Abstract 132: Simulated Intraplaque Hemorrhage Stimulates Plaque Progression in an Animal Model
Bibliographic record
Abstract
Intraplaque hemorrhage (IPH) is a feature of advanced plaques and a risk factor for clinical events. Several studies have demonstrated a link between carotid IPH and subsequent cerebrovascular events. Deposited RBCs contribute ingredients likely to promote plaque instability. In this study, a catheter-based approach was used for intramural injection of RBCs into atherosclerotic plaques. We explored the hypothesis that an animal model of atherosclerosis demonstrates increased macrophage infiltration and neovascularization in plaques injected with RBCs. Rabbits (n=4) were administered high cholesterol diet starting 2 weeks prior to endothelial denudation. Five weeks after denudation, a microinfusion catheter with a balloon-actuated microneedle delivered 70-100 μl of RBC and iodinated contrast mixture at multiple sites along the aorta. X-ray fluoroscopy and CT identified plaque injection sites and aortas were harvested for histopathology 5 weeks later. Only sections from plaque injection sites (n=14) were positive for Perl’s iron stain. In the 3 aortas analyzed with immunohistochemistry (1 excluded due to plaque variability), plaque macrophage area proportion was significantly higher in plaque injection sites vs. non-injected vessel sections. Increase in plaque neovessel density was not significant. In conclusion, intraplaque deposition of RBCs in the atherosclerotic rabbit aorta increases measures of plaque instability. Micrographs show Perl’s iron (a), macrophage (b), and neovessel (c) staining in an RBC-injected plaque. Scale bars represent 250 μm. Mean macrophage proportion and microvessel density and associated SEM are shown in bar graphs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".