Evidence map›Paper›PMID 25231644›Full record

ReviewNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2014

Identifying the role of microRNAs in spinal cord injury.

Jun Dong, Meng Lu, Xijing He, Junkui Xu, Jie Qin, Zhijian Cheng, Baobao Liang, Dong Wang, Haopeng Li

Abstract readReview
PubMed Publisher
In one paragraph

Review in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2014. 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
–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

11 citing papers in PubMed.

  1. Long non-coding RNA DANCR increases spinal cord neuron apoptosis and inflammation of spinal cord injury by mediating the microRNA-146a-5p/MAPK6 axis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024
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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

9 authors.

Jun DongThe Orthopedics Department, The Second Affiliated Hospital of Xi'an Jiaotong University, no. 157, West Five Road, Xi'an, 710004, China.
Meng Lu
Xijing He
Junkui Xu
Jie Qin
Zhijian Cheng
Baobao Liang
Dong Wang
Haopeng Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spinal cord injury (SCI) is medically and socioeconomically debilitating, and effective treatments are lacking. The elucidation of the pathophysiological mechanisms underlying SCI is essential for developing effective treatments for SCI. MicroRNAs (miRNAs) are small non-coding RNA molecules (18-24 nucleotides long) that regulate gene expression by interacting with specific target sequences. Recent studies suggest that miRNAs can act as post-transcriptional regulators to inhibit mRNA translation. Bioinformatic analyses indicate that the altered expression of miRNAs has an effect on critical processes of SCI physiopathology, including astrogliosis, oxidative stress, inflammation, apoptosis, and neuroplasticity. Therefore, the study of miRNAs may provide new insights into the molecular mechanisms of SCI. Current studies have also provided potential therapeutic clinical applications that involve targeting mRNAs to treat SCI. This review summarizes the biogenesis and function of miRNAs and the roles of miRNAs in SCI. We also discuss the potential therapeutic applications of miRNA-based interventions for SCI.

Indexed as

AnimalsHumansMicroRNAsSpinal Cord InjuriesMicroRNAs

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.