Shortening Speed Dependence of Concentric Force Potentiation in the Absence of Myosin Phosphorylation
Bibliographic record
Abstract
Contraction‐induced elevation of myoplasmic Ca 2+ leads to sequential activation of skeletal muscle myosin light chain kinase (skMLCK), an enzyme responsible for phosphorylating the myosin regulatory light chain (RLC). In wildtype (WT) mouse skeletal muscle containing skMLCK, force potentiation correlates with RLC phosphate content; although, these muscles may contain an RLC phosphorylation‐independent component. In this study, extensor digitorum longus (EDL) muscles from knockout (KO) C57BL/6 mice, devoid of skMLCK, were activated in vitro (25°C) across a range of stimulation frequencies (10, 25, 45, 70 and 100 Hz) and subjected to shortening ramps at 0.1, 0.3 or 0.5 of maximal shortening velocity (V max ). This was performed before and after a standard conditioning stimulus (CS) that potentiated mean concentric force at 0.3 and 0.5 V max to 1.20 ± 0.03 and 1.30 ± 0.02 of unpotentiated ( pre‐CS ) values, respectively; however, mean forces were depressed to 0.84 ± 0.03 of pre‐CS values at 0.1 V max ( n = 3, P < 0.05). Increasing shortening speed augmented the frequency at which concentric force potentiation was maximal: 25 and 45 Hz at 0.3 and 0.5 V max , respectively. These results mirrored previous results from WT muscles (Gittings et al., 2012), except that concentric force potentiation was attenuated by ~50% across all frequencies at 0.3 and 0.5 V max , while force at 0.1 V max was reduced rather than unchanged. Thus, our data indicates the presence of an RLC phosphorylation‐independent mechanism for potentiation in skMLCK KO muscles that may complement the intact RLC phosphorylation mechanism in WT muscles. Supported by NSERC (2014‐05122).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".