DDR1: a novel regulator of intimal calcification
Bibliographic record
Abstract
Intimal calcification is a serious complication of advanced atherosclerotic disease. Low density lipoprotein receptor‐deficient mice (Ldlr −/− ) fed a high fat diet develop complicated atherosclerotic lesions. Here we report that Ldlr −/− mice develop foci of intimal calcification in the aortic arch, which are positive for Alizarin Red S (AR) and Von Kossa (VK), two histological stains for mineralized tissues. Cells within these foci are surrounded by a type II collagen‐rich matrix and express a chondrocyte‐specific transcription factor, Sox‐9. Atherosclerotic lesions are rich in collagens, which have been shown to promote smooth muscle cell‐mediated calcification. Thus, we hypothesized a role for the discoidin domain receptor 1 (DDR1), a collagen receptor, in intimal calcification. Male mice with a combined deficiency in LDLR and DDR1 (Ldlr −/− ;Ddr1 −/− ) and controls (Ldlr −/− ;Ddr1 +/+ ) were fed a high fat diet for 12 weeks. DDR1‐deficiency attenuated the incidence of intimal calcification, measured by positive staining for AR and VK. Aortic arch calcium extraction confirmed a reduction in the extent of calcification in the Ldlr −/− ;Ddr1 −/− mice compared with control mice (45 ± 22 vs 123 ± 52 μmol/g dry weight). This study demonstrates regions of calcification within the intimal lesions of Ldlr −/− mice fed an atherogenic diet and provides novel evidence of a role for DDR1 in this process.
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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) | 0.001 | 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) | 0.001 | 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".