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Record W2910611315 · doi:10.1113/ep087401

Repeatability of exercise‐induced changes in mRNA expression and technical considerations for qPCR analysis in human skeletal muscle

2019· article· en· W2910611315 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueExperimental Physiology · 2019
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of WaterlooUniversity of GuelphSaint John Regional HospitalQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRepeatabilitySkeletal muscleMessenger RNAHuman muscleBiologyComputational biologyInternal medicineEndocrinologyMedicineChemistryGeneticsGeneChromatography

Abstract

fetched live from OpenAlex

New Findings What is the central question of this study? Are individual changes in exercise‐induced mRNA expression repeatable (i.e. representative of the true response to exercise rather than random error)? What is the main finding and its importance? Exercise‐induced changes in mRNA expression are not repeatable even under identical experimental conditions, thereby challenging the use of mRNA expression as a biomarker of adaptive potential and/or individual responsiveness to exercise. Abstract It remains unknown if (1) the observed change in mRNA expression reflects an individual's true response to exercise or random (technical and/or biological) error, and (2) the individual responsiveness to exercise is protocol‐specific. We examined the repeatability of skeletal muscle PGC‐1α, PDK4, NRF‐1, VEGF‐A, HSP72 and p53 mRNA expression following two identical endurance exercise (END) bouts (END‐1, END‐2; 30 min of cycling at 65% of peak work rate (WR peak ), n = 11) and inter‐individual variability in PGC‐1α and PDK4 mRNA expression following END and sprint interval training (SIT; 8 × 20 s cycling intervals at ∼170% WR peak , n = 10) in active young males. The repeatability of key gene analysis steps (RNA extraction, reverse transcription, qPCR) and within‐sample fibre‐type distribution ( n = 8) was also determined to examine potential sources of technical error in our analyses. Despite highly repeatable exercise bout characteristics (work rate, heart rate, blood lactate; ICC > 0.71; CV < 10%; r > 0.85, P < 0.01), gene analysis steps (ICC > 0.73; CV < 24%; r > 0.75, P < 0.01), and similar group‐level changes in mRNA expression, individual changes in PGC‐1α, PDK4, VEGF‐A and p53 mRNA expression were not repeatable (ICC < 0.22; CV > 20%; r < 0.21). Fibre‐type distribution in two portions of the same muscle biopsy was highly variable and not significantly related (ICC = 0.39; CV = 26%; r = 0.37, P = 0.37). Since individual changes in mRNA expression following identical exercise bouts were not repeatable, inferences regarding individual responsiveness to END or SIT were not made. Substantial random error exists in changes in mRNA expression following acute exercise, thereby challenging the use of mRNA expression for analysing individual responsiveness to exercise.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.433
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.339
Teacher spread0.310 · 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