Evidence mapPaperPMID 41555186Full record

ArticleImmunity, inflammation and disease2026

Integrated Analysis of the Immune Infiltration Pattern and Novel Diagnostic Biomarkers in Septic Cardiomyopathy.

Wei Liu, Xi Zheng, Dong Wang, Jingyi Wang, Xincheng Li, Fei Li, Wenxiong Li, Jin Zhang

Abstract read
In one paragraph

Article in Immunity, inflammation and disease, 2026. 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

8 authors.

Wei LiuDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0009-3045-7056
Xi ZhengDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-3976-4510
Dong WangDepartment of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0005-6834-6184
Jingyi WangDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-7283-9580
Xincheng LiDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0009-2806-9644
Fei LiDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-2872-5313
Wenxiong LiDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0009-0098-7312
Jin ZhangDepartment of SICU, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0009-6207-1051

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn this study, various informatics analyses were employed to identify the hub genes associated with septic cardiomyopathy (SCM) onset and investigate their immune infiltration status.

methodsHigh-throughput sequencing data of myocardial tissue samples from mice with SCM were obtained from the GEO database and our previously published articles. The Limma and weighted gene co-expression network analysis (WGCNA) packages were used to identify the hub genes associated with SCM onset. GSEA and the DAVID database were employed for gene enrichment analysis. Additionally, the CIBERSORT database was used to analyze the immune infiltration in SCM. Finally, the multiMiR package was used to analyze the microRNAs acting as ceRNAs for the hub genes. Receiver operating characteristic (ROC) curves and Mendelian randomization analysis were used to evaluate the predictive value of hub genes for SCM.

resultsThe SCM group included nine samples, while the control group included ten samples. SCM upregulated 15 genes and downregulated 7. Mt1 and Actc1 were the most significantly upregulated and downregulated, respectively. GO analysis indicated that the most significantly enriched biological process was "response to bacterium," and the most enriched signaling pathway was "mineral absorption." Immunoinfiltration analysis revealed decreased T cells CD4 naive, B cells naive, resting mast cells, and M2 macrophage infiltration in the hearts of SCM mice. WGCNA and Limma package analyses identified Clu, Igf1, and Trp53 as hub genes associated with SCM onset. The ROC curves demonstrated a strong correlation and predictive value for Trp53, Igf1, and Clu in the SCM. Moreover, Clu and Igf1 demonstrated predictive values for SCM using Mendelian randomization analysis from the IEU database. Eleven miRNAs formed a ceRNA network with these hub genes.

conclusionIn summary, our results implicated Igf1 and Clu as the potential candidates involved in SCM pathogenesis.

Indexed as

CardiomyopathiesSepsisAnimalsBiomarkersGene Expression ProfilingGene Regulatory NetworksMiceMicroRNAsBiomarkersMicroRNAshub genesimmune infiltrationseptic cardiomyopathyWGCNA

Identifiers

PMID41555186
PMCPMC12815696

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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 Socratic graph.