Integrins αvβ5 and αvβ3 promote latent TGF-β1 activation by human cardiac fibroblast contraction
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Bibliographic record
Abstract
AIMS: Pathological tissue remodelling by myofibroblast contraction is a hallmark of cardiac fibrosis. Myofibroblasts differentiate from cardiac fibroblasts under the action of transforming growth factor-β1 (TGF-β1), which is secreted into the extracellular matrix as a large latent complex. Integrin-mediated traction forces activate TGF-β1 by inducing a conformational change in the latent complex. The mesenchymal integrins αvβ5 and αvβ3 are expressed in the heart, but their role in the activation of TGF-β1 remains elusive. Here, we test whether targeting αvβ5 and αvβ3 integrins reduces latent TGF-β1 activation by cardiac fibroblasts with the goal to prevent the formation of α-smooth muscle actin (α-SMA)-expressing cardiac myofibroblasts and their contribution to fibrosis. METHODS AND RESULTS: Using a porcine model of induced right ventricular fibrosis and pro-fibrotic culture conditions, we show that integrins αvβ5 and αvβ3 are up-regulated in myofibroblast-enriched fibrotic lesions and differentiated cultured human cardiac myofibroblasts. Both integrins autonomously contribute to latent TGF-β1 activation and myofibroblast differentiation, as demonstrated by function-blocking peptides and antibodies. Acute blocking of both integrins leads to significantly reduced TGF-β1 activation by cardiac fibroblast contraction and loss of α-SMA expression, which is restored by adding active TGF-β1. Manipulating integrin protein levels in overexpression and shRNA experiments reveals that both integrins can compensate for each other with respect to TGF-β1 activation and induction of α-SMA expression. CONCLUSIONS: Integrins αvβ5 and αvβ3 both control myofibroblast differentiation by activating latent TGF-β1. Pharmacological targeting of mesenchymal integrins is a possible strategy to selectively block TGF-β1 activation by cardiac myofibroblasts and progression of fibrosis in the heart.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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