How do differences in Achilles’ tendon moment arm lengths affect muscle-tendon dynamics and energy cost during running?
Bibliographic record
Abstract
Introduction The relationship between the Achilles tendon moment arm length (ATMA) and the energy cost of running (Erun) has been disputed. Some studies suggest a short ATMA reduces Erun while others claim a long ATMA reduces Erun. For a given ankle joint moment, a short ATMA permits a higher tendon strain energy storage, whereas a long ATMA reduces muscle fascicle force and muscle energy cost but shortening velocity is increased, elevating the metabolic cost. These are all conflicting mechanisms to reduce Erun, since AT energy storage comes at a metabolic cost. Neither of these proposed mechanisms have been examined together. Methods We measured ATMA using the tendon travel method in 17 males and 3 females (24 ± 3 years, 75 ± 11 kg, 177 ± 7 cm). They ran on a motorized treadmill for 10 min at 2.5 m · s−1 while Erun was measured. AT strain energy storage, muscle lengths, velocities and muscle energy cost were calculated during time-normalized stance from force and ultrasound data. A short (SHORT n = 11, ATMA = 29.5 ± 2.0 mm) and long (LONG, n = 9, ATMA = 36.6 ± 2.5 mm) ATMA group was considered based on a bimodal distribution of measured ATMA. Results Mean Erun was 4.9 ± 0.4 J · kg−1 · m−1. The relationship between ATMA and Erun was not significant (r2 = 0.13, p = 0.12). Maximum AT force during stance was significantly lower in LONG (5,819 ± 1,202 N) compared to SHORT (6,990 ± 920 N, p = 0.028). Neither AT stretch nor AT strain energy storage was different between groups (mean difference: 0.3 ± 1 J · step−1, p = 0.84). Fascicle force was significantly higher in SHORT (508 ± 93 N) compared to LONG (468 ± 84 N. p = 0.02). Fascicle lengths and velocities were similar between groups (p > 0.72). Muscle energy cost was significantly lower in LONG (0.028 ± 0.08 J · kg · step−1) compared to SHORT (0.045 ± 0.14 J · kg · step−1p = 0.004). There was a significant negative relationship between ATMA and total muscle energy cost relative to body mass across the stance phase (r = −0.699, p < 0.001). Discussion Together these results suggest that a LONG ATMA serves to potentially reduce Erun by reducing the muscle energy cost of the plantarflexors during stance. The relative importance of AT energy storage and return in reducing Erun should be re-considered.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".