Optimal length, calcium sensitivity, and twitch characteristics of skeletal muscles from <i>mdm</i> mice with a deletion in N2A titin
Bibliographic record
Abstract
During isometric contractions, the optimal length of skeletal muscles increases with decreasing activation. The underlying mechanism for this phenomenon is thought to be linked to length-dependence of Ca2+-sensitivity. Muscular dystrophy with myositis (mdm), a recessive titin mutation in mice, was used as a tool to study the role of titin in activation-dependence of optimal length and length-dependence of Ca2+ sensitivity. We measured the shift in optimal length between tetanic and twitch stimulation in mdm and wild type muscles, and the length-dependence of Ca2+ sensitivity at short and long sarcomere lengths in mdm and wild type fiber bundles. The results indicate that the mdm mutation leads to a loss of activation-dependence of optimal length without the expected change in length-dependence of Ca2+ sensitivity, demonstrating that these properties are not linked, as previously suggested. Furthermore, mdm muscles produced maximum tetanic stress during sub-optimal filament overlap at lengths similar to twitch contractions in both genotypes, but the difference explains less than half of the observed reduction in active force of mdm muscles. Mdm muscles also exhibited increased electromechanical delay, contraction and relaxation times, and decreased rate of force development in twitch contractions. We conclude that the small deletion in titin associated with mdm in skeletal muscles alters force production, suggesting an important regulatory role for titin in active force production. The molecular mechanisms for titin's role in regulating muscle force production remain to be elucidated.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".