Short-term high- vs. low-velocity isokinetic lengthening training results in greater hypertrophy of the elbow flexors in young men
Bibliographic record
Abstract
We performed two studies to determine the effect of a resistive training program comprised of fast vs. slow isokinetic lengthening contractions on muscle fiber hypertrophy. In study I, we investigated the effect of fast (3.66 rad/s; Fast) or slow (0.35 rad/s; Slow) isokinetic high-resistance muscle lengthening contractions on muscle fiber and whole muscle cross-sectional area (CSA) of the elbow flexors was investigated in young men. Twelve subjects (23.8 +/- 2.4 yr; means +/- SD) performed maximal resistive lengthening isokinetic exercise with both arms for 8 wk (3 days/wk), during which they trained one arm at a Fast velocity while the contralateral arm performed an equivalent number of contractions at a Slow velocity. Before (Pre) and after (Post) the training, percutaneous muscle biopsies were taken from the midbelly of the biceps brachii and analyzed for fiber type and CSA. Type I muscle fiber size increased Pre to Post (P < 0.05) in both Fast and Slow arms. Type IIa and IIx muscle fiber CSA increased in both arms, but the increases were greater in the Fast- vs. the Slow-trained arm (P < 0.05). Elbow flexor CSA increased in Fast and Slow arms, with the increase in the Fast arm showing a trend toward being greater (P = 0.06). Maximum torque-generating capacity also increased to a greater degree (P < 0.05) in the Fast arm, regardless of testing velocity. In study II, we attempted to provide some explanation of the greater hypertrophy observed in study I by examining an indicator of protein remodeling (Z-line streaming), which we hypothesized would be greater in the Fast condition. Nine men (21.7 +/- 2.4 yr) performed an acute bout (n = 30, 3 sets x 10 repetitions/set) of maximal lengthening contractions at Fast and Slow velocities used in the training study. Biopsies revealed that Fast lengthening contractions resulted in more (185 +/- 1 7%; P < 0.01) Z-band streaming per millimeter squared muscle vs. the Slow arm. In conclusion, training using Fast (3.66 rad/s) lengthening contractions leads to greater hypertrophy and strength gains than Slow (0.35 rad/s) lengthening contractions. The greater hypertrophy seen in the Fast-trained arm (study I) may be related to a greater amount of protein remodeling (Z-band streaming; study II).
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".