Evidence map›Paper›PMID 39429885›Full record

ArticleiMeta2024

TCellSI: A novel method for T cell state assessment and its applications in immune environment prediction.

Jing-Min Yang, Nan Zhang, Tao Luo, Mei Yang, Wen-Kang Shen, Zhen-Lin Tan, Yun Xia, Libin Zhang, Xiaobo Zhou, Qian Lei and 1 more

Abstract read
In one paragraph

Article in iMeta, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

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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

11 authors.

Jing-Min YangHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.ORCID 0009-0006-7126-9017
Nan ZhangHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.ORCID https://orcid.org/0000-0001-6518-2501
Tao LuoBGI Education Center University of Chinese Academy of Sciences Shenzhen China.
Mei YangHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.
Wen-Kang ShenHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.
Zhen-Lin TanHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.
Yun XiaHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.
Libin ZhangHubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology Huazhong University of Science and Technology Wuhan China.
Xiaobo ZhouCenter for Computational Systems Medicine, School of Biomedical Informatics The University of Texas Health Science Center at Houston Houston Texas USA.
Qian LeiDepartment of Thoracic Surgery West China Biomedical Big Data Center, West China Hospital, Sichuan University Chengdu China.
An-Yuan GuoDepartment of Thoracic Surgery West China Biomedical Big Data Center, West China Hospital, Sichuan University Chengdu China.ORCID https://orcid.org/0000-0002-5099-7465

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

T cell is an indispensable component of the immune system and its multifaceted functions are shaped by the distinct T cell types and their various states. Although multiple computational models exist for predicting the abundance of diverse T cell types, tools for assessing their states to characterize their degree of resting, activation, and suppression are lacking. To address this gap, a robust and nuanced scoring tool called T cell state identifier (TCellSI) leveraging Mann-Whitney

Indexed as

immune profilingimmunotherapyTCellSIT cell statesTCSS

Identifiers

PMID39429885
PMCPMC11487559

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.