Impaired ECM Remodeling and Macrophage Activity Define Necrosis and Regeneration Following Damage in Aged Skeletal Muscle
Bibliographic record
Abstract
Regenerative capacity of skeletal muscle declines with age, the cause of which remains largely unknown. We investigated extracellular matrix (ECM) proteins and their regulators during early regeneration timepoints to define a link between aberrant ECM remodeling, and impaired aged muscle regeneration. The regeneration process was compared in young (three month old) and aged (18 month old) C56BL/6J mice at 3, 5, and 7 days following cardiotoxin-induced damage to the tibialis anterior muscle. Immunohistochemical analyses were performed to assess regenerative capacity, ECM remodeling, and the macrophage response in relation to plasminogen activator inhibitor-1 (PAI-1), matrix metalloproteinase-9 (MMP-9), and ECM protein expression. The regeneration process was impaired in aged muscle. Greater intracellular and extramyocellular PAI-1 expression was found in aged muscle. Collagen I was found to accumulate in necrotic regions, while macrophage infiltration was delayed in regenerating regions of aged muscle. Young muscle expressed higher levels of MMP-9 early in the regeneration process that primarily colocalized with macrophages, but this expression was reduced in aged muscle. Our results indicate that ECM remodeling is impaired at early time points following muscle damage, likely a result of elevated expression of the major inhibitor of ECM breakdown, PAI-1, and consequent suppression of the macrophage, MMP-9, and myogenic responses.
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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) | 0.000 | 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".