Evidence map›Paper›PMID 40873777›Full record

ArticleJournal of inflammation research2025

Time-Course Renal and Pulmonary Injury Analysis and Bioinformatics Screening of Core Pathogenic Genes and Immune Cell Infiltration Patterns in a Sepsis.

Anwaier Apizi, Jian Li, Paiheriding Kamilijiang, Chun-Bo Yang, Zheng-Kai Wang, Rui-Feng Chai, Zhao-Xia Yu

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. Article
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

7 authors.

Anwaier Apizi *Department of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Jian Li *Department of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Paiheriding KamilijiangDepartment of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Chun-Bo YangDepartment of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Zheng-Kai WangDepartment of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Rui-Feng ChaiDepartment of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
Zhao-Xia YuDepartment of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to evaluate the extent of organ damage associated with sepsis and to identify key genes implicated in its pathogenesis. Methods: Eighteen rats were randomized into experimental and control groups. Cecal ligation and puncture induced sepsis in the experimental group, with lung and kidney inflammatory injury assessed at 12, 24, and 36 hours. Gene expression profiles of sepsis patients and healthy controls were obtained from Gene Expression Omnibus database. Weighted gene co-expression network analysis and bioinformatics identified sepsis-related pathways and core genes, constructing a predictive risk model. Immune cell composition was compared between groups, and correlations between core gene expression and immune cell populations were analyzed. Results: The experimental group exhibited greater lung and kidney tissue damage at all time points compared to the control group, with severity increasing over time. Cross-analysis identified 505 core genes associated with sepsis. Gene Ontology enrichment analysis revealed that differentially expressed genes were predominantly enriched in biological processes, molecular functions, cellular components, and the hematopoietic cell lineage pathway. A sepsis risk model constructed using five key genes- Conclusion: The severity of lung and kidney tissue damage in sepsis increased over time. The five identified sepsis-related genes have predictive value in assessing sepsis risk. Insights into the interactions between key genes and immune cell populations may contribute to improved clinical management of sepsis.

Indexed as

GEOimmune cell infiltrationkey genesnomogramsepsis

Identifiers

PMID40873777
PMCPMC12379963

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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.