Evidence map›Paper›PMID 31496670›Full record

ArticleClinical interventions in aging2019

Epigenetic mechanism controls

Tomohiro Kamo, Satoshi Kurose, Hiroshi Ohno, Minoru Murata, Masaki Hashiyada, Takanori Saito, Yutaka Kimura

Open access · goldAbstract read
In one paragraph

Article in Clinical interventions in aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 53% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

7 authors at 1 institution in 1 country.

Tomohiro KamoDepartment of Health Science, Kansai Medical University, Osaka, Japan.
Satoshi KuroseDepartment of Health Science, Kansai Medical University, Osaka, Japan.
Hiroshi OhnoDepartment of Orthopaedic Surgery, Kansai Medical University Hospital, Osaka, Japan.
Minoru MurataDepartment of Orthopaedic Surgery, Kansai Medical University Hospital, Osaka, Japan.
Masaki HashiyadaDepartment of Forensic Medicine, Kansai Medical University, Osaka, Japan.
Takanori SaitoDepartment of Orthopaedic Surgery, Kansai Medical University Hospital, Osaka, Japan.
Yutaka KimuraDepartment of Health Science, Kansai Medical University, Osaka, Japan.
Kansai Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDNA methylation is thought to play a role in exercise-induced gene expression. We aimed to examine changes in muscular strength and body composition in elderly patients with end-stage knee osteoarthritis before and after artificial knee arthroplasty and exercise therapy. We aimed to confirm the relationship between DNA methylation and body composition, using the methylation rate of the pyruvate dehydrogenase kinase 4 ( PATIENTS AND

methodsPatients underwent artificial knee arthroplasty between April 2017 and June 2017 at Kansai Medical University Hospital. Six patients (seven knees) were included in the analysis (four males/two females; average age, 75.7 years; body mass index, 25.1 kg/m

resultsBody weight (

conclusionRehabilitative exercise resulted in significant decreases in weight and body fat. Hypomethylation of the

Indexed as

Arthroplasty, Replacement, KneeAdipose TissueAgedBody Mass IndexDNA MethylationEpigenesis, GeneticExercise TherapyFemaleHumansMaleMiddle AgedMuscle StrengthProtein KinasesTranscriptional ActivationWeight LossProtein Kinasespyruvate dehydrogenase kinase 4elderly personmethylationmuscle biopsyrehabilitation

Identifiers

PMID31496670
PMCPMC6689537
OpenAlexW2964939850

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.