Evidence map›Paper›PMID 32973530›Full record

ReviewFrontiers in pharmacology2020

New Insights and Current Approaches in Cardiac Hypertrophy Cell Culture, Tissue Engineering Models, and Novel Pathways Involving Non-Coding RNA.

Nina Kastner, Katrin Zlabinger, Andreas Spannbauer, Denise Traxler, Julia Mester-Tonczar, Ena Hašimbegović, Mariann Gyöngyösi

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

7 authors at 1 institution in 1 country.

Nina KastnerDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Katrin ZlabingerDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Andreas SpannbauerDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Denise TraxlerDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Julia Mester-TonczarDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Ena HašimbegovićDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Mariann GyöngyösiDepartment of Cardiology, Medical University of Vienna, Vienna, Austria.
Medical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac hypertrophy is an ongoing clinical challenge, as risk factors such as obesity, smoking and increasing age become more widespread, which lead to an increasing prevalence of developing hypertrophy. Pathological hypertrophy is a maladaptive response to stress conditions, such as pressure overload, and involve a number of changes in cellular mechanisms, gene expression and pathway regulations. Although several important pathways involved in the remodeling and hypertrophy process have been identified, further research is needed to achieve a better understanding and explore new and better treatment options. More recently discovered pathways showed the involvement of several non-coding RNAs, including micro RNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which either promote or inhibit the remodeling process and pose a possible target for novel therapy approaches.

Indexed as

cardiac hypertrophydisease modelinghypertrophy inductionnon-coding RNAtissue engineering

Identifiers

PMID32973530
PMCPMC7472597
OpenAlexW3081005989

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.