Hirulog-Like Peptide Reduces Balloon Catheter Injury Induced Neointima Formation in Rat Carotid Artery without Increase in Bleeding Tendency
Why this work is in the frame
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Bibliographic record
Abstract
Vascular restenosis is one of the major concerns for the management of coronary artery disease using therapeutic vascular procedures. Treatments with thrombin-specific inhibitors, hirudin or hirulog-1, reduced ischemic events in coronary artery disease patients. Early started and prolonged infusions of these thrombin inhibitors partially prevented balloon catheter injury induced restenosis or neointima formation in experimental animal models, but increased the bleeding tendency. Hirulog-like peptide (HLP) was rationally designed to enhance the inhibition of the binding of thrombin to its receptor with less interruption of coagulation activity in comparison to hirulog-1. A single infusion of HLP for 4 h started 0.5 h before balloon catheter injury reduced neointima formation by 36% in rat carotid artery compared to vehicle controls. Tail bleeding time and activated partial thromboplastin time during HLP infusion were not significantly different from vehicle controls, but were significantly shorter than during heparin or hirulog-1 infusion. HLP treatment attenuated the expression of platelet-derived growth factor in the neointima of injured arteries. HLP also inhibited thrombin-induced thymidine incorporation in cultured baboon aortic smooth muscle cells. The findings suggest that HLP may substantially inhibit balloon catheter injury induced neointima formation without noticeable increase in bleeding tendency in rats. The inhibition by HLP of the expression of platelet-derived growth factor and of the smooth muscle cell proliferation in the vascular wall potentially contributes to the preventive effect of the new thrombin inhibitor on injury-induced neointima formation in the vascular wall.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it