Repetitive mechanical stretching modulates transforming growth factor-β induced collagen synthesis and apoptosis in human patellar tendon fibroblasts
Bibliographic record
Abstract
The cellular and molecular mechanisms underlying the development of tendinopathy are not clear, but inflammatory mediators produced by tendon fibroblasts in response to repetitive mechanical loading may be an important factor for this illness. In this study, we explored the effect of cyclic mechanical stretching on collagen synthesis and apoptosis of human patellar tendon fibroblasts (HPTFs). The role of a candidate inflammatory mediator, transforming growth factor-β1 (TGFβ1), which we identified in a cytokine antibody array, in collagen synthesis and apoptosis during repetitive mechanical stretching was also investigated. Our results showed that there was a significant increase in collagen type I synthesis at 4% and 8% stretch. Significantly, enhancement of apoptosis may account for the observed decrease in fibroblast numbers after 8% stretching. Furthermore, the exogenous addition of an anti-TGFβ1 antibody or gene silencing by si-TGFβ1 eliminated the increase in collagen type I production and activities of caspases during apoptosis under cyclic uniaxial stretching conditions. These results suggest that TGFβ1 may take part in the increase of cellular production of collagen type I and apoptosis during the development of tendinopathy. Furthermore, caspase 8 mediates activation of caspase 3 and poly ADP-ribose polymerase (PARP) cleavage during TGFβ1-induced apoptosis in stretching HPTFs.
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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".