Regulation of muscle force in the absence of actin-myosin-based cross-bridge interaction
Bibliographic record
Abstract
For the past half century, the sliding filament-based cross-bridge theory has been the cornerstone of our understanding of how muscles contract. According to this theory, active force can only occur if there is overlap between the contractile filaments, actin and myosin. Otherwise, forces are thought to be caused by passive structural elements and are assumed to vary solely because of the length of the muscle. We observed increases in muscle force by a factor of 3 to 4 above the purely passive forces for activated and stretched myofibrils in the absence of actin-myosin overlap. We show that this dramatic increase in force is crucially dependent on the presence of the structural protein titin, cannot be explained with calcium activation, and is regulated by actin-myosin-based cross-bridge forces before stretching. We conclude from these observations that titin is a strong regulator of muscle force and propose that this regulation is based on cross-bridge force-dependent titin-actin interactions. These results suggest a mechanism for stability of sarcomeres on the "inherently unstable" descending limb of the force-length relationship, and they further provide an explanation for the protection of muscles against stretch-induced muscle injuries.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".