Evidence map›Paper›PMID 38155319›Full record

ReviewMolecular biology reports2023

ANRIL, H19 and TUG1: a review about critical long non-coding RNAs in cardiovascular diseases.

Lívia da Cunha Agostini, Tamires Cunha Almeida, Glenda Nicioli da Silva

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biology reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 1 country.

Lívia da Cunha AgostiniPrograma de Pós-Graduação em Ciências Farmacêuticas (CiPharma), Escola de Farmácia, Universidade Federal de Ouro Preto, Morro do Cruzeiro, s/nº, Ouro Prêto, Minas Gerais, CEP 35402-163, Brazil.
Tamires Cunha AlmeidaEscola Superior Instituto Butantan (ESIB), Laboratório de Dor e Sinalização, Instituto Butantan, São Paulo, São Paulo, Brazil.
Glenda Nicioli da SilvaPrograma de Pós-Graduação em Ciências Farmacêuticas (CiPharma), Escola de Farmácia, Universidade Federal de Ouro Preto, Morro do Cruzeiro, s/nº, Ouro Prêto, Minas Gerais, CEP 35402-163, Brazil. nicioli@ufop.edu.br.
Universidade Federal de Ouro Preto · BRInstituto Butantan · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular diseases are the leading cause of death worldwide. They are non-transmissible diseases that affect the cardiovascular system and have different etiologies such as smoking, lipid disorders, diabetes, stress, sedentary lifestyle and genetic factors. To date, lncRNAs have been associated with increased susceptibility to the development of cardiovascular diseases such as hypertension, acute myocardial infarction, stroke, angina and heart failure. In this way, lncRNAs are becoming a very promising point for the prevention and diagnosis of cardiovascular diseases. Therefore, this review highlights the most important and recent discoveries about the mechanisms of action of the lncRNAs ANRIL, H19 and TUG1 and their clinical relevance in these pathologies. This may contribute to early detection of cardiovascular diseases in order to prevent the pathological phenotype from becoming established.

Indexed as

Cardiovascular DiseasesRNA, Long NoncodingGenetic Predisposition to DiseaseHumansCDKN2B antisense RNA, humanH19 long non-coding RNARNA, Long NoncodingTUG1 long noncoding RNA, humanCardiovascular diseasesGenetic factorslncRNA ANRILlncRNA H19lncRNA TUG1Non-coding RNA

Identifiers

PMID38155319
OpenAlexW4390335685

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.