Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/4677
Title: An optofluidic platform for cell-counting applications
Authors: Avcı, Meryem Beyza
Yaşar, S. Deniz
Çetin, Arif E.
Keywords: Proteomic Analysis
Assays
Publisher: Royal Soc Chemistry
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.
URI: https://doi.org/10.1039/d3ay00344b
https://hdl.handle.net/20.500.14365/4677
ISSN: 1759-9660
1759-9679
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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