Angiopoietin‐like 4 promotes angiogenesis in the tendon and is increased in cyclically loaded tendon fibroblasts
Bibliographic record
Abstract
KEY POINTS: Angiopoietin-like 4 (ANGPTL4) modulates tendon neovascularization. Cyclic loading stimulates the activity of transforming growth factor-β and hypoxia-inducible factor 1α and thereby increases the expression and release of ANGPTL4 from human tendon cells. Targeting ANGPTL4 and its regulatory pathways is a potential avenue for regulating tendon vascularization to improve tendon healing or adaptation. ABSTRACT: The mechanisms that regulate angiogenic activity in injured or mechanically loaded tendons are poorly understood. The present study examined the potential role of angiopoietin-like 4 (ANGPTL4) in the angiogenic response of tendons subjected to repetitive mechanical loading or injury. Cyclic stretching of human tendon fibroblasts stimulated the expression and release of ANGPTL4 protein via transforming growth factor-β (TGF-β) and hypoxia-inducible factor 1α (HIF-1α) signalling, and the released ANGPTL4 was pro-angiogenic. Angiogenic activity was increased following ANGPTL4 injection into mouse patellar tendons, whereas the patellar tendons of ANGPTL4 knockout mice displayed reduced angiogenesis following injury. In human rotator cuff tendons, the expression of ANGPTL4 was correlated with the density of tendon endothelial cells. To our knowledge, this is the first study characterizing a role of ANGPTL4 in the tendon. ANGPTL4 may assist in the regulation of vascularity in the injured or mechanically loaded tendon. TGF-β and HIF-1α comprise two signalling pathways that modulate the expression of ANGPTL4 by mechanically stimulated tendon fibroblasts and, in the future, these could be manipulated to influence tendon healing or adaptation.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".