Evolving Roles of Muscle-Resident Fibro-Adipogenic Progenitors in Health, Regeneration, Neuromuscular Disorders, and Aging
Bibliographic record
Abstract
Normal skeletal muscle functions are affected following trauma, chronic diseases, inherited neuromuscular disorders, aging, and cachexia, hampering the daily activities and quality of life of the affected patients. The maladaptive accumulation of fibrous intramuscular connective tissue and fat are hallmarks of multiple pathologies where chronic damage and inflammation are not resolved, leading to progressive muscle replacement and tissue degeneration. Muscle-resident fibro-adipogenic progenitors are adaptable stromal cells with multilineage potential. They are required for muscle homeostasis, neuromuscular integrity, and tissue regeneration. Fibro-adipogenic progenitors actively regulate and shape the extracellular matrix and exert immunomodulatory functions via cross-talk with multiple other residents and non-resident muscle cells. Remarkably, cumulative evidence shows that a significant proportion of activated fibroblasts, adipocytes, and bone-cartilage cells, found after muscle trauma and disease, descend from these enigmatic interstitial progenitors. Despite the profound impact of muscle disease on human health, the fibrous, fatty, and ectopic bone tissues' origins are poorly understood. Here, we review the current knowledge of fibro-adipogenic progenitor function on muscle homeostatic integrity, regeneration, repair, and aging. We also discuss how scar-forming pathologies and disorders lead to dysregulations in their behavior and plasticity and how these stromal cells can control the onset and severity of muscle loss in disease. We finally explore the rationale of improving muscle regeneration by understanding and modulating fibro-adipogenic progenitors' fate and behavior.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".