Differences in titin segmental elongation between passive and active stretch in skeletal muscle
Bibliographic record
Abstract
Since the 1950s, muscle contraction has been explained using a two-filament system in which actin and myosin exclusively dictate active force in muscle sarcomeres. Decades later, a third filament called titin was discovered. This titin filament has recently been identified as an important regulator of active force, but has yet to be incorporated into contemporary theories of muscle contraction. When sarcomeres are actively stretched, a substantial and rapid increase in force occurs, which has been suggested to arise in part from titin-actin binding that is absent in passively stretched sarcomeres. However, there is currently no direct evidence for such binding within muscle sarcomeres. Therefore, we aimed to determine whether titin binds to actin in actively but not in passively stretched sarcomeres by observing length changes of proximal and distal titin segments in the presence and absence of calcium. We labeled I-band titin with fluorescent F146 antibody in rabbit psoas myofibrils and tracked segmental elongations during passive (no calcium) and active (high calcium) stretch. Without calcium, proximal and distal segments of titin elongated as expected based on their free spring properties. In contrast, active stretch differed statistically from passive stretch, demonstrating that calcium activation increases titin segment stiffness, but not in an actin-dependent manner. The consistent elongation of the proximal segment was contrary to what was expected if titin's proximal segment was attached to actin. This rapid calcium-dependent change in titin stiffness likely contributes to active muscle force regulation in addition to actin and myosin.
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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) | 0.001 | 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".