avci, Meryem Beyza; Yasar, S. Deniz; Cetin, Arif E.] Izmir Biomed & Genome Ctr, TR-35340 Izmir, Turkiye; [Avci, Meryem Beyza] Izmir Univ Econ, Dept Elect & Elect Engn, TR-35330 Izmir, Turkiye; [Yasar, S. Deniz] Izmir Katip Celebi Univ, Dept Biomed Engn, TR-35620 Izmir, Turkiye en_US
gdc.description.endpage 2252 en_US
gdc.description.issue 18 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 2244 en_US
gdc.description.volume 15 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W4362684189
gdc.identifier.pmid 37128772
gdc.identifier.wos WOS:000978875600001
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gdc.index.type PubMed
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gdc.oaire.keywords Microscopy
gdc.oaire.keywords Image Processing, Computer-Assisted
gdc.oaire.keywords Medicine
gdc.oaire.keywords Cell Count
gdc.oaire.popularity 4.35603E-9
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gdc.opencitations.count 5
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