Quantitative Analysis and Characterization of Atherosclerotic Lesions in the Murine Aortic Sinus
Bibliographic record
Abstract
Atherosclerosis is a disease of the large arteries and a major underlying cause of myocardial infarction and stroke. Several different mouse models have been developed to facilitate the study of the molecular and cellular pathophysiology of this disease. In this manuscript we describe specific techniques for the quantification and characterization of atherosclerotic lesions in the murine aortic sinus and ascending aorta. The advantage of this procedure is that it provides an accurate measurement of the cross-sectional area and total volume of the lesion, which can be used to compare atherosclerotic progression across different treatment groups. This is possible through the use of the valve leaflets as an anatomical landmark, together with careful adjustment of the sectioning angle. We also describe basic staining methods that can be used to begin to characterize atherosclerotic progression. These can be further modified to investigate antigens of specific interest to the researcher. The described techniques are generally applicable to a wide variety of existing and newly created dietary and genetically-induced models of atherogenesis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".