Novel Fibrogenic Pathways Are Activated in Response to Endothelial Apoptosis: Implications in the Pathophysiology of Systemic Sclerosis
Bibliographic record
Abstract
Apoptosis of endothelial cells (EC) is appreciated as a primary pathogenic event in systemic sclerosis. Yet, how apoptosis of EC leads to fibrosis remains to be determined. We report that apoptosis of EC triggers the release of novel fibrogenic mediators. Medium conditioned by apoptotic EC (SSC) was found to inhibit apoptosis of fibroblasts, whereas medium conditioned by EC in which apoptosis was blocked (with either pan-caspase inhibition or Bcl-x(L) overexpression) did not. PI3K was activated in fibroblasts exposed to SSC. This was associated with downstream repression of Bim-EL and long-term up-regulation of Bcl-x(L) protein levels. RNA interference for Bim-EL in fibroblasts blocked apoptosis. SSC also induced PI3K-dependent myofibroblast differentiation with expression of alpha-smooth muscle actin, formation of stress fibers, and production of collagen I. A C-terminal fragment of the domain V of perlecan was identified as one of the fibrogenic mediators present in SSC. A synthetic peptide containing an EGF motif present on the perlecan fragment and chondroitin 4-sulfate, a glycosaminoglycan anchored on the domain V of perlecan, induced PI3K-dependent resistance to apoptosis in fibroblasts and myofibroblast differentiation. Human fibroblasts derived from sclerodermic skin lesions were more sensitive to the antiapoptotic activities of the synthetic peptide and chondroitin 4-sulfate than fibroblasts derived from normal controls. Hence, we propose that a chronic increase in endothelial apoptosis and/or increased sensitivity of fibroblasts to mediators produced by apoptotic EC could form the basis of a fibrotic response characterized by sustained induction of an antiapoptotic phenotype in fibroblasts and persistent myofibroblast differentiation.
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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".