Neurogranin is expressed in mammalian skeletal muscle and inhibits calcineurin signaling and myoblast fusion
Bibliographic record
Abstract
Calcineurin is a Ca2+/calmodulin (CaM)-dependent phosphatase that plays a critical role in promoting the slow fiber phenotype and myoblast fusion in skeletal muscle, thereby making calcineurin an attractive cellular target for enhancing fatigue resistance, muscle metabolism, and muscle repair. Neurogranin (Ng) is a CaM-binding protein thought to be expressed solely in brain and neurons, where it inhibits calcineurin signaling by sequestering CaM, thus lowering its cellular availability. Here, we demonstrate for the first time the expression of Ng protein and mRNA in mammalian skeletal muscle. Both protein and mRNA levels are greater in slow-oxidative compared with fast-glycolytic muscles. Coimmunoprecipitation of CaM with Ng in homogenates of C2C12 myotubes, mouse soleus, and human vastus lateralis suggests that these proteins physically interact. To determine whether Ng inhibits calcineurin signaling in muscle, we used Ng siRNA with C2C12 myotubes to reduce Ng protein levels by 60%. As a result of reduced Ng expression, C2C12 myotubes had enhanced CaM-calcineurin binding and calcineurin signaling as indicated by reduced phosphorylation of nuclear factor of activated T cells and increased utrophin mRNA. In addition, calcineurin signaling affects the expression of myogenin and stabilin-2, which are involved in myogenic differentiation and myoblast fusion, respectively. Here, we found that both myogenin and stabilin-2 were significantly elevated by Ng siRNA in C2C12 cells, concomitantly with an increased fusion index. Taken together, these results demonstrate the expression of Ng in mammalian skeletal muscle where it appears to be a novel regulator of calcineurin signaling.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".