Evidence map›Paper›PMID 27378453›Full record

ArticleRejuvenation research2017

Enhancement of Skeletal Muscle in Aged Rats Following High-Intensity Stretch-Shortening Contraction Training.

Erik P Rader, Marshall A Naimo, Kayla N Layner, Alyssa M Triscuit, Robert D Chetlin, James Ensey, Brent A Baker

Open access · greenAbstract read
In one paragraph

Article in Rejuvenation research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. The Relationship between Resistance Training Frequency and Muscle Quality in Adolescents.International journal of environmental research and public health · 2022
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Role of exercise in age-related sarcopenia.Journal of exercise rehabilitation · 2018
    Review
  9. Article
  10. 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 2 institutions in 1 country.

Erik P Rader1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Marshall A Naimo1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Kayla N Layner1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Alyssa M Triscuit1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Robert D Chetlin1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
James Ensey1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Brent A Baker1 Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health , Morgantown, West Virginia.
Centers for Disease Control and Prevention · USNational Institute for Occupational Safety and Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exercise is the most accessible, efficacious, and multifactorial intervention to improve health and treat chronic disease. High-intensity resistance exercise, in particular, also maximizes skeletal muscle size and strength-outcomes crucial at advanced age. However, such training is capable of inducing muscle maladaptation when misapplied at old age. Therefore, characterization of parameters (e.g., mode and frequency) that foster adaptation is an active research area. To address this issue, we utilized a rodent model that allowed training at maximal intensity in terms of muscle activation and tested the hypothesis that muscles of old rats adapt to stretch-shortening contraction (SSC) training, provided the training frequency is sufficiently low. At termination of training, normalized muscle mass (i.e., muscle mass divided by tibia length) and muscle quality (isometric force divided by normalized muscle mass) were determined. For young rats, normalized muscle mass increased by ∼20% regardless of training frequency. No difference was observed for muscle quality values after 2 days versus 3 days per week training (0.65 ± 0.09 N/mg/mm vs. 0.59 ± 0.05 N/mg/mm, respectively). For old rats following 3 days per week training, normalized muscle mass was unaltered and muscle quality was 30% lower than young levels. Following 2 days per week training at old age, normalized muscle mass increased by 17% and muscle quality was restored to young levels. To investigate this enhanced response, oxidative stress was assessed by lipid peroxidation quantification. For young rats, lipid peroxidation levels were unaltered by training. With aging, baseline levels of lipid peroxidation increased by 1.5-fold. For old rats, only 2 days per week training decreased lipid peroxidation to levels indistinguishable from young values. These results imply that, appropriately scheduled high-intensity SSC training at old age is capable of restoring muscle to a younger phenotype in terms of lipid peroxidation levels and muscle quality.

Indexed as

Physical Conditioning, AnimalAgingAnimalsBiomarkersFluorescent Antibody TechniqueLipid PeroxidationMaleMalondialdehydeMuscle ContractionMuscle Fibers, SkeletalMuscle, SkeletalOrgan SizeOxidative StressRats, Inbred BNBiomarkersMalondialdehydedorsiflexor musclesdynamometerFisher 344XBrown Norway ratsoxidative stressrepetitive exposure

Identifiers

PMID27378453
PMCPMC9206483
OpenAlexW2490918295

What OpenQuestion holds

Textmetadata
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.