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Non-label immune cell state prediction using Raman spectroscopy
by
Ichimura, Taro
, Watanabe, Tomonobu M.
, Chiu, Liang-da
, Machiyama, Hiroaki
, Yamaguchi, Tomoyuki
, Fujita, Hideaki
, Fujita, Katsumasa
in
140/133
/ 631/1647
/ 631/57
/ Antibodies
/ CD28 antigen
/ CD3 antigen
/ Cell activation
/ Discriminant analysis
/ Humanities and Social Sciences
/ Immune system
/ Lymphocytes
/ Lymphocytes B
/ Lymphocytes T
/ multidisciplinary
/ Raman spectroscopy
/ Science
/ Spectroscopy
/ Spectrum analysis
/ T cell receptors
2016
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Non-label immune cell state prediction using Raman spectroscopy
by
Ichimura, Taro
, Watanabe, Tomonobu M.
, Chiu, Liang-da
, Machiyama, Hiroaki
, Yamaguchi, Tomoyuki
, Fujita, Hideaki
, Fujita, Katsumasa
in
140/133
/ 631/1647
/ 631/57
/ Antibodies
/ CD28 antigen
/ CD3 antigen
/ Cell activation
/ Discriminant analysis
/ Humanities and Social Sciences
/ Immune system
/ Lymphocytes
/ Lymphocytes B
/ Lymphocytes T
/ multidisciplinary
/ Raman spectroscopy
/ Science
/ Spectroscopy
/ Spectrum analysis
/ T cell receptors
2016
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Non-label immune cell state prediction using Raman spectroscopy
by
Ichimura, Taro
, Watanabe, Tomonobu M.
, Chiu, Liang-da
, Machiyama, Hiroaki
, Yamaguchi, Tomoyuki
, Fujita, Hideaki
, Fujita, Katsumasa
in
140/133
/ 631/1647
/ 631/57
/ Antibodies
/ CD28 antigen
/ CD3 antigen
/ Cell activation
/ Discriminant analysis
/ Humanities and Social Sciences
/ Immune system
/ Lymphocytes
/ Lymphocytes B
/ Lymphocytes T
/ multidisciplinary
/ Raman spectroscopy
/ Science
/ Spectroscopy
/ Spectrum analysis
/ T cell receptors
2016
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Non-label immune cell state prediction using Raman spectroscopy
Journal Article
Non-label immune cell state prediction using Raman spectroscopy
2016
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Overview
The acquired immune system, mainly composed of T and B lymphocytes, plays a key role in protecting the host from infection. It is important and technically challenging to identify cell types and their activation status in living and intact immune cells, without staining or killing the cells. Using Raman spectroscopy, we succeeded in discriminating between living T cells and B cells, and visualized the activation status of living T cells without labeling. Although the Raman spectra of T cells and B cells were similar, they could be distinguished by discriminant analysis of the principal components. Raman spectra of activated T cells with anti-CD3 and anti-CD28 antibodies largely differed compared to that of naïve T cells, enabling the prediction of T cell activation status at a single cell level. Our analysis revealed that the spectra of individual T cells gradually change from the pattern of naïve T cells to that of activated T cells during the first 24 h of activation, indicating that changes in Raman spectra reflect slow changes rather than rapid changes in cell state during activation. Our results indicate that the Raman spectrum enables the detection of dynamic changes in individual cell state scattered in a heterogeneous population.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
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