Effects of Taper on Endurance Cycling Capacity and Single Muscle Fiber Properties
Bibliographic record
Abstract
PURPOSE: It was hypothesized that metabolic adaptations in single muscle cells after a taper period are fiber type (I and II) specific and protocol regimen dependent. METHODS: After 7-wk intensive endurance training, 22 male cyclists (VO2max=4.42 +/- 0.40 L.min(-1)) were randomly assigned to one of three 7-d taper groups: the control group (CON, N=7) continued weekly training, the first experimental group (INT) maintained training intensity but reduced duration (N=7), and the second experimental group (DUR) maintained training duration but reduced exercise intensity (N=8). Each cyclist completed a simulated 40-km time trial (40TT) before and after tapering on a set of wind-loaded rollers using their own bicycle. Muscle biopsies were taken immediately before the 40TT both before and after tapering, and analyzed for mATPase, succinate dehydrogenase (SDH), cyctochrome oxidase (CYTOX), alpha-glycerolphosphate dehydrogenase (alpha-GPD), and beta-hydroxyacyl CoA dehydrogenase (beta-HOAD) in Type I and II fibers, separately, using quantitative histochemistry. RESULTS: The results showed significant (P< or =0.05) increases in SDH (Type I) and mATPase, CYTOX, beta-HOAD, and SDH (Type II fibers) in the INT group, and significant increases in CYTOX (Type I) and beta-HOAD (Type I and II fibers) in the DUR group. Regression analysis showed that the change (posttaper minus pretaper) in simulated 40-km endurance time was correlated with the change in CYTOX and SDH activity for all groups combined (r2=0.62-0.72). CONCLUSION: These results demonstrated that the metabolic properties of different fiber types are altered with tapering, that the type of taper protocol used influences their physiological adaptation, and that improvements in simulated 40-km endurance time were related to changes in metabolic properties of the muscle at the single fiber level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".