Evidence map›Paper›PMID 32455124›Full record

ArticleInternational journal of genomics2020

Diagnostic Value of miR-103 in Patients with Sepsis and Noninfectious SIRS and Its Regulatory Role in LPS-Induced Inflammatory Response by Targeting TLR4.

Min Yang, Li Zhao, Mingyan Sun

Abstract read
In one paragraph

Article in International journal of genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. MicroRNA as Sepsis Biomarkers: A Comprehensive Review.International journal of molecular sciences · 2024
    Review
  2. MicroRNA Profiles in Critically Ill Patients.Current medicinal chemistry · 2024
    Review
  3. Article
  4. Role of miRNA dysregulation in sepsis.Molecular medicine (Cambridge, Mass.) · 2022
    Review
  5. Review
  6. 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

3 authors.

Min YangDepartment of Infectious Diseases, Affiliated Hospital of Weifang Medical University, Weifang, Shandong 261031, China.ORCID https://orcid.org/0000-0003-4015-7427
Li ZhaoDepartment of Infectious Diseases, Yidu Central Hospital of Weifang, Weifang, Shandong 262500, China.ORCID https://orcid.org/0000-0002-8808-2981
Mingyan SunClinical Laboratory, Affiliated Hospital of Weifang Medical University, Weifang, Shandong 261031, China.ORCID https://orcid.org/0000-0003-3562-2769

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis is a life-threatening condition and a systemic inflammatory response syndrome (SIRS) driven by infection. This study aimed at investigating the expression of microRNA-103 (miR-103) in sepsis patients, evaluating its diagnostic value, and exploring the regulatory effect of miR-103 on LPS-induced inflammation in monocytes.

methodsExpression of miR-103 was measured using quantitative real-time PCR. A receiver operating characteristics curve was plotted to evaluate the diagnostic vale of miR-103. Serum and cell supernatant levels of proinflammatory cytokines were analyzed using ELISA. The interaction between miR-103 and Toll-like receptors 4 (TLR4) was analyzed using luciferase reporter assay. The effect of miR-103 on inflammation was examined in LPS-treated monocytes.

resultsSerum expression of miR-103 was decreased in noninfectious SIRS and sepsis patients compared with healthy controls, and the lowest expression value was observed in sepsis patients (all

conclusionAll the data revealed that serum decreased miR-103 in sepsis patients serves as a promising noninvasive diagnostic biomarker and may be involved in the pathogenesis of sepsis by regulating inflammatory responses via targeting TLR4.

Identifiers

PMID32455124
PMCPMC7243004

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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.