Impaired muscle stem cell function and abnormal myogenesis in acquired myopathies
Bibliographic record
Abstract
Skeletal muscle possesses a high plasticity and a remarkable regenerative capacity that relies mainly on muscle stem cells (MuSCs). Molecular and cellular components of the MuSC niche, such as immune cells, play key roles to coordinate MuSC function and to orchestrate muscle regeneration. An abnormal infiltration of immune cells and/or imbalance of pro- and anti-inflammatory cytokines could lead to MuSC dysfunctions that could have long lasting effects on muscle function. Different genetic variants were shown to cause muscular dystrophies that intrinsically compromise MuSC function and/or disturb their microenvironment leading to impaired muscle regeneration that contributes to disease progression. Alternatively, many acquired myopathies caused by comorbidities (e.g., cardiopulmonary or kidney diseases), chronic inflammation/infection, or side effects of different drugs can also perturb MuSC function and their microenvironment. The goal of this review is to comprehensively summarize the current knowledge on acquired myopathies and their impact on MuSC function. We further describe potential therapeutic strategies to restore MuSC regenerative capacity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".