MétaCan
Menu
Back to cohort

Regulation of Erythropoietin Expression in Response to Exercise in Mouse and Human Skeletal Muscle

2017· article· en· W4389025542 on OpenAlexaffabout
Brittany A. Edgett, Laura Farquharson, Nadya Romanova, Keith R. Brunt, Brendon J. Gurd, Jeremy A. Simpson

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsSaint John Regional HospitalDalhousie UniversityUniversity of GuelphQueen's University
Fundersnot available
KeywordsErythropoietinSkeletal muscleInternal medicineEndocrinologyMedicineGlycolysisContractilityErythropoiesisVastus lateralis muscleSoleus muscleGene expressionEndurance trainingBiologyMetabolismAnemiaBiochemistry

Abstract

fetched live from OpenAlex

Erythropoietin (EPO) is the master regulator of erythropoiesis and also plays a role in cytoprotection, cell proliferation and heart contractility. In human skeletal muscle, EPO mRNA expression increases in response to acute exercise, however, whether glycolytic or oxidative muscle fibers differentially produce EPO is unknown. Thus, the purpose of this study was to examine EPO mRNA expression in oxidative and glycolytic muscles following acute exercise in mice. Further, we also examined whether training status had an effect on EPO expression. Experiment 1 involved young healthy men (age, 21.4 ± 2.8 years; VO 2 peak, 47.1 ± 11.8 mL min −1 kg −1 ) from a previously published study (Edgett et al. 2016) who performed a single bout of exercise at ~55% of peak aerobic work rate for 1 hour. Muscle biopsies were obtained from the vastus lateralis at rest and 3 hours post‐exercise. Experiment 2 involved 8 week‐old male C57/B6 mice that were either exercise‐trained by treadmill running (1 hour/day, 4 days/week) or remained sedentary (untrained) for 5 weeks. Following the intervention, all mice performed an exhaustive exercise bout that began at a speed of 12 m/min with a 20‐degree grade; speed was subsequently increased by 1 m/min at 2, 5, 10, 20, 30 and 40 min, or until mice reached exhaustion. Soleus (oxidative muscle) and extensor digitorum longus (EDL, glycolytic muscle) were harvested at 1, 2 and 4 hours post‐exercise. All samples were analyzed by real‐time qPCR for changes in EPO mRNA expression. In agreement with a previous report, EPO mRNA expression increased 14 ± 5% in human skeletal muscle 3 hours post‐exercise. In experiment 2, EPO expression increased 4.1 ± 2.8 and 7.4 ± 1.7 fold at 1 hour post‐exercise in the soleus muscle of untrained and trained mice, respectively, before returning towards baseline. In EDL, post‐exercise EPO expression increased 4.1 ± 1.0 fold by 2 hours and plateaued thereafter in only untrained mice; this response was blunted in trained mice. Here we show that EPO expression increased post‐exercise in both glycolytic and oxidative murine skeletal muscles; training had a fiber‐type‐specific differential effect in these muscles. Future studies should determine the physiological significance of skeletal muscle‐derived EPO. Support or Funding Information This study was supported by funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) to B.A.E., K.R.B., B.J.G. and J.A.S.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.299
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicErythropoietin and Anemia TreatmentFrench-language works237,207