Evidence map›Paper›PMID 37932249›Full record

ArticleLight, science & applications2023

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

Abstract read
In one paragraph

Article in Light, science & applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Three-dimensional isotropic imaging of live suspension cells enabled by droplet microvortices.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

MinDong Sung *Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0002-5217-8877
Jong Hyun Kim *Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hyun-Seok Min *Tomocube, Inc, 155 Sinseong-ro, Shinsung-dong, Yuseong-gu, Daejeon, Republic of Korea.ORCID http://orcid.org/0000-0002-7435-7884
Sooyoung JangDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
JaeSeong HongDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
Bo Kyu ChoiDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
JuHye ShinDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Kyung Soo ChungDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. chungks@yuhs.ac.ORCID http://orcid.org/0000-0003-1604-8730
Yu Rang ParkDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea. yurangpark@yuhs.ac.ORCID http://orcid.org/0000-0002-4210-2094

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 (N = 8) and healthy controls (N = 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.

Identifiers

PMID37932249
PMCPMC10628166

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.