Running 40 Minutes under Temperate or Hot Environment Does Not Affect Operating Fascicle Length
Bibliographic record
Abstract
PURPOSE: Muscle mechanics is paramount in our understanding of motor performance. However, little is known regarding the sensitivity of fascicle dynamics and connective tissues stiffness to exercise duration and ambient temperature during running, both increasing muscle temperature. This study aimed to determine gastrocnemius medialis (GM) fascicle dynamics in vivo during running in temperate and hot conditions, as well as muscle-tendon unit responses. METHODS: Using ultrafast ultrasound, 15 participants (8 men, 7 women; 26 ± 3 yr) were tested before, during (2 and 40 min), and after a running task (40 min at 10 km·h -1 ) in temperate (TEMP; ~23°C) and hot (HOT: ~38°C) conditions. RESULTS: Although core, skin temperatures, and heart rate increased from the beginning to the end of the exercise and in a larger extent in HOT than TEMP ( P < 0.001), the physiological stress elicited did not alter running temporal parameters and GM fascicle operating lengths, with similar behavior of the fascicles on their force-length relationship, over time (2 vs 40 min) or across condition (TEMP vs HOT; P ≥ 0.248). Maximal voluntary force production did not reported statistical changes after exercise ( P = 0.060), and the connective tissues stiffness measured (i.e., passive muscle and stiffness of the series-elastic elements) did not show neither time ( P ≥ 0.281), condition ( P ≥ 0.256) nor time-condition interaction ( P ≥ 0.465) effect. CONCLUSIONS: This study revealed that prolonged running exercise does not alter muscle-tendon unit properties and interplay, which are not influenced by ambient temperature. These findings may rule out potential detrimental effects of heat on muscle properties and encourage further investigations on longer and more intense running exercise.
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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) | 0.003 | 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".