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Blood flow restriction does not alter the early hypertrophic signaling and short-term adaptive response to resistance exercise when performed to task failure

2023· article· en· W4365458055 on OpenAlexafffund
Christopher Pignanelli, Graham P. Holloway, Jamie F. Burr

Bibliographic record

VenueJournal of Applied Physiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Guelph
FundersOntario Ministry of Economic Development, Job Creation and TradeCanada Foundation for InnovationOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsBlood flow restrictionAnabolismMuscle hypertrophyResistance trainingMedicineP70-S6 Kinase 1Internal medicineAnalysis of varianceEndocrinologyCardiologyPhosphorylationBiologyProtein kinase B

Abstract

fetched live from OpenAlex

The addition of blood flow restriction during low-load resistance exercise is considered to increase the signaling events and muscle growth responses to a greater extent than low-load resistance exercise alone. It remains unclear whether blood flow restriction accelerates or increases these adaptive responses, as most studies have each condition perform the same amount of work. Despite different amounts of work performed, we show similar signaling and muscle growth responses occur after low-load resistance exercise with and without blood flow restriction. Our work supports that blood flow restriction accelerates fatigue but does not increase the signaling events and muscle growth responses during low-load resistance 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.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

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