Reduced atherosclerotic plaque burden in mice with targeted deletion of the discoidin domain receptor 1 (DDR1) gene
Bibliographic record
Abstract
Vascular smooth muscle cell (SMC) migration, proliferation and matrix metalloproteinase (MMP) expression are critical events in atherosclerotic plaque development and rupture. The discoidin domain receptor 1 ( DDR1 ), a novel collagen receptor tyrosine kinase, is expressed by SMCs and controls the expression of collagen and multiple MMPs. We have previously shown that DDR1 deficient ( DDR1 −/− ) mice develop less intimal thickening after wire injury secondary to decreased MMP‐2 and −9 activity and impaired SMC adhesion, proliferation and migration on collagens I and VIII. To assess the involvement of the DDR1 gene in atherogenesis, DDR1 −/− mice were crossed with LDL receptor deficient mice ( LDLR −/− ) to generate mice with a single deficiency in LDLR ( DDR1 +/+ ;LDLR −/− ) or with a combined deficiency in DDR1 and LDLR ( DDR1 −/− ;LDLR −/− ). Mice were fed an atherogenic diet (40% Kcal fat, 1.25% cholesterol) for 12, 24 or 48 weeks. Atherosclerotic plaque burden in the descending aorta was quantified by en face staining with Oil Red O and plaque area in the aortic root was measured using digital histomorphometry. Compared with DDR1 +/+ ;LDLR −/− mice, Oil Red O staining in the descending aortae of DDR1 −/− ;LDLR −/− mice was significantly reduced at 12 weeks (9.13% vs 2.94%, p<0.05), 24 weeks (33.6% vs 13.5%, p<0.05) and 48 weeks (70.4% vs 42.5%, p<0.05), however plaque area in the aortic root was unaffected at these timepoints. There were no differences in body weight or fasting plasma cholesterol and triglycerides between groups at 12 and 24 weeks. This study is the first to demonstrate the effect of DDR1 deficiency on 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".