Energy Cost of Force Production After a Stretch-Shortening Cycle in Skinned Muscle Fibers: Does Muscle Efficiency Increase?
Bibliographic record
Abstract
Muscle force is enhanced during shortening when shortening is preceded by an active stretch. This phenomenon is known as the stretch-shortening cycle (SSC) effect. For some stretch-shortening conditions this increase in force during shortening is maintained following SSCs when compared to the force following a pure shortening contraction. It has been suggested that the residual force enhancement property of muscles, which comes into play during the stretch phase of SSCs may contribute to the force increase after SSCs. Knowing that residual force enhancement is associated with a substantial reduction in metabolic energy per unit of force, it seems reasonable to assume that the metabolic energy cost per unit of force is also reduced following a SSC. The purpose of this study was to determine the energy cost per unit of force at steady-state following SSCs and compare it to the corresponding energy cost following pure shortening contractions of identical speed and magnitude. We hypothesized that the energy cost per unit of muscle force is reduced following SSCs compared to the pure shortening contractions. For the SSC tests, rabbit psoas fibers (n= 12) were set at an average sarcomere length (SL) of 2.4 μm, activated, actively stretched to a SL of 3.2 μm, and shortened to a SL of 2.6 or 3.0 μm. For the pure shortening contractions, the same fibers were activated at a SL of 3.2 μm and actively shortened to a SL of 2.6 or 3.0 μm. The amount of ATP consumed was measured over a 40 s steady-state total isometric force following either the SSCs or the pure active shortening contractions. Fiber stiffness was determined in an additional set of 12 fibers, at steady-state for both experimental conditions. Total force, ATP consumption, and stiffness were greater following SSCs compared to the pure shortening contractions, but ATP consumption per unit of force was the same between conditions. These results suggest that the increase in total force observed following SSCs was achieved with an increase in the proportion of attached cross-bridges and titin stiffness. We conclude that muscle efficiency is not enhanced at steady-state following SSCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".