Evidence map›Paper›PMID 33321920›Full record

ReviewBiology2020

Discoveries for Long Non-Coding RNA Dynamics in Traumatic Brain Injury.

Key-Hwan Lim, Sumin Yang, Sung-Hyun Kim, Sungkun Chun, Jae-Yeol Joo

Abstract readReview
In one paragraph

Review in Biology, 2020. 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. Article
  2. Review
  3. LncRNAs Orchestrating Neuroinflammation: A Comprehensive Review.Cellular and molecular neurobiology · 2025
    Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  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

5 authors.

Key-Hwan LimNeurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Korea.
Sumin YangNeurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Korea.
Sung-Hyun KimNeurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Korea.
Sungkun ChunDepartment of Physiology, Jeonbuk National University Medicine School, Jeonju 54907, Korea.ORCID 0000-0001-9837-2299
Jae-Yeol JooNeurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Korea.

Funding

Medical Research Center Program NRF-2017R1A5A2015061Ministry of Science and ICT, South Korea 2019M3C7A1032551Ministry of Science and ICT, South Korea 20-BR-02-13National Research Foundation of Korea 2019R1F1A1059595
6 · The paper itself

Abstract

In recent years, our understanding of long non-coding RNAs (lncRNAs) has been challenged with advances in genome sequencing and the widespread use of high-throughput analysis for identifying novel lncRNAs. Since then, the characterization of lncRNAs has contributed to the establishment of their molecular roles and functions in transcriptional regulation. Although genetic studies have so far explored the sequence-based primary function of lncRNAs that guides the expression of target genes, recent insights have shed light on the potential of lncRNAs for widening the identification of biomarkers from non-degenerative to neurodegenerative diseases. Therefore, further advances in the genetic characteristics of lncRNAs are expected to lead to diagnostic accuracy during disease progression. In this review, we summarized the latest studies of lncRNAs in TBI as a non-degenerative disease and discussed their potential limitations for clinical treatment.

Indexed as

biomarkerlong non-coding RNAnon-degenerative diseasetraumatic brain injury

Identifiers

PMID33321920
PMCPMC7763048

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.