Evidence map›Paper›PMID 39964243›Full record

ArticleFASEB journal : official publication of the Federation of American Societies for Experimental Biology2025

Muscle-specific ERRγ activation mitigates muscle atrophy after ACL injury.

Aiping Lu, Katie J Sikes, Ping Guo, Matthieu Huard, Shelbi Green, Kelly Santangelo, Jacob Singer, Ashley Groesbeck, Scott Tashman, Vihang A Narkar and 1 more

Abstract read
In one paragraph

Article in FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 2025. 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
–field-weighted citation impact
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.

  1. Review
  2. Review
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

11 authors.

Aiping LuCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.ORCID https://orcid.org/0000-0001-5529-6599
Katie J SikesDepartment of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.ORCID https://orcid.org/0000-0002-3750-4777
Ping GuoCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.ORCID https://orcid.org/0000-0003-0096-4814
Matthieu HuardCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.
Shelbi GreenCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.
Kelly SantangeloDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, Colorado, USA.ORCID https://orcid.org/0000-0002-2348-594X
Jacob SingerCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.
Ashley GroesbeckCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.
Scott TashmanCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.ORCID https://orcid.org/0000-0003-0534-3785
Vihang A NarkarInstitute of Molecular Medicine, McGovern Medical School at the University of Texas Health Science Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-5574-083X
Johnny HuardCenter for Regenerative & Personalized Medicine, Steadman Philippon Research Institute, Vail, Colorado, USA.ORCID https://orcid.org/0000-0002-2926-569X

Funding

Development of biological approaches to enhance skeletal muscle rehabilitation after anterior cruciate ligament injuryR21AR075997 · NIAMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HUARD, JOHNNY, NARKAR, VIHANG A · 2019 to 2020
$332k
Foundation for the National Institutes of Health (FNIH) R21AR075997-01NIAMS NIH HHS R21 AR075997
6 · The paper itself

Abstract

Anterior cruciate ligament (ACL) injury adversely affects skeletal muscle, leading to muscle atrophy and weakness, significantly impacting clinical outcomes. This study aimed to determine if estrogen-related receptor gamma (ERRγ) overexpression in skeletal muscle could mitigate muscle atrophy after ACL injury. An animal model with selective overexpression of ERRγ in skeletal muscle (ERR-gamma transgenic mice, TG) and WT control mice were used for this study. All the mice received a mechanical ACL rupture and were euthanized at 4- and 8-week post-injury. Muscle histology, atrophy, and function were evaluated and compared between the TG and WT mice. Muscle-specific ERRγ activation in TG mice demonstrated a reduction in muscle fiber atrophy, which consequently ameliorated muscle function loss post-ACL rupture. Less fibrogenic cellular expansion and muscle fibrosis were observed after ACL injury in TG mice compared to WT mice. Both male and female TG mice can maintain their muscle function 4 weeks after ACL rupture with the muscle function of female TG mice declining 8 weeks post-injury. In vivo results revealed that ERRγ activation decreased fibrogenic factors, P65, and myostatin expression, prevented the functional loss of muscle progenitor cells (MPCs), and increased CD31 and VEGF expression. These results suggest that overexpression ERRγ in skeletal muscle has a beneficial effect in preventing muscle atrophy and fibrosis after ACL rupture. This study's results will help to develop a novel rehabilitation approach that can significantly improve outcomes after ACL injury.

Indexed as

Anterior Cruciate Ligament InjuriesMuscle, SkeletalMuscular AtrophyReceptors, EstrogenAnimalsDisease Models, AnimalFemaleFibrosisMaleMiceMice, Inbred C57BLMice, TransgenicEsrrg protein, mouseReceptors, EstrogenACL injuryERRγ overexpressionmuscle atrophyvascularization

Identifiers

PMID39964243
PMCPMC12335894

What OpenQuestion holds

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Registered trials

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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.