Evidence map›Paper›PMID 31137597›Full record

ArticleGenes2019

Advances in Genetics of Regeneration in Metabesity.

Benoit R Gauthier, Francisco J Bermúdez-Silva

Open access · goldAbstract readEditorial
In one paragraph

Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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.

Benoit R GauthierAndalusian Center of Molecular Biology and Regenerative Medicine-CABIMER, Junta de Andalucia-University of Pablo de Olavide-University of Seville-CSIC, 41092 Seville, Spain. benoit.gauthier@cabimer.es.ORCID 0000-0001-8146-7486
Francisco J Bermúdez-SilvaCentro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain. javier.bermudez@ibima.eu.ORCID 0000-0003-3133-9691
Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

'Metabesity' is a recent term comprising a wide range of diseases with underlying metabolic disarrangements at its root, and whose aetiology lies in complex relationships among genes and the obesogenic environment to which individuals are currently exposed in most countries. Of note, epigenetic changes are increasingly being reported to play an outstanding role in carrying deleterious information that, together with susceptibility genes, boost the development of metabesity in subsequent generations. In this context, it is noteworthy to mention that the transition from the pre-industrial era to the current high-technology society and global economy, even after suffering two world wars, has been very fast. By contrast, evolution-driven processes, such as biological ones, are slow. In fact, there is a general consensus that at the metabolic level, adipogenic processes and thrifty pathways prevail over those promoting energy expenditure in a way that currently leads to metabolic diseases by excessive energy storage. In such an imbalanced social-biological scenario, genes that were beneficial in the past have shifted to becoming detrimental, i.e., favouring metabesity, which is quickly growing to reach pandemic proportions.

Indexed as

Energy MetabolismHumansMetabolic DiseasesObesityRegenerationanimal modelcell therapygenesgenetic networksinflammationmetabolic diseasesregenerationregenerative medicinetransgenic

Identifiers

PMID31137597
PMCPMC6563018
OpenAlexW2945638392

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.