Scinderin promotes fusion of electron transport chain dysfunctional muscle stem cells with myofibers
Bibliographic record
Abstract
Muscle stem cells (MuSCs) experience age-associated declines in number and function, accompanied by mitochondrial electron transport chain (ETC) dysfunction and increased reactive oxygen species (ROS). The source of these changes, and how MuSCs respond to mitochondrial dysfunction, is unknown. We report here that in response to mitochondrial ROS, murine MuSCs directly fuse with neighboring myofibers; this phenomenon removes ETC-dysfunctional MuSCs from the stem cell compartment. MuSC-myofiber fusion is dependent on the induction of Scinderin, which promotes formation of actin-dependent protrusions required for membrane fusion. During aging, we find that the declining MuSC population accumulates mutations in the mitochondrial genome, but selects against dysfunctional variants. In the absence of clearance by Scinderin, the decline in MuSC numbers during aging is repressed; however, ETC-dysfunctional MuSCs are retained and can regenerate dysfunctional myofibers. We propose a model in which ETC-dysfunctional MuSCs are removed from the stem cell compartment by fusing with differentiated tissue.
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 | 0.000 | 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) | 0.001 | 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".