Evidence map›Paper›PMID 33816776›Full record

ArticleRegenerative engineering and translational medicine2021

The Treatment of Muscle Atrophy after Rotator Cuff Tears Using Electroconductive Nanofibrous Matrices.

Xiaoyan Tang, Nikoo Saveh Shemshaki, Varadraj N Vernekar, Anupama Prabhath, Emmanuel Kuyinu, Ho-Man Kan, Mohammed Barajaa, Yusuf Khan, Cato T Laurencin

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Regenerative engineering and translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. [Key role of biomechanical properties and material selection in rotator cuff repair].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025
    Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Muscle degeneration in chronic massive rotator cuff tears of the shoulder: Addressing the real problem using a graphene matrix.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  11. Article
  12. 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

9 authors at 2 institutions in 1 country.

Xiaoyan TangConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Nikoo Saveh ShemshakiConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Varadraj N VernekarConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Anupama PrabhathConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Emmanuel KuyinuConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Ho-Man KanConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Mohammed BarajaaConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Yusuf KhanConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
Cato T LaurencinConnecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health Center, Farmington, CT 06030, USA.
University of Connecticut · USUConn Health · US

Funding

Regenerative Engineering of Complex Musculoskeletal Tissues and JointsDP1AR068147 · NIAMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI LAURENCIN, CATO T. · 2014 to 2018
$4.1M
A Translational Approach Towards Ligament RegenerationR01AR063698 · NIAMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI LAURENCIN, CATO T. · 2013 to 2018
$1.9M
NIAMS NIH HHS DP1 AR068147NIAMS NIH HHS R01 AR063698
6 · The paper itself

Abstract

Rotator cuff tears (RCTs) are a common cause of disability and pain in the adult population. Despite the successful repair of the torn tendon, the delay between the time of injury and time of repair can cause muscle atrophy. The goal of the study was to engineer an electroconductive nanofibrous matrix with an aligned orientation to enhance muscle regeneration after rotator cuff (RC) repair. The electroconductive nanofibrous matrix was fabricated by coating Poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) nanoparticles onto the aligned poly(ε-caprolactone) (PCL) electrospun nanofibers. The regenerative potential of the matrix was evaluated using two repair models of RCTs include acute and sub-acute. Sprague-Dawley rats (n=39) were randomly assigned to 1 of 8 groups. For the acute model, the matrix was implanted on supraspinatus muscle immediately after the injury. The repair surgery for the sub-acute model was conducted 6 weeks after injury. The supraspinatus muscle was harvested for histological analysis two and six weeks after repair. The results demonstrated the efficacy of electrical and topographical cues on the treatment of muscle atrophy

Indexed as

electroconductive matrixmuscle atrophynanofibersRotator cuff

Identifiers

PMID33816776
PMCPMC8011566
OpenAlexW3101119058

What OpenQuestion holds

Textmetadata
LicenceTDM
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.