Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker

MinDong Sung; Jong Hyun Kim; Hyun-Seok Min; Sooyoung Jang; JaeSeong Hong; Bo Kyu Choi; JuHye Shin; Kyung Soo Chung; Yu Rang Park

doi:10.1038/s41377-023-01309-w

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Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker

Original Articles

- Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker
- Light: Science & Applications Vol. 12, Issue 12, Pages: 2565-2576(2023)
- Affiliations：
  
  1.Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
  2.Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
  3.Tomocube, Inc, 155 Sinseong-ro, Shinsung-dong, Yuseong-gu, Daejeon, Republic of Korea
- Author bio：
  
  Kyung Soo Chung (chungks@yuhs.ac)
  Yu Rang Park (yurangpark@yuhs.ac)
- Funds：
- DOI：10.1038/s41377-023-01309-w
  CLC：
- Published：31 December 2023，
  
  Published Online：07 November 2023，
  
  Received：19 May 2023，
  
  Revised：20 September 2023，
  
  Accepted：13 October 2023
- Accepted：
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Sung, M. D. et al. Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker. Light: Science & Applications, 12, 2565-2576 (2023).
DOI：

Sung, M. D. et al. Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker. Light: Science & Applications, 12, 2565-2576 (2023). DOI： 10.1038/s41377-023-01309-w.

摘要

Abstract

Sepsis is a dysregulated immune response to infection that leads to organ dysfunction and is associated with a high incidence and mortality rate. The lack of reliable biomarkers for diagnosing and prognosis of sepsis is a major challenge in its management. We aimed to investigate the potential

of three-dimensional label-free CD8 + T cell morphology as a biomarker for sepsis. This study included three-time points in the sepsis recovery cohort (

= 8) and healthy controls (

= 20). Morphological features and spatial distribution within cells were compared among the patients' statuses. We developed a deep learning model to predict the diagnosis and prognosis of sepsis using the internal cell morphology. Correlation between the morphological features and clinical indices were analysed. Cell morphological features and spatial distribution differed significantly between patients with sepsis and healthy controls and between the survival and non-survival groups. The model for predicting the diagnosis and prognosis of sepsis showed an area under the receiver operating characteristic curve of nearly 100% with only a few cells

and a strong correlation between the morphological features and clinical indices was observed. Our study highlights the potential of three-dimensional label-free CD8 + T cell morphology as a promising biomarker for sepsis. This approach is rapid

requires a minimum amount of blood samples

and has the potential to provide valuable information for the early diagnosis and prognosis of sepsis.

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Keywords

references

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