Calreticulin Regulates Neointima Formation and Collagen Deposition following Carotid Artery Ligation
Bibliographic record
Abstract
BACKGROUND/AIMS: The endoplasmic reticulum (ER) stress protein, calreticulin (CRT), is required for the production of TGF-β-stimulated extracellular matrix (ECM) by fibroblasts. Since TGF-β regulates vascular fibroproliferative responses and collagen deposition, we investigated the effects of CRT knockdown on vascular smooth-muscle cell (VSMC) fibroproliferative responses and collagen deposition. METHODS: Using a carotid artery ligation model of vascular injury, Cre-recombinase-IRES-GFP plasmid was delivered with microbubbles (MB) to CRT-floxed mice using ultrasound (US) to specifically reduce CRT expression in the carotid artery. RESULTS: In vitro, Cre-recombinase-mediated CRT knockdown in isolated, floxed VSMCs decreased the CRT transcript and protein, and attenuated the induction of collagen I protein in response to TGF-β. TGF-β stimulation of collagen I was partly blocked by the NFAT inhibitor 11R-VIVIT. Following carotid artery ligation, CRT staining was upregulated with enhanced expression in the neointima 14-21 days after injury. Furthermore, Cre-recombinase-IRES-GFP plasmid delivered by targeted US reduced CRT expression in the neointima of CRT-floxed mice and led to a significant reduction in neointima formation and collagen deposition. The neointimal cell number was also reduced in mice, with a local, tissue-specific knockdown of CRT. CONCLUSIONS: This work establishes a novel role for CRT in mediating VSMC responses to injury through the regulation of collagen deposition and neointima formation.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".