Tenocyte responses to mechanical loading in vivo: A role for local insulin‐like growth factor 1 signaling in early tendinosis in rats
Bibliographic record
Abstract
OBJECTIVE: To investigate tenocyte regulatory events during the development of overuse supraspinatus tendinosis in rats. METHODS: Supraspinatus tendinosis was induced by running rats downhill at 1 km/hour for 1 hour a day. Tendons were harvested at 4, 8, 12, and 16 weeks and processed for brightfield, polarized light, or transmission electron microscopy. The development of tendinosis was assessed semiquantitatively using a modified Bonar histopathologic scale. Apoptosis and proliferation were examined using antibodies against fragmented DNA or proliferating cell nuclear antigen, respectively. Insulin-like growth factor 1 (IGF-1) expression was determined by computer-assisted quantification of immunohistochemical reaction. Local IGF-1 signaling was probed using antibodies to phosphorylated insulin receptor substrate 1 (IRS-1) and ERK-1/2. RESULTS: Tendinosis was present after 12 weeks of downhill running and was characterized by tenocyte rounding and proliferation as well as by glycosaminoglycan accumulation and collagen fragmentation. The proliferation index was elevated in CD90+ tenocytes in association with tendinosis and correlated with increased local IGF-1 expression by tenocytes and phosphorylation of IRS-1 and ERK-1/2. Both apoptosis and cellular inflammation were absent at all time points. CONCLUSION: In this animal model, early tendinosis was associated with local stimulation of tenocytes rather than with extrinsic inflammation or apoptosis. Our data suggest a role for IGF-1 in the load-induced tenocyte responses during the pathogenesis of overuse tendon disorders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".