Hepatocyte growth factor (HGF) and the satellite cell response following muscle lengthening contractions in humans
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Bibliographic record
Abstract
The time-courses of satellite cell (SC) activation and protein expression of hepatocyte growth factor (HGF), HGF activator (HGFA), HGFA inhibitor-1 (HAI-1), and HGFA inhibitor-2 (HAI-2) in human skeletal muscle, as well as serum HGF following a single bout of muscle lengthening contractions, were determined. Eight recreationally active participants were recruited for the study. Subjects performed 300 lengthening contractions involving the quadriceps femoris muscles of a single leg at a fixed velocity of 180 degrees/s. Percutaneous muscle biopsies were taken before (PRE) and at 4 h (T4), 24 h (T24), 72 h (T72), and 120 h (T120) following the exercise. The protocol resulted in an increase in the number of SCs [neural cell adhesion molecule (NCAM)-labeled cells] expressed relative to total myonuclei, at T24, compared with both PRE and T4 (P<0.05), and peaked at T72 (approximately 80% increase vs. PRE, P<0.05). HGF protein increased significantly in serum from baseline (PRE) to T4 (P<0.05). Active HGF protein was detected in skeletal muscle at rest [14.4+/-1.3 average integrated density value (IDV)/actin average IDV] and tended to increase at early time-points (P=0.12). HGFA protein increased significantly from PRE to T24 (P<0.05). HAI-1 protein increased significantly from PRE to T24 (P<0.05). HAI-2 (32 kDa) increased significantly from baseline (PRE) by T24 (P<0.05), and also by T72 and T120 (P<0.05). We conclude that a single bout of lengthening muscle contractions is sufficient to activate SCs, which may involve both a local and systemic HGF response to contraction-induced injury.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it