P131 Cellular communication network factor (CCN3)-derived peptide BLR200 impairs bleomycin-induced lung fibrosis
Bibliographic record
Abstract
Abstract Background/Aims Scleroderma (systemic sclerosis; SSc) is an autoimmune connective tissue disease characterized by progressive fibrosis of the skin and internal organs. Lung fibrosis is a significant cause of mortality in SSc. Alterations in the expression of members of the cellular communication network (CCN) family of matricellular proteins are a hallmark of SSc. Of the CCN family, CCN2 is profibrotic and CCN3 is antifibrotic. We have developed a CCN3-derived peptide, BLR-200, as an anti-fibrotic therapeutic. BLR-200 has been given orphan drug designation by the US Food and Drug Administration. Whether BLR-200 has antifibrotic activity in a model of SSc lung fibrosis is unknown. Methods We use Western blot analysis to assess CCN3 expression levels in fibroblasts from healthy individuals and individuals with SSc. We use the bleomycin model (one dose of bleomycin, injected intratracheally at d0) of lung fibrosis (the industry-standard method of assessing experimental SSc lung fibrosis) to assess the effect of BLR-200 (subcutaneous injection, 3 times/week, over 21 days) on histological and molecular markers of lung fibrogenesis. Results CCN3 protein expression is reduced in SSc fibroblasts (N = 3, p < 0.05). Injection of BLR-200, compared to control scrambled peptide, significantly attenuated bleomycin-induced lung fibrosis, as visualized by histological (Ashcroft score of Trichrome-stained sections), protein (hydroxyproline collagen assay), lung weight, and mRNA (expression of CCN1, CCN2, COL1A2, ACTA2, PLOD2 as assessed by real-time polymerase chain reaction) analyses (all N = 5, all p < 0.05). Conclusion As BLR-200 reduces bleomycin-induced lung fibrosis, BLR-200 may represent a novel treatment for SSc lung fibrosis. Disclosure P. Chitturi: None. S. Xu: None. R.J. Stratton: None. B.L. Riser: Corporate appointments; CEO, BLR Bio, LLC. A. Leask: Grants/research support; Canadian Institutes of Health Research.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".