In Vivo Sarcomere Lengths Become More Non-uniform upon Activation in Intact Whole Muscle
Bibliographic record
Abstract
The sarcomere force-length relationship has been extensively used to predict muscle force potential. The common practice is to measure the mean sarcomere length (SL) in a relaxed muscle at a single location and at a given length, and this mean SL is assumed to represent the SLs at other locations across the muscle. However, in a previous study, we found that SLs are highly non-uniform across an intact passive muscle. Moreover, SL non-uniformity increases during activation in single myofibril experiments. Myofibrils lack some structural proteins that comprise an intact muscle, and therefore, the increased SL dispersion upon activation seen in myofibrils may not occur in intact whole muscle. The objectives of the current study were (i) to measure the distribution of SLs in an activated intact muscle; and (ii) to assess the feasibility of using the mean SL measured at a specific location of the muscle to predict muscle force. Using state-of-the-art multi-photon microscopy and a miniature tendon force transducer, in vivo sarcomeres in the mouse tibialis anterior were imaged simultaneously with muscle force during isometric tetanic contractions. We found that in vivo SL dispersion increased substantially during activation and reached average differences of ~1.0µm. These differences in SL are associated with theoretical force differences of 70-100% of the maximal isometric force. Furthermore, SLs measured at a single location in the passive muscle were poor predictors of active force potential. Although mean SLs in the activated muscle were better predictors of force potential, predicted forces still differed by as much as 35% from the experimentally measured maximal isometric forces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".