Label-free quantification of cell-to-substrate separation by surface plasmon resonance microscopy

Taehwang Son; Jinwon Seo; In Hong Choi; Donghyun Kim

doi:10.1016/j.optcom.2017.10.001

Label-free quantification of cell-to-substrate separation by surface plasmon resonance microscopy

Taehwang Son, Jinwon Seo, In Hong Choi, Donghyun Kim

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

We study surface plasmon resonance microscopy (SPRM) for label-free quantification of cell-to-substrate separation. We have established a depth extraction model in which we compare a layered cell substrate model with resonance characteristics obtained by SPRM. We have applied the model to human aortic endothelial cell (HAEC) culture and determined the separation distance to be 40–60 nm. We have also investigated the precision of the SPRM model associated with the deviation in the model parameters, which is estimated to be 15 nm. The results can serve as the basis for more extensive cell-to-surface studies in a massive and automated way.

Original language	English
Pages (from-to)	64-68
Number of pages	5
Journal	Optics Communications
Volume	422
DOIs	https://doi.org/10.1016/j.optcom.2017.10.001
Publication status	Published - 2018 Sep 1

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation (NRF) grants funded by the Korean Government (NRF- 2012R1A4A1029061 and 2015R1A2A1A10052826 ).

Publisher Copyright:
© 2017 Elsevier B.V.

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Physical and Theoretical Chemistry
Electrical and Electronic Engineering

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10.1016/j.optcom.2017.10.001

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title = "Label-free quantification of cell-to-substrate separation by surface plasmon resonance microscopy",

abstract = "We study surface plasmon resonance microscopy (SPRM) for label-free quantification of cell-to-substrate separation. We have established a depth extraction model in which we compare a layered cell substrate model with resonance characteristics obtained by SPRM. We have applied the model to human aortic endothelial cell (HAEC) culture and determined the separation distance to be 40–60 nm. We have also investigated the precision of the SPRM model associated with the deviation in the model parameters, which is estimated to be 15 nm. The results can serve as the basis for more extensive cell-to-surface studies in a massive and automated way.",

author = "Taehwang Son and Jinwon Seo and Choi, {In Hong} and Donghyun Kim",

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AU - Son, Taehwang

AU - Seo, Jinwon

AU - Choi, In Hong

AU - Kim, Donghyun

N1 - Funding Information: This work was supported by the National Research Foundation (NRF) grants funded by the Korean Government (NRF- 2012R1A4A1029061 and 2015R1A2A1A10052826 ). Publisher Copyright: © 2017 Elsevier B.V.

PY - 2018/9/1

Y1 - 2018/9/1

N2 - We study surface plasmon resonance microscopy (SPRM) for label-free quantification of cell-to-substrate separation. We have established a depth extraction model in which we compare a layered cell substrate model with resonance characteristics obtained by SPRM. We have applied the model to human aortic endothelial cell (HAEC) culture and determined the separation distance to be 40–60 nm. We have also investigated the precision of the SPRM model associated with the deviation in the model parameters, which is estimated to be 15 nm. The results can serve as the basis for more extensive cell-to-surface studies in a massive and automated way.

AB - We study surface plasmon resonance microscopy (SPRM) for label-free quantification of cell-to-substrate separation. We have established a depth extraction model in which we compare a layered cell substrate model with resonance characteristics obtained by SPRM. We have applied the model to human aortic endothelial cell (HAEC) culture and determined the separation distance to be 40–60 nm. We have also investigated the precision of the SPRM model associated with the deviation in the model parameters, which is estimated to be 15 nm. The results can serve as the basis for more extensive cell-to-surface studies in a massive and automated way.

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Label-free quantification of cell-to-substrate separation by surface plasmon resonance microscopy

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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