Heat shock protein 27 attenuates neointima formation and accelerates reendothelialization after arterial injury and stent implantation: importance of vascular endothelial growth factor up‐regulation
Bibliographic record
Abstract
Elevated serum heat shock protein 27 (HSP27) levels are atheroprotective; however, the role of HSP27 after arterial injury is unknown. Human endothelial progenitor cells (EPCs) were treated with recombinant (r)HSP27 (50 μg/ml) or its inactive C1 terminus, and gene expression was characterized before functional studies were performed in vitro and in vivo. Vascular endothelial growth factor (VEGF) was markedly up‐regulated by rHSP27 (10‐ and 6‐fold increases in mRNA and secretion, respectively). Pretreatment of EPCs with rHSP27 resulted in a 60% reduction in reendothelialization (RE) time in a scratch assay, an effect that was blocked with VEGF‐neutralizing antibodies. Mice overexpressing HSP27 demonstrated more robust mobilization of EPCs at the time of arterial injury, as well as a 67% increase in RE and a 45% reduction in neointima (NI) formation at 28 d. Implantation of rHSP27‐eluting stents in rabbit carotid arteries resulted in a marked improvement in RE at 7 and 28 d and transient attenuation of NI formation by 42% at 7 d. Hence, extracellular HSP27 up‐regulated VEGF and improved EPC migration in vitro. Augmented systemic or local levels of HSP27 markedly improved RE after vascular injury, an effect that is of particular relevance to the safety profile of vascular stents.—Ma, X., Hibbert, B., McNulty, M., Hu, T., Zhao, X., Ramirez, F. D., Simard, T., de Belleroche, J. S., O'Brien, E. R. Heat shock protein 27 attenuates neointima formation and accelerates reendothelialization after arterial injury and stent implantation: importance of vascular endothelial growth factor up‐regulation. FASEB J. 28, 594–602 (2014). www.fasebj.org
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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".