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Intermittent and continuous high‐intensity exercise training induce similar acute but different chronic muscle adaptations

2014· article· en· W1531770149 on OpenAlexaff
Andrew J.R. Cochran, Michael E. Percival, Steven Tricarico, Jonathan P. Little, Naomi M. Cermak, Jenna B. Gillen, Mark A. Tarnopolsky, Martin J. Gibala

Bibliographic record

VenueExperimental Physiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsHigh-intensity interval trainingInterval trainingSkeletal muscleAMPKMedicineMitochondrial biogenesisInternal medicineContinuous trainingEndocrinologyCardiologyPhysical therapyProtein kinase ABiologyKinaseMitochondrionCell biology

Abstract

fetched live from OpenAlex

New Findings What is the central question of this study? How important is the interval in high‐intensity interval training (HIIT)? What is the main finding and its importance? The intermittent nature of HIIT is important for maximizing skeletal muscle adaptations to this type of exercise, at least when a relatively small total volume of work is performed in an ‘all‐out’ manner. The protein signalling responses to an acute bout of HIIT were generally not predictive of training‐induced outcomes. Nonetheless, a single session of exercise lasting <10 min including warm‐up, performed three times per week for 6 weeks, was sufficient to improve maximal aerobic capacity. High‐intensity interval training (HIIT) performed in an ‘all‐out’ manner (e.g. repeated Wingate tests) is a time‐efficient strategy to induce skeletal muscle remodelling towards a more oxidative phenotype. A fundamental question that remains unclear, however, is whether the intermittent or ‘pulsed’ nature of the stimulus is critical to the adaptive response. In study 1, we examined whether the activation of signalling cascades linked to mitochondrial biogenesis was dependent on the manner in which an acute high‐intensity exercise stimulus was applied. Subjects performed either four 30 s Wingate tests interspersed with 4 min of rest (INT) or a bout of continuous exercise (CONT) that was matched for total work (67 ± 7 kJ) and which required ∼4 min to complete as fast as possible. Both protocols elicited similar increases in markers of adenosine monophosphate‐activated protein kinase (AMPK) and p38 mitogen‐activated protein kinase activation, as well as Peroxisome proliferator‐activated receptor gamma coactivator 1‐alpha (PGC‐1α) mRNA expression (main effects for time, P ≤ 0.05). In study 2, we determined whether 6 weeks of the CONT protocol (3 days per week) would increase skeletal muscle mitochondrial content to a similar extent to what we have previously reported after 6 weeks of INT. Despite similar acute signalling responses to the CONT and INT protocols, training with CONT did not increase the maximal activity or protein content of a range of mitochondrial markers. However, peak oxygen uptake was higher after CONT training (from 45.7 ± 5.4 to 48.3 ± 6.5 ml kg−1 min−1; P < 0.05) and 250 kJ time trial performance was improved (from 26:32 ± 4:48 to 23:55 ± 4:16 min:s; P < 0.001) in our recreationally active participants. We conclude that the intermittent nature of the stimulus is important for maximizing skeletal muscle adaptations to low‐volume, all‐out HIIT. Despite the lack of skeletal muscle mitochondrial adaptations, our data show that a training programme based on a brief bout of high‐intensity exercise, which lasted <10 min per session including warm‐up, and performed three times per week for 6 weeks, improved peak oxygen uptake in young healthy subjects.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.258
Teacher spread0.240 · 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

Citations123
Published2014
Admission routes1
Has abstractyes

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