Five Weeks of Sprint Interval Training Improve Muscle Glycolytic Content and Activity But Not Time to Task Failure in Severe-Intensity Exercise
Bibliographic record
Abstract
PURPOSE: This study examined the impact of a 5-wk sprint interval training (SIT) intervention on time to task failure (TTF) during severe-intensity constant work rate (CWR) exercise, as well as in glycolytic enzymatic content and activity, and glycogen content. METHODS: Fourteen active males were randomized into either a SIT group ( n = 8) composed of 15 SIT sessions over 5 wk, or a control group ( n = 6). At pretraining period, participants performed i) ramp incremental test to measure the cardiorespiratory function; ii) CWR cycling TTF at 150% of the power output (PO) at the respiratory compensation point (RCP-PO) with muscle biopsies at rest and immediately following task failure. After 5 wk, the same evaluations were repeated (i.e., exercise intensities matched to current training status), and an additional cycling CWR matched to pretraining 150% RCP-PO was performed only for TTF evaluation. The content and enzymatic activity of glycogen phosphorylase (GPhos), hexokinase (HK), phosphofructokinase (PFK), and lactate dehydrogenase (LDH), as well as the glycogen content, were analyzed. Content of monocarboxylate transporter isoform 4 (MCT4) and muscle buffering capacity were also measured. RESULTS: Despite improvements in total work performed at CWR posttraining, no differences were observed for TTF. The GPhos, HK, PFK, and LDH content and activity, and glycogen content also improved after training only in the SIT group. Furthermore, the MCT4 concentrations and muscle buffering capacity were also improved only for the SIT group. However, no difference in glycogen depletion was observed between groups and time. CONCLUSIONS: Five weeks of SIT improved the glycolytic pathway parameters and total work performed; however, glycogen depletion was not altered during CWR severe-intensity exercise, and TTF remained similar.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".