Pericytes express markers of cellular proliferation without expansion of the pool in response to exercise-induced skeletal muscle damage
Bibliographic record
Abstract
Muscle-resident stromal cells, known as pericytes, have been shown to support muscle repair and/or regeneration. However, the extent to which pericytes respond during skeletal muscle repair in humans remains relatively unknown. The purpose of this study was to evaluate the pericyte response following damage-inducing eccentric muscle contractions. Healthy, young men (21.5 ± 0.5 years, n = 22), performed maximal muscle lengthening contractions via an isokinetic dynamometer. Muscle biopsies from the vastus lateralis were taken at baseline (Pre) and, 6 h-, 24 h-, 72 h-, 96 h following exercise-induced damage. Muscle-resident NG2+ pericyte content remained unchanged over time (p > 0.05), but the number of pericytes actively proliferating (Ki67+/NG2+) was significantly (p < 0.05) elevated 24 h following damage. NG2 protein and associated mRNA expression of CSPG4 were significantly (p < 0.05) increased 24 h post-exercise. mRNA expression of signaling factors, related to pericyte mobility and activation including TNFa, CD248 and CXCR4 were significantly upregulated at 24 h post-exercise (p < 0.05). Taken together, muscle injury promotes the upregulation of nuclear proteins associated with proliferation of NG2+ pericytes and increases pericyte associated mRNA expression.
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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".