PINK1 Deficiency Alters Muscle Stem Cell Fate Decision and Muscle Regenerative Capacity
Bibliographic record
Abstract
ABSTRACT Maintenance of optimal mitochondrial function plays a crucial role in the regulation of muscle stem cell (MuSC) behavior, but the underlying maintenance mechanisms remain ill defined. In this study, we explored the importance of mitophagy, as a mitochondrial quality control regulator, in MuSCs and the role this process plays in maintaining optimal muscle regenerative capacity. Here we show that MuSCs exhibit dynamic alterations in mitophagy under different physiological myogenic states. In particular, quiescent MuSCs exhibit high levels of PINK1/Parkin-dependent mitophagy, which is rapidly decreased upon transition to an early activation state. Genetic disruption of this pathway using Pink1 knockout mice reduced mitophagy in quiescent MuSCs, which was accompanied by increased mitochondrial ROS release and mitochondrial network fragmentation. These abnormalities led to hampered self-renewal of MuSCs which ultimately translated in a progressive loss of muscle regeneration following repetitive injury. However, proliferation and differentiation capacity were unaltered in the absence of PINK1, indicating that altered fate decisions is the main mechanism underlying impaired muscle regeneration. Impaired fate decisions in PINK1 deficient MuSCs could be restored by scavenging excess mitochondrial ROS. Together, these data shed new light on the regulation of mitophagy during MuSC state transitions and position the PINK1-dependent pathway as an important regulator of MuSC mitochondrial properties and fate decisions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.003 | 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".