Evidence map›Paper›PMID 35002285›Full record

ArticleJournal of inflammation research2021

Establishment and Clinical Application of a Method for Detecting T Lymphocyte Subsets by Cellular Immunochip Technology.

Chen Chen, Yan-Mei Liu, Shu-Xia Xuan, Mei-Fang Zhou, Peng Zhou, Bin Cheng, Jin-Duan Lin, Wei-Guo Yin, Lin-Hai Li

Open access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 83% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Chen Chen *Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Yan-Mei Liu *Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Shu-Xia XuanDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Mei-Fang ZhouDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Peng ZhouDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Bin ChengDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Jin-Duan LinDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Wei-Guo YinDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Lin-Hai LiDepartment of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo establish and verify the method for detecting the immune phenotype of peripheral blood T lymphocytes by cellular immune chip technology, analyze the immune status, and discuss its clinical diagnostic value of different populations in the Qingyuan area.

methodsFirst, a cellular immune chip was used to detect the number of T lymphocyte subsets CD3+, CD4+, CD8+, and CD4/CD8, followed by evaluating the accuracy and precision through a comparison with flow cytometry. After passing the performance verification, a large-scale detection was performed by a cellular immune chip in 8389 cases. Immunochip technology detects the expression of T lymphocyte subsets and analyzes the differences in cellular immune function among people with physical examination, inflammation, and cancer, as well as different cancer types and in genders.

resultsThe cell immunochip method and flow cytometry method have the same accuracy and precision in detecting specimens, and the former is fast and simple, and is suitable for clinical use; big data analysis is expected to establish a reference range for CD3+, CD4+, and CD8+ T cell counts in Qingyuan. There are statistical differences in CD3+, CD4+, CD8+ T cell counts in physical examination, inflammation and cancer populations; there are also certain differences in CD3+, CD4+, CD8+ T cell counts and CD4/CD8 ratios between different cancer types and different diseases.

conclusionThe method of cell immunochip technology to detect T lymphocyte subsets is simple and practical, with accurate results and rapid detection. It can be used for immune function monitoring and treatment prognosis evaluation of people with different diseases, and it is worthy of popularization and application in clinical practice.

Indexed as

CD4/CD8cellular immune chipphysical examinationT lymphocyte

Identifiers

PMID35002285
PMCPMC8725877
OpenAlexW4205806767

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.