Discoidin Domain Receptor-1 Regulates Calcific Extracellular Vesicle Release in Vascular Smooth Muscle Cell Fibrocalcific Response via Transforming Growth Factor-β Signaling
Bibliographic record
Abstract
OBJECTIVE: Collagen accumulation and calcification are major determinants of atherosclerotic plaque stability. Extracellular vesicle (EV)-derived microcalcifications in the collagen-poor fibrous cap may promote plaque rupture. In this study, we hypothesize that the collagen receptor discoidin domain receptor-1 (DDR-1) regulates collagen deposition and release of calcifying EVs by vascular smooth muscle cells (SMCs) through the transforming growth factor-β (TGF-β) pathway. APPROACH AND RESULTS: SMCs from the carotid arteries of DDR-1(-/-) mice and wild-type littermates (n=5-10 per group) were cultured in normal or calcifying media. At days 14 and 21, SMCs were harvested and EVs isolated for analysis. Compared with wild-type, DDR-1(-/-) SMCs exhibited a 4-fold increase in EV release (P<0.001) with concomitantly elevated alkaline phosphatase activity (P<0.0001) as a hallmark of EV calcifying potential. The DDR-1(-/-) phenotype was characterized by increased mineralization (Alizarin Red S and Osteosense, P<0.001 and P=0.002, respectively) and amorphous collagen deposition (P<0.001). We further identified a novel link between DDR-1 and the TGF-β pathway previously implicated in both fibrotic and calcific responses. An increase in TGF-β1 release by DDR-1(-/-) SMCs in calcifying media (P<0.001) stimulated p38 phosphorylation (P=0.02) and suppressed activation of Smad3. Inhibition of either TGF-β receptor-I or phospho-p38 reversed the fibrocalcific DDR-1(-/-) phenotype, corroborating a causal relationship between DDR-1 and TGF-β in EV-mediated vascular calcification. CONCLUSIONS: DDR-1 interacts with the TGF-β pathway to restrict calcifying EV-mediated mineralization and fibrosis by SMCs. We therefore establish a novel mechanism of cell-matrix homeostasis in atherosclerotic plaque formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".