Verteporfin inhibits the persistent fibrotic phenotype of lesional scleroderma dermal fibroblasts
Bibliographic record
Abstract
Fibrosis is perpetuated by an autocrine, pro-adhesive signaling loop maintained by the synthetic and contractile abilities of myofibroblasts and the stiff, highly-crosslinked extracellular matrix. Transcriptional complexes that are exquisitely responsive to mechanotransduction include the co-activator YAP1, which regulates the expression of members of the CCN family of matricellular proteins such as CCN2 and CCN1. Although selective YAP1 inhibitors exist, the effect of these inhibitors on profibrotic gene expression in fibroblasts is largely unknown, and is the subject of our current study. Herein, we use genome-wide expression profiling, real-time polymerase chain reaction and Western blot analyses, cell migration and collagen gel contraction assays to assess the ability of a selective YAP inhibitor verteporfin (VP) to block fibrogenic activities in dermal fibroblasts from healthy individual human controls and those from isolated from fibrotic lesions of patients with diffuse cutaneous systemic sclerosis (dcSSc). In control fibroblasts, VP selectively reduced expression of fibrogenic genes and also blocked the ability of TGFbeta to induce actin stress fibers in dermal fibroblasts. VP also reduced the persistent profibrotic phenotype of dermal fibroblasts cultured from fibrotic lesions of patients with dcSSc. Our results are consistent with the notion that, in the future, YAP1 inhibitors may represent a novel, valuable method of treating fibrosis as seen in dcSSc.
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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".