Evidence map›Paper›PMID 25539834›Full record

ArticlePhysiological reports2014

Bioinformatic identification of connective tissue growth factor as an osteogenic protein within skeletal muscle.

Steven J Forrester, Keisuke Kawata, Hojun Lee, Ji-Seok Kim, Kelly Sebzda, Tiffiny Butler, Vanessa R Yingling, Joon-Young Park

Open access · goldAbstract read
In one paragraph

Article in Physiological reports, 2014. 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
0.4field-weighted citation impact, top 35% 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, 6 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

8 authors at 2 institutions in 1 country.

Steven J ForresterCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Keisuke KawataCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Hojun LeeCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Ji-Seok KimCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Kelly SebzdaCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Tiffiny ButlerCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania.
Vanessa R YinglingDepartment of Kinesiology, California State University, East BayHayward, California.
Joon-Young ParkCardiovascular Genomics Laboratory, Department of Kinesiology, College of Public Health, Temple University, Philadelphia, Pennsylvania Cardiovascular Research Center, School of Medicine, Temple UniversityPhiladelphia, Pennsylvania.
Temple University · USCalifornia State University, East Bay · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is associated with increasing incidence of osteoporosis; a skeletal disorder characterized by compromised bone strength that may predispose patients to an increased risk of fracture. It is imperative to identify novel ways in which to attenuate such declines in the functional properties of bone. The purpose of this study was to identify, through in silico, in vitro, and in vivo approaches, a protein secreted from skeletal muscle that is putatively involved in bone formation. We performed a functional annotation bioinformatic analysis of human skeletal muscle-derived secretomes (n = 319) using DAVID software. Cross-referencing was conducted using OMIM, Unigene, UniProt, GEO, and CGAP databases. Signal peptides and transmembrane residues were analyzed using SignalP and TMHMM software. To further investigate functionality of the identified protein, L6 and C2C12 myotubes were grown for in vitro analysis. C2C12 myotubes were subjected to 16 h of glucose deprivation (GD) prior to analysis. In vivo experiments included analysis of 6-week calorie restricted (CR) rat muscle samples. Bioinformatic analysis yielded 15 genes of interest. GEO dataset analysis identified BMP5, COL1A2, CTGF, MGP, MMP2, and SPARC as potential targets for further processing. Following TMHMM and SignalP processing, CTGF was chosen as a candidate gene. CTGF expression level was increased during L6 myoblast differentiation (P < 0.01). C2C12 myotubes showed no change in response to GD. Rat soleus muscle samples exhibited an increase in CTGF expression (n = 16) in response to CR (35%) (P < 0.05). CTGF was identified as a skeletal muscle expressed protein through bioinformatic analysis of skeletal muscle-derived secretomes and in vitro/in vivo analysis. Future study is needed to determine the role of muscle-derived CTGF in bone formation and remodeling processes.

Indexed as

Calorie RestrictionCTGFexercisemyokine

Identifiers

PMID25539834
PMCPMC4332228
OpenAlexW2121342973

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.