Granzyme B is important in the progression of atherosclerosis
Bibliographic record
Abstract
Granzyme B (GrB) is a serine protease expressed in certain T‐cells, NK cells, mast cells and macrophages. We have shown GrB expression in human atherosclerotic plaques and its levels correspond to disease severity. Hypothesis: During chronic hyperlipidemia and inflammation, GrB contributes to elastin degradation, medial thinning and reduced elasticity. Methods: To study the role of GrB in a chronic inflammatory, hyperlipidemic environment, ApoE−/− x GrB−/− double knockout (ApoE/GrB‐DKO) mice were created, fed a high fat diet for 30 wks and sacrificed. Tissues were stained with H&E, ORO and Movat's pentachrome. GrB co‐localization to elastin was assessed using confocal microscopy. Results: ApoE−/− mice developed xanthomatosis and atherosclerotic lesions by 30 weeks. The absence of the GrB gene in the ApoE/GrB‐DKO mice abolished cutaneous xanthomatosis in addition to both the frequency and size of atherosclerotic lesions. The absence of GrB was associated with a marked reduction of elastin degradation in both the skin and blood vessels. Using confocal microscopy, we observed GrB strongly co‐localized to the shoulder regions of plaques in addition to the medial elastin fibres. Conclusion: GrB plays a key role in atherosclerotic plaque formation. Lipid accumulation on elastin fibres promotes the recruitment of GrB resulting in a slow, chronic degradation of elastin.
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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 | 0.001 | 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".