Evidence map›Paper›PMID 36102304›Full record

ArticleMolecular medicine reports2022

MicroRNAs combined with the TLR4/TDAG8 mRNAs and proinflammatory cytokines are biomarkers for the rapid diagnosis of sepsis.

Xiyuan Xu, Baoying Bu, Hongjun Tian, Rina Wu, Jingping Yang

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 31% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  5. Review
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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 at 2 institutions in 1 country.

Xiyuan Xu *Department of Respiratory and Critical Medicine, Third Affiliated Hospital, Inner Mongolia Medical University, Baotou, Inner Mongolia Autonomous Region 014010, P.R. China.
Baoying Bu *Department of Respiratory and Critical Medicine, Third Affiliated Hospital, Inner Mongolia Medical University, Baotou, Inner Mongolia Autonomous Region 014010, P.R. China.
Hongjun TianDepartment of Respiratory and Critical Medicine, Third Affiliated Hospital, Inner Mongolia Medical University, Baotou, Inner Mongolia Autonomous Region 014010, P.R. China.
Rina WuDepartment of Respiratory and Critical Medicine, Third Affiliated Hospital, Inner Mongolia Medical University, Baotou, Inner Mongolia Autonomous Region 014010, P.R. China.
Jingping YangDepartment of Respiratory and Critical Medicine, Third Affiliated Hospital, Inner Mongolia Medical University, Baotou, Inner Mongolia Autonomous Region 014010, P.R. China.
Inner Mongolia Medical University · CNThird Affiliated Hospital of Inner Mongolia Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The early diagnosis and treatment of sepsis are of particular importance to patient survival. To obtain novel biomarkers that serve as prompt indicators of sepsis, the current study screened the differentially expressed microRNAs (DEMs) that were associated with sepsis susceptibility. The correlation between the elucidated DEMs and the inflammatory response was also examined. The present study included 40 patients with sepsis and 40 healthy controls. RNA‑sequencing technology and bioinformatics analysis were applied to screen the DEMs between the two cohorts. The expression of these DEMs was subsequently verified by performing reverse transcription‑quantitative PCR (RT‑qPCR). In addition, IL‑6, IL‑21, C‑X‑C motif chemokine ligand‑8 (CXCL8) and monocyte chemoattractant protein‑1 (MCP‑1) levels, along with T‑cell death‑associated gene 8 (TDAG8) and toll‑like receptor 4 (TLR4) mRNA expression levels were assessed. The association between microRNA (miRNA/miR)‑3663‑3p and the secretion of various proinflammatory cytokines or TDAG8 and TLR4 mRNA expressions were subsequently evaluated by linear correlation analysis. The results revealed 305 DEMs (P<0.05; fold change >2) between patients with sepsis and healthy controls. Among these, the top 18 up‑ and downregulated miRNAs were selected for RT‑qPCR verification. In addition, the serum content of IL‑6, IL‑21, CXCL8 and MCP‑1, and the expression of TDAG8 and TLR4 mRNAs were significantly increased in patients with sepsis compared with healthy controls. Moreover, in patients with sepsis, a positive correlation was identified between miR‑3663‑3p and the secretion of inflammatory cytokines or TDAG8 and TLR4 mRNA expression. A positive correlation was also elucidated between TDAG8 and TLR4 mRNA expression and proinflammatory cytokine/chemokine secretion. Receiver operating characteristic curve analysis of miR‑3663‑3p expression, IL‑6, IL‑21, CXCL8 and MCP‑1 secretion and TDAG8 and TLR4 mRNA expression demonstrated that miRNA analysis may be invaluable for the diagnosis of sepsis. Collectively, the results determined that miR‑3663‑3p may be a potentially powerful diagnostic and predictive biomarker of sepsis and that the combined and simultaneous detection of several biomarkers, including proteins, miRNAs and mRNA may be a reliable approach for the fast diagnosis and early identification of sepsis.

Indexed as

MicroRNAsSepsisBiomarkersCytokinesHumansInterleukin-6Receptors, G-Protein-CoupledRNA, MessengerToll-Like Receptor 4BiomarkersCytokinesGPR65 protein, humanInterleukin-6MicroRNAsReceptors, G-Protein-CoupledRNA, MessengerTLR4 protein, humanToll-Like Receptor 4chemokinescorrelation analysisdifferentially expressed microRNAsproinflammatory cytokinessepsisT‑cell death‑associated gene 8 mRNAtoll‑like receptor 4 mRNA

Identifiers

PMID36102304
PMCPMC9494599
OpenAlexW4295234267

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.