Evidence map›Paper›PMID 27306370›Full record

ReviewHeart failure reviews2016

Myocardial transcription factors in diastolic dysfunction: clues for model systems and disease.

Alexander T Mikhailov, Mario Torrado

Abstract readReview
PubMed Publisher
In one paragraph

Review in Heart failure reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Understanding the molecular basis of cardiomyopathy.American journal of physiology. Heart and circulatory physiology · 2022
    Review
  6. Review
  7. Article
  8. 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

2 authors at 1 institution in 1 country.

Alexander T MikhailovInstitute of Health Sciences, University of La Coruña, 15006, La Coruña, Spain. a.mikhailov@udc.es.ORCID 0000-0002-1146-4113
Mario TorradoInstitute of Health Sciences, University of La Coruña, 15006, La Coruña, Spain.
Universidade da Coruña · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are multiple intrinsic mechanisms for diastolic dysfunction ranging from molecular to structural derangements in ventricular myocardium. The molecular mechanisms regulating the progression from normal diastolic function to severe dysfunction still remain poorly understood. Recent studies suggest a potentially important role of core cardio-enriched transcription factors (TFs) in the control of cardiac diastolic function in health and disease through their ability to regulate the expression of target genes involved in the process of adaptive and maladaptive cardiac remodeling. The current relevant findings on the role of a variety of such TFs (TBX5, GATA-4/6, SRF, MYOCD, NRF2, and PITX2) in cardiac diastolic dysfunction and failure are updated, emphasizing their potential as promising targets for novel treatment strategies. In turn, the new animal models described here will be key tools in determining the underlying molecular mechanisms of disease. Since diastolic dysfunction is regulated by various TFs, which are also involved in cross talk with each other, there is a need for more in-depth research from a biomedical perspective in order to establish efficient therapeutic strategies.

Indexed as

Stroke VolumeAnimalsHeartHeart Failure, DiastolicHumansMiceMicroRNAsMyocardiumRatsSignal TransductionTranscription FactorsVentricular RemodelingMicroRNAsTranscription FactorsDiastolic dysfunctionMicroRNAsTranscription factors

Identifiers

PMID27306370
OpenAlexW2429564612

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.