Residual force enhancement decreases when scaling from the single muscle fiber to joint level in humans
Bibliographic record
Abstract
• Residual force enhancement experiments were matched between the joint level and single fibre level within the same participants by employing the same fascicle/fibre excursions relative to optimal length • Residual force enhancement “non-responders” were only present at the joint level • Residual force enhancement was ∼300%–500% greater at the single fibre level than the joint level within the same participants • No relationships were observed between joint-level and single fibre-level residual force enhancement • The development of the rFE non-responder phenomenon is upstream of rFE's cellular mechanisms, most likely involving neural factors Residual force enhancement (rFE), defined as increased isometric force following active lengthening compared to a fixed-end isometric contraction at the same muscle length and level of activation, is present across all scales of muscle. While rFE is always present at the cellular level, often rFE “non-responders” are observed during joint-level voluntary contractions. We compared rFE between the joint level and single fiber level (vastus lateralis biopsies) in 16 young males. In vivo voluntary knee-extensor rFE was measured by comparing steady-state isometric torque between a stretch-hold (maximal activation at 150°, stretch to 70°, hold) and a fixed-end isometric contraction, with ultrasonographic recording of vastus lateralis fascicle length (FL). Fixed-end contractions were performed at 67.5°, 70.0°, 72.5°, and 75.0°; the joint angle that most closely matched FL of the stretch-hold contraction's isometric steady-state was used to calculate rFE. The starting and ending FLs of the stretch-hold contraction were expressed as % optimal FL, determined via torque-angle relationship. In single fiber experiments, the starting and ending fiber lengths were matched relative to optimal length determined from in vivo testing, yielding an average sarcomere excursion of ∼2.2–3.4 µm. There was a greater magnitude of rFE at the single fiber (∼20%) than joint level (∼5%) ( p = 0.004), with “non-responders” only observed at the joint level. By comparing rFE across scales within the same participants, we show the development of the rFE non-responder phenomenon is upstream of rFE's cellular mechanisms, with rFE only lost rather than gained when scaling from single fibers to the joint 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".