Improvement of Ca <sup>2+</sup> Transport and Muscle Relaxation in Skeletal Muscle From Sarcolipin Null Mice
Bibliographic record
Abstract
Sarcolipin (SLN) is an inhibitor of SERCA type pumps by direct binding. To demonstrate whether ablation of SLN in skeletal muscle might impair skeletal muscle function directly, we analyzed skeletal muscle contractility and Ca 2+ uptake in SLN null mice (KO). SLN protein expression in wildtype mice (WT) was found to be highest in the quadriceps and gastrocnemius (G) followed by the diaphragm and soleus (Sol), whereas very little SLN expression was seen in the tibialis anterior or extensor digitorum longus (EDL). No SLN protein was detected in muscles from KO. Compared with WT, Ca 2+ uptake was increased in the G and Sol of KO muscles, while no significant difference was observed in the EDL. Contractility measurements of WT and KO Sol and EDL muscles were performed. No differences were seen between WT and KO muscles in peak tetanic force; however, peak twitch force was lower in KO by ~28% but only in Sol. Maximum normalized (s‐1) rates of contraction (+dF/dt) and relaxation (−dF/dt) measured during a twitch contraction were significantly higher in Sol of KO compared with WT (+dF/dt, 50.2±5.9 in KO vs 30.9±1.0 in WT; −dF/dt, 7.2±0.5 in KO vs 5.2±0.5 in WT). There were no differences between KO and WT in +dF/dt or −dF/dt in EDL. These results show that SLN regulates muscle contractility in mouse slow twitch fibers by inhibiting SERCA function and reducing Ca 2+ uptake. Supported by HSFO (DHM, PHB, AOG), CIHR (DHM, PHB) and NSERC (ART).
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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".