Different Muscle Action Training Protocols on Quadriceps-Hamstrings Neuromuscular Adaptations
Bibliographic record
Abstract
The aim of this study was to compare three specific concentric and eccentric muscle action training protocols on quadriceps-hamstrings neuromuscular adaptations. Forty male volunteers performed 6 weeks of training (two sessions/week) of their dominant and non-dominant legs on an isokinetic dynamometer. They were randomly assigned to one of four groups; concentric quadriceps and concentric hamstrings (CON/CON, n=10), eccentric quadriceps and eccentric hamstrings (ECC/ECC, n=10), concentric quadriceps and eccentric hamstrings (CON/ECC, n=10), or no training (CTRL, n=10). Intensity of training was increased every week by decreasing the angular velocity for concentric and increasing it for eccentric groups in 30°/s increments. Volume of training was increased by adding one set every week. Dominant leg quadriceps and hamstrings muscle thickness, muscle quality, muscle activation, muscle coactivation, and electromechanical delay were tested before and after training. Results revealed that all training groups similarly increased MT of quadriceps and hamstrings compared to control (p<0.05). However, CON/ECC and ECC/ECC training elicited a greater magnitude of change. There were no significant differences between groups for all other neuromuscular variables (p>0.05). These findings suggest that different short-term muscle action isokinetic training protocols elicit similar muscle size increases in hamstrings and quadriceps, but not for other neuromuscular variables. Nevertheless, effect sizes indicate that CON/ECC and ECC/ECC may elicit the greatest magnitude of change in muscle hypertrophy.
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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".