Combinatory effects of siRNA-induced myostatin inhibition and exercise on skeletal muscle homeostasis and body composition
Bibliographic record
Abstract
Abstract Inhibition of myostatin (Mstn) stimulates skeletal muscle growth, reduces body fat, and induces a number of metabolic changes. However, it remains unexplored how exercise training modulates the response to Mstn inhibition. The aim of this study was to investigate how siRNA-mediated Mstn inhibition alone but also in combination with physical activity affects body composition and skeletal muscle homeostasis. Adult mice were treated with Mstn-targeting siRNA and subjected to a treadmill-based exercise protocol for 4 weeks. Effects on skeletal muscle and fat tissue, expression of genes, and serum concentration of proteins involved in myostatin signaling, skeletal muscle homeostasis, and lipid metabolism were investigated and compared with Mstn(-/-) mice. The combination of siRNA-mediated Mstn knockdown and exercise induced skeletal muscle hypertrophy, which was associated with an upregulation of markers for satellite cell activity. SiRNA-mediated Mstn knockdown decreased visceral fat and modulated lipid metabolism similar to effects observed in Mstn(-/-) mice. Myostatin did not regulate its own expression via an autoregulatory loop, however, Mstn knockdown resulted in a decrease in the serum concentrations of myostatin propeptide, leptin, and follistatin. The ratio of these three parameters was distinct between Mstn knockdown, exercise, and their combination. Taken together, siRNA-mediated Mstn knockdown in combination with exercise stimulated skeletal muscle hypertrophy. Each intervention or their combination induced a specific set of adaptive responses in the skeletal muscle and fat metabolism which could be identified by marker proteins in serum.
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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".