Evidence map›Paper›PMID 34878641›Full record

SynthesisSports medicine (Auckland, N.Z.)2022

Factors Influencing AMPK Activation During Cycling Exercise: A Pooled Analysis and Meta-Regression.

Jeffrey A Rothschild, Hashim Islam, David J Bishop, Andrew E Kilding, Tom Stewart, Daniel J Plews

Open access · greenAbstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.9field-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

16 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Mechanisms of the NADFrontiers in cell and developmental biology · 2024
    Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Irisin, Exercise, and COVID-19.Frontiers in endocrinology · 2022
    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

6 authors at 3 institutions in 3 countries.

Jeffrey A RothschildSports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand. Jeffrey.Rothschild@aut.ac.nz.ORCID 0000-0003-0014-5878
Hashim IslamSchool of Health and Exercise Sciences, University of British Columbia Okanagan, Kelowna, BC, Canada.ORCID 0000-0002-7145-0522
David J BishopInstitute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia.ORCID 0000-0002-6956-9188
Andrew E KildingSports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.ORCID 0000-0002-5334-8831
Tom StewartSports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.
Daniel J PlewsSports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.
Auckland University of Technology · NZEdith Cowan University · AUUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 5' adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a cellular energy sensor that is activated by increases in the cellular AMP/adenosine diphosphate:adenosine triphosphate (ADP:ATP) ratios and plays a key role in metabolic adaptations to endurance training. The degree of AMPK activation during exercise can be influenced by many factors that impact on cellular energetics, including exercise intensity, exercise duration, muscle glycogen, fitness level, and nutrient availability. However, the relative importance of these factors for inducing AMPK activation remains unclear, and robust relationships between exercise-related variables and indices of AMPK activation have not been established.

objectivesThe purpose of this analysis was to (1) investigate correlations between factors influencing AMPK activation and the magnitude of change in AMPK activity during cycling exercise, (2) investigate correlations between commonly reported measures of AMPK activation (AMPK-α2 activity, phosphorylated (p)-AMPK, and p-acetyl coenzyme A carboxylase (p-ACC), and (3) formulate linear regression models to determine the most important factors for AMPK activation during exercise.

methodsData were pooled from 89 studies, including 982 participants (93.8% male, maximal oxygen consumption [[Formula: see text]] 51.9 ± 7.8 mL kg

resultsSignificant correlations (r = 0.19-0.55, p < .05) with AMPK activity were found between end-exercise muscle glycogen, exercise intensity, and muscle metabolites phosphocreatine, creatine, and free ADP. All markers of AMPK activation were significantly correlated, with the strongest relationship between AMPK-α2 activity and p-AMPK (r = 0.56, p < 0.001). The most important predictors of AMPK activation were the muscle metabolites and exercise intensity.

conclusionMuscle glycogen, fitness level, exercise intensity, and exercise duration each influence AMPK activity during exercise when all other factors are held constant. However, disrupting cellular energy charge is the most influential factor for AMPK activation during endurance exercise.

Indexed as

AMP-Activated Protein KinasesMuscle, SkeletalAcetyl-CoA CarboxylaseAdenosine DiphosphateAdenosine MonophosphateFemaleGlycogenHumansMaleAcetyl-CoA CarboxylaseAdenosine DiphosphateAdenosine MonophosphateAMP-Activated Protein KinasesGlycogen

Identifiers

PMID34878641
OpenAlexW4200609842

What Socratic 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 Socratic graph.