Evidence map›Paper›PMID 35782387›Full record

ReviewFrontiers in molecular neuroscience2022

Regulation of Oxidative Stress by Long Non-coding RNAs in Central Nervous System Disorders.

Xiaoman Xu, Yi Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in molecular neuroscience, 2022. 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
1.1field-weighted citation impact, top 23% 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, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Non-coding RNA-mediated gene regulation in Alzheimer's disease pathogenesis: molecular insights and emerging innovations.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025
    Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
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

2 authors at 1 institution in 1 country.

Xiaoman XuDepartment of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
Yi ZhangDepartment of Gerontology and Geriatrics, Shengjing Hospital of China Medical University, Shenyang, China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Central nervous system (CNS) disorders, such as ischemic stroke, Alzheimer's disease, Parkinson's disease, spinal cord injury, glioma, and epilepsy, involve oxidative stress and neuronal apoptosis, often leading to long-term disability or death. Emerging studies suggest that oxidative stress may induce epigenetic modifications that contribute to CNS disorders. Non-coding RNAs are epigenetic regulators involved in CNS disorders and have attracted extensive attention. Long non-coding RNAs (lncRNAs) are non-coding RNAs more than 200 nucleotides long and have no protein-coding function. However, these molecules exert regulatory functions at the transcriptional, post-transcriptional, and epigenetic levels. However, the major role of lncRNAs in the pathophysiology of CNS disorders, especially related to oxidative stress, remains unclear. Here, we review the molecular functions of lncRNAs in oxidative stress and highlight lncRNAs that exert positive or negative roles in oxidation/antioxidant systems. This review provides novel insights into the therapeutic potential of lncRNAs that mediate oxidative stress in CNS disorders.

Indexed as

central nervous systemlong non-coding RNAsoxidative stresspathogenesistherapeutic target

Identifiers

PMID35782387
PMCPMC9241987
OpenAlexW4282981932

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.