Evidence map›Paper›PMID 40896540›Full record

ArticleJournal of inflammation research2025

Dysregulated Immune Responses in Sepsis: Insights From Treg-Related Gene Expression.

Guangyan Zhu, Yanlin Liao, Simin Liu, Ping Liu, Kai Yang, Minghe Tan, Lisha Yi, Dingyu Zhang, Haifa Xia

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Guangyan Zhu *Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Yanlin Liao *Department of Surgical Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Simin LiuDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Ping LiuDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Kai YangDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Minghe TanDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Lisha YiDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Dingyu ZhangWuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, People's Republic of China.
Haifa XiaDepartment of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Sepsis, a life-threatening dysregulated immune response to infection, has a high global mortality rate. Tregs play dual roles in sepsis pathogenesis, with their expansion linked to immunosuppression. This study explores Treg dynamics and the novel role of CD82 in sepsis. Methods: Peripheral blood from sepsis patients was analyzed using scRNA-seq. Machine learning (SVM, LASSO, random forest) integrated scRNA-seq data with three GEO datasets (n=380) to identify biomarkers. CD82 expression in Tregs was validated via flow cytometry and RT-qPCR in CLP mouse model. Anti-CD25 antibody depleted Tregs in mice. Results: The scRNA-seq revealed neutrophil expansion and T/NK cell reduction in sepsis. Tregs were enriched and exhibited CD82 upregulation. A seven-gene diagnostic signature (CD82, CD52, EVI2B, IL32, RCAN3, AQP3, NAP1L1) achieved high accuracy (AUCs up to 99.9%). Treg-depleted CLP mice showed reduced CD82 expression, elevated IL-6 and neutrophils, and worsened inflammation, implicating CD82 in immune modulation. Discussion: CD82 may mediate Treg hyperactivation during sepsis, balancing the immune response and suppression. The gene signature shows diagnostic potential, but CD82's mechanistic role needs further investigation. Therapeutic targeting of CD82 could improve sepsis management.

Indexed as

logistic regressionmachine learning methodsepsissingle-cell analysisTreg

Identifiers

PMID40896540
PMCPMC12399092

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.