Sarcolipin Ablation Impairs Muscle Regeneration After Acute Injury
Bibliographic record
Abstract
Sarcolipin (SLN) is a small transmembrane protein that regulates the sarco(endo)plasmic reticulum calcium ATPase (SERCA) pump in muscle. SLN is highly expressed in embryonic muscle and is involved in the regulation of myogenesis. SLN is also upregulated in mouse dystrophic muscles but the role of SLN in muscular dystrophy is unknown. Since muscular dystrophy is characterized by high rates of muscle degeneration/regeneration, one hypothesis is that SLN may be important in the regeneration process but this has not been examined specifically. Here, we used an acute cardiotoxin injury model and Sln ‐null mice to determine SLN's role in muscle regeneration. The tibialis anterior of 30 mice, 15 wild type (WT) and 15 Sln ‐null mice were injected with cardiotoxin and sacrificed at day 7, 14 and 21 post injury. Muscle homogenates and sections were prepared and used for immunoblotting and immunofluorescence analyses, respectively. Interestingly, ectopic expression of SLN was seen in WT animals only at 21 days post injury. Correspondingly, Sln‐ null mice showed elevated centralized nuclei, a marker of regenerating fibers, specifically at day 21 post injury compared to their WT counterparts (2.7 ± 1.0 ×10 −4 vs. 3.8 ± 0.6 ×10 −4 , per regenerating area (μm 2 ), p=0.03 ). In addition, the average cross‐sectional area of the regenerating myofibers was significantly smaller in the Sln‐ null mice only at day 21 post injury compared to WT (1925 ± 168 μm 2 vs. 1471 ± 57 μm 2 , p =0.01 ). Taken together, the failure to clear central nuclei and increase myofiber size at day 21 post injury indicates that SLN ablation delays the later stages of muscle regeneration. Support or Funding Information This work was supported by the Canadian Institutes of Health Research (CIHR; MOP 86618 and MOP 47296 to A.R.T).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".