Low-Volume Interval Training Improves Muscle Oxidative Capacity in Sedentary Adults
Bibliographic record
Abstract
INTRODUCTION: High-intensity interval training (HIT) increases skeletal muscle oxidative capacity similar to traditional endurance training, despite a low total exercise volume. Much of this work has focused on young active individuals, and it is unclear whether the results are applicable to older less active populations. In addition, many studies have used "all-out" variable-load exercise interventions (e.g., repeated Wingate tests) that may not be practical for all individuals. We therefore examined the effect of a more practical low-volume submaximal constant-load HIT protocol on skeletal muscle oxidative capacity and insulin sensitivity in middle-aged adults, who may be at a higher risk for inactivity-related disorders. METHODS: Seven sedentary but otherwise healthy individuals (three women) with a mean ± SD age, body mass index, and peak oxygen uptake (VO(2peak)) of 45 ± 5 yr, 27 ± 5 kg·m(-2), and 30 ± 3 mL·kg(-1)·min(-1) performed six training sessions during 2 wk. Each session involved 10 × 1-min cycling at ∼60% of peak power achieved during a ramp VO(2peak) test (eliciting ∼80%-95% of HR reserve) with 1 min of recovery between intervals. Needle biopsy samples (vastus lateralis) were obtained before training and ∼72 h after the final training session. RESULTS: Muscle oxidative capacity, as reflected by the protein content of citrate synthase and cytochrome c oxidase subunit IV, increased by ∼35% after training. The transcriptional coactivator peroxisome proliferator-activated receptor γ coactivator 1α was increased by ∼56% after training, but the transcriptional corepressor receptor-interacting protein 140 remained unchanged. Glucose transporter protein content increased ∼260%, and insulin sensitivity, on the basis of the insulin sensitivity index homeostasis model assessment, improved by ∼35% after training. CONCLUSIONS: Constant-load low-volume HIT may be a practical time-efficient strategy to induce metabolic adaptations that reduce the risk for inactivity-related disorders in previously sedentary middle-aged adults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".