Evidence map›Paper›PMID 36980239›Full record

ArticleCells2023

Different Resistance Exercise Loading Paradigms Similarly Affect Skeletal Muscle Gene Expression Patterns of Myostatin-Related Targets and mTORC1 Signaling Markers.

Mason C McIntosh, Casey L Sexton, Joshua S Godwin, Bradley A Ruple, J Max Michel, Daniel L Plotkin, Tim N Ziegenfuss, Hector L Lopez, Ryan Smith, Varun B Dwaraka and 5 more

Open access · goldFull text read
In one paragraph

Article in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 24 citations in OpenAlex.

  1. Trial
  2. Review
  3. Blood Flow Restriction Training in Hemodialysis Patients: Clinical Benefits, Challenges, and Future Perspectives.Hemodialysis international. International Symposium on Home Hemodialysis · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. βFrontiers in physiology · 2024
    Article
  16. Article
  17. 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

15 authors at 4 institutions in 3 countries.

Mason C McIntoshSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0002-8760-8494
Casey L SextonSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Joshua S GodwinSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Bradley A RupleSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
J Max MichelSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0001-9894-3856
Daniel L PlotkinSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Tim N ZiegenfussCenter for Applied Health Sciences, Canfield, OH 44406, USA.
Hector L LopezCenter for Applied Health Sciences, Canfield, OH 44406, USA.
Ryan SmithTruDiagnotic, Lexington, KY 40511, USA.ORCID 0000-0001-7362-8753
Varun B DwarakaTruDiagnotic, Lexington, KY 40511, USA.
Adam P SharplesInstitute for Physical Performance, Norwegian School of Sport Sciences, 0164 Oslo, Norway.ORCID 0000-0003-1526-9400
Vincent J DalboSchool of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton 4700, Australia.ORCID 0000-0002-5944-7558
C Brooks MobleySchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.
Christopher G VannDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 03824, USA.ORCID 0000-0002-9072-4488
Michael D RobertsSchool of Kinesiology, Auburn University, Auburn, AL 36849, USA.ORCID 0000-0002-7359-5362
Auburn University · USCentral Queensland University · AUDuke University · USNorwegian School of Sport Sciences · NO

Funding

Epigenetic Mechanisms Promoting LongevityR01AG054840 · NIA · DUKE UNIVERSITY · PI KRAUS, VIRGINIA · 2018 to 2022
$3.4M
G-RISE at Auburn UniversityT32GM141739 · NIGMS · AUBURN UNIVERSITY AT AUBURN · PI CLAYTON, TAFFYE BENSON, RUSSELL, MELODY L · 2021 to 2024
$1.2M
NIA NIH HHS R01 AG054840NIGMS NIH HHS T32 GM141739
6 · The paper itself

Abstract

Although transcriptome profiling has been used in several resistance training studies, the associated analytical approaches seldom provide in-depth information on individual genes linked to skeletal muscle hypertrophy. Therefore, a secondary analysis was performed herein on a muscle transcriptomic dataset we previously published involving trained college-aged men (n = 11) performing two resistance exercise bouts in a randomized and crossover fashion. The lower-load bout (30 Fail) consisted of 8 sets of lower body exercises to volitional fatigue using 30% one-repetition maximum (1 RM) loads, whereas the higher-load bout (80 Fail) consisted of the same exercises using 80% 1 RM loads. Vastus lateralis muscle biopsies were collected prior to (PRE), 3 h, and 6 h after each exercise bout, and 58 genes associated with skeletal muscle hypertrophy were manually interrogated from our prior microarray data. Select targets were further interrogated for associated protein expression and phosphorylation induced-signaling events. Although none of the 58 gene targets demonstrated significant bout x time interactions, ~57% (32 genes) showed a significant main effect of time from PRE to 3 h (15↑ and 17↓,

Indexed as

Muscle, SkeletalResistance TrainingGene ExpressionHumansHypertrophyMaleMechanistic Target of Rapamycin Complex 1MyostatinRNA, MessengerYoung AdultMechanistic Target of Rapamycin Complex 1MyostatinRNA, Messengeracute resistance exercisegene expressionmRNAprotein

Identifiers

PMID36980239
PMCPMC10047349
OpenAlexW4324360046

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read27
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.