Residual force enhancement is regulated by titin in skeletal and cardiac myofibrils
Bibliographic record
Abstract
KEY POINTS: When a skeletal muscle is stretched while it contracts, the muscle produces a relatively higher force than the force from an isometric contraction at the same length: a phenomenon referred to as residual force enhancement. Residual force enhancement is puzzling because it cannot be directly explained by the classical force-length relationship and the sliding filament theory of contraction, the main paradigms in the muscle field. We used custom-built instruments to measure residual force enhancement in skeletal myofibrils, and, for the first time, in cardiac myofibrils. Our data report that residual force enhancement is present in skeletal muscles, but not cardiac muscles, and is regulated by the different isoforms of the titin protein filaments. ABSTRACT: When a skeletal muscle contracts isometrically, the muscle produces a force that is relative to the final isometric sarcomere length (SL). However, when the same final SL is reached by stretching the muscle while it contracts, the muscle produces a relatively higher force: a phenomenon commonly referred to as residual force enhancement. In this study, we investigated residual force enhancement in rabbit skeletal psoas myofibrils and, for the first time, cardiac papillary myofibrils. A custom-built atomic force microscope was used in experiments that stretched myofibrils before and after inhibiting myosin and actin interactions to determine whether the different cardiac and skeletal titin isoforms regulate residual force enhancement. At SLs ranging from 2.24 to 3.13 μm, the skeletal myofibrils enhanced the force by an average of 9.0%, and by 29.5% after hindering myosin and actin interactions. At SLs ranging from 1.80 to 2.29 μm, the cardiac myofibrils did not enhance the force before or after hindering myosin and actin interactions. We conclude that residual force enhancement is present only in skeletal muscles and is dependent on the titin isoforms.
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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 | 0.000 |
| 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".