Abstract 5809: Recombinant HSP27 Therapy Reduces Serum Cholesterol Levels and Experimental Atherogenesis
Bibliographic record
Abstract
Introduction: Recently we demonstrated that Heat Shock Protein 27 (HSP27) is a biomarker of atherosclerosis and apoE −/− mice that over-express HSP27 show a marked attenuation of aortic lesion size compared to apoE −/− mice (ATVB 20005; Circ Res 2008). Moreover, serum HSP27 levels are inversely related to atherosclerotic burden, estrogens mediate the release of HSP27 from cells and extracellular HSP27 binds to Scavenger Receptor-A where competitively inhibits acLDL uptake. Purpose/Methods: The goal of this study was to determine if recombinant HSP27 (rHSP27) administered to apoE −/− mice can attenuate atherogenesis. rHSP27 was produced in E.coli; (endotoxin concentration <8EU/mg). In vitro aggregation and refolding assays revealed appropriate rHSP27 function. In vivo a series of subcutaneous dosing schedules were explored. Herein we report the results obtained for ApoE −/− mice maintained on a high fat diet and randomized to rHSP27 (100 μ g) vs. phosphate buffered saline (PBS) twice a day for 3 weeks. Results: All mice survived the study period without changes in body weight or adverse events. Total serum cholesterol levels were approximately 40% lower in rHSP27 treated mice. The aortic lesion areas were reduced by approximately 30% and 25% for en face and sinus cross-sectional analyses. In rHSP27 treated mice the abundance of aortic sinus lesion macrophages and apoptotic macrophages were reduced by approximately 45% and 80%, respectively. Conclusions: rHSP27 is a promising new therapeutic modality for reducing serum cholesterol levels as well as atherogenesis. Moreover, the lesions that form in mice treated with rHSP27 contain fewer inflammatory cells and undergo less apoptosis. Studies are ongoing to optimize the dose, schedule and form of rHSP27 that might be used not only for the prevention of atherogenesis but also regression of existing lesions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".