Evidence map›Paper›PMID 38887322›Full record

ArticleCureus2024

Exploring Ferroptosis-Associated Gene Signatures as Diagnostic and Therapeutic Targets for Sepsis-Induced Cardiomyopathy.

Haobin Huang, Chenbo Ge, Yawei Dai, Yanhu Wu, Jinfu Zhu

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

5 authors.

Haobin HuangCardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, CHN.
Chenbo GeCardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, CHN.
Yawei DaiCardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, CHN.
Yanhu WuCardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, CHN.
Jinfu ZhuCardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, CHN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis-induced cardiomyopathy (SICM) is a severe complication of sepsis associated with high mortality rates. Despite its significance, the molecular mechanisms underlying SICM remain poorly understood, particularly the role of ferroptosis - a form of iron-dependent programmed cell death. METHODOLOGY: This study analyzed the GSE79962 dataset from the Gene Expression Omnibus, containing cardiac gene expression profiles from SICM patients and controls. A list of ferroptosis-related genes (FRGs) was retrieved from the FerrDb. We used the

resultsAfter differential expression analysis, we identified 145 DE-FRGs. Functional enrichment analyses underscored the involvement of these genes in critical biological processes and pathways, such as lipid metabolism and insulin resistance. Machine learning approaches pinpointed five key DE-FRGs (NCOA4, GABARAPL1, GJA1, CISD1, CP), with strong predictive potential for SICM. Further analyses, including the construction of a ceRNA network, revealed intricate post-transcriptional regulatory mechanisms that may influence the expression of these key genes.

conclusionsOur findings highlight the central role of ferroptosis in SICM and identify potential biomarkers and therapeutic targets that could help refine diagnostic and treatment strategies. This study advances our understanding of the molecular underpinnings of SICM and sets the stage for future research aimed at mitigating this severe sepsis complication.

Indexed as

bioinformaticscerna networkferroptosissepsis-induced cardiomyopathytherapeutic targets

Identifiers

PMID38887322
PMCPMC11182375

What Socratic holds

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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 Socratic graph.