Augmented mitochondrial apoptotic signaling impairs C2C12 myoblast differentiation following cellular aging through sequential passaging
Bibliographic record
Abstract
Aging is associated with the steady decline of several cellular processes. The loss of skeletal muscle mass, termed sarcopenia, is one of the major hallmarks of aging. Aged skeletal muscle exhibits a robust reduction in its regenerative capacity due to dysfunction (i.e., senescence, lack of self-renewal, and impaired differentiation) of resident muscle stem cells, called satellite cells. To replicate aging in vitro, immortalized skeletal muscle cells (myoblasts) can be treated with various agents to mimic age-related dysfunction; however, these come with their own set of limitations. In the present study, we used sequential passaging of mouse myoblasts to mimic impaired differentiation that is observed in aged skeletal muscle. Further, we investigated mitochondrial apoptotic mechanisms to better understand the impaired differentiation in these "aged" cells. Our data shows that sequential passaging (>20 passages) of myoblasts is accompanied with significant reductions in differentiation and elevated cell death. Furthermore, high-passage (HP) myoblasts exhibit greater mitochondrial-mediated apoptotic signaling through mitochondrial BAX translocation, CYCS and AIFM1 release, and caspase-9 activation. Finally, we show that inhibition of mitochondrial outer membrane permeability partly recovered differentiation in HP myoblasts. Together, our findings suggests that mitochondrial apoptotic signaling is a contributing factor to the diminished differentiation that is observed in aged myoblasts.
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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) | 0.001 | 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 | 0.001 |
| 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".