Oxidative low-density lipoprotein and shear induced calcification within a calcific aortic valve disease-on-a-chip platform
Bibliographic record
Abstract
Background Early-stage calcific aortic valve disease (CAVD) has been characterized by the infiltration of immune cells, reorganization of the extracellular matrix, and the deposition and oxidation of low-density lipoproteins (oxLDL). Worldwide studies have revealed that aortic valve disease accounts for up to 43% of patients exhibiting heart disease. Methods We utilized a CAVD-on-a-chip platform of the aortic valve fibrosa to assess the hypothesis that culture calcification will increase with endothelial cell presence, increased oxLDL concentration (25 μg/ml or 50 μg/ml), and shear stress (20 dyne/cm 2 ). CAVD chips consisted of collagen I hydrogels with porcine aortic valve interstitial cells embedded and porcine aortic valve endothelial cells seeded on top of the matrix for up to two days. Results Here, we demonstrate that the presence of endothelial cells and shear stress drives alkaline phosphatase activity, sulfated glycosaminoglycan production, and the formation of mono-, di-, and octa- calcium phosphates, and hydroxyapatites. Two-day dynamic cultures showed 3D cell-oxLDL interactions, leading to extracellular matrix remodeling and endothelial dysfunction. Discussion Given that CAVD has no targeted intervention, continued evolution of this CAVD-on-a-chip model sheds light on mechanisms in disease onset and can lead to significant contributions in preclinical drug development.
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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 | 0.000 |
| 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".