Evidence map›Paper›PMID 36781867›Full record

ArticleScientific reports2023

Diagnostic, clustering, and immune cell infiltration analysis of m6A regulators in patients with sepsis.

Fenghui Li, Yuan Zhang, Zhiyun Peng, Yingjing Wang, Zhaoshang Zeng, Zhongxiang Tang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

11 citing papers in PubMed, 11 citations in OpenAlex.

  1. mRedox biology · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Identification and validation of mFrontiers in immunology · 2025
    Article
  7. Article
  8. Article
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  10. Article
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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

6 authors at 1 institution in 1 country.

Fenghui Li *Intensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China.
Yuan Zhang *Intensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China.
Zhiyun PengIntensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China.
Yingjing WangIntensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China.
Zhaoshang ZengIntensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China.
Zhongxiang TangIntensive Care Unit, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong Province, China. icudrtang@163.com.
Guangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA N6-methladenosine (m6A) regulators are required for a variety of biological processes, including immune responses, and increasing evidence indicates that their dysregulation is closely associated with many diseases. However, the potential roles of m6A regulators in sepsis remain unknown. We comprehensively analyzed the transcriptional variations in and interactions of 26 m6A regulators in sepsis based on the Gene Expression Omnibus (GEO) database. A random forest (RF) model and nomogram were established to predict the occurrence and risk of sepsis in patients. Then, two different m6A subtypes were defined by consensus clustering analysis, and we explored the correlation between the subtypes and immune cells. We found that 17 of the 26 m6A regulators were significantly differentially expressed between patients with and without sepsis, and strong correlations among these 17 m6A regulators were revealed. Compared with the support vector machine (SVM) model, the RF model had better predictive ability, and therefore was used to construct a reliable nomogram containing 10 candidate m6A regulators to predict the risk of sepsis in patients. In addition, a consensus clustering algorithm was used to identify two different subtypes of m6A, which helped us distinguish different levels of immune cell infiltration and inflammation in patients with sepsis. Comprehensive analysis of m6A regulators in sepsis revealed their potential roles in sepsis occurrence, immune cell infiltration and inflammation in patients with sepsis. This study may contribute to the development of follow-up treatment strategies for sepsis.

Indexed as

PatientsSepsisAlgorithmsCluster AnalysisHumansInflammation

Identifiers

PMID36781867
PMCPMC9925440
OpenAlexW4320498237

What OpenQuestion 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 OpenQuestion graph.