Sarcolipin deletion exacerbates soleus muscle atrophy and weakness in phospholamban overexpressing mice
Bibliographic record
Abstract
Sarcolipin (SLN) and phospholamban (PLN) are two small proteins that regulate the sarco(endo)plasmic reticulum Ca2+-ATPase pumps. In a recent study, we discovered that Pln overexpression (PlnOE) in slow-twitch type I skeletal muscle fibers drastically impaired SERCA function and caused a centronuclear myopathy-like phenotype, severe muscle atrophy and weakness, and an 8 to 9-fold upregulation of SLN protein in the soleus muscles. Here, we sought to determine the physiological role of SLN upregulation, and based on its role as a SERCA inhibitor, we hypothesized that it would represent a maladaptive response that contributes to the SERCA dysfunction and the overall myopathy observed in the PlnOE mice. To this end, we crossed Sln-null (SlnKO) mice with PlnOE mice to generate a PlnOE/SlnKO mouse colony and assessed SERCA function, CNM pathology, in vitro contractility, muscle mass, calcineurin signaling, daily activity and food intake, and proteolytic enzyme activity. Our results indicate that genetic deletion of Sln did not improve SERCA function nor rescue the CNM phenotype, but did result in exacerbated muscle atrophy and weakness, due to a failure to induce type II fiber compensatory hypertrophy and a reduction in total myofiber count. Mechanistically, our findings suggest that impaired calcineurin activation and resultant decreased expression of stabilin-2, and/or impaired autophagic signaling could be involved. Future studies should examine these possibilities. In conclusion, our study demonstrates the importance of SLN upregulation in combating muscle myopathy in the PlnOE mice, and since SLN is upregulated across several myopathies, our findings may reveal SLN as a novel and universal therapeutic target.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".