Evidence map›Paper›PMID 36186445›Full record

ReviewFrontiers in genetics2022

Focus on long non-coding RNA MALAT1: Insights into acute and chronic lung diseases.

Xingning Lai, Jie Zhong, Aihua Zhang, Boyi Zhang, Tao Zhu, Ren Liao

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
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  8. Epigenetic regulation of pulmonary inflammation.Seminars in cell & developmental biology · 2024
    Review
  9. Review
  10. Mechanisms Contributing to the Comorbidity of COPD and Lung Cancer.International journal of molecular sciences · 2023
    Review
  11. 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

6 authors.

Xingning LaiDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.
Jie ZhongDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.
Aihua ZhangDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.
Boyi ZhangDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.
Tao ZhuDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.
Ren LiaoDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdou, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute lung injury (ALI) is a pulmonary illness with a high burden of morbidity and mortality around the world. Chronic lung diseases also represent life-threatening situations. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a type of long non-coding RNA (lncRNA) and is highly abundant in lung tissues. MALAT1 can function as a competitive endogenous RNA (ceRNA) to impair the microRNA (miRNA) inhibition on targeted messenger RNAs (mRNAs). In this review, we summarized that MALAT1 mainly participates in pulmonary cell biology and lung inflammation. Therefore, MALAT1 can positively or negatively regulate ALI and chronic lung diseases (e.g., chronic obstructive pulmonary disease (COPD), bronchopulmonary dysplasia (BPD), pulmonary fibrosis, asthma, and pulmonary hypertension (PH)). Besides, we also found a MALAT1-miRNA-mRNA ceRNA regulatory network in acute and chronic lung diseases. Through this review, we hope to cast light on the regulatory mechanisms of MALAT1 in ALI and chronic lung disease and provide a promising approach for lung disease treatment.

Indexed as

acute lung injurychronic lung diseaseinflammationMALAT1miRNA

Identifiers

PMID36186445
PMCPMC9523402

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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.