Association of N‐cadherin and beta‐catenin with activation of valve interstitial cells
Bibliographic record
Abstract
Background Valve interstitial cells (VICs), the most prevalent cells in the heart valve, become activated upon injury and disease. Cell‐cell adhesion proteins N‐cadherin and β‐catenin should be present in VICs and the latter may translocate to the nucleus upon disruption of cell‐cell contacts to regulate gene expression. We hypothesize that absence or disruption of cell‐cell contacts increases cytosolic β‐catenin and VIC activation. Methods Porcine VIC cultures were maintained in standard media in 10% fetal bovine serum for 7 to 10 days. Subconfluent, confluent, and wounded monolayers were fixed and stained with antibodies against β‐catenin and N‐cadherin, and α‐SMA to demonstrate VIC activation. Immunofluorescently stained VICs were viewed under a scanning confocal microscope. Results Comparing single, islands, confluent monolayers, and wound edge VICs, we found diffuse, stress fiber and diffuse, reduced, and stress fiber α‐SMA staining respectively. Single VICs and VICs that migrated into the wound showed N‐cadherin and β‐catenin staining in the cytoplasm and lamellapodia with some cells showing nuclear or perinuclear staining for β‐catenin. Cellular islands and confluent monolayers showed co‐localized staining of N‐cadherin and β‐catenin at cell‐cell contacts with weak diffuse cytoplasmic staining. Conclusion N‐cadherin and β‐catenin at cell‐cell contacts may regulate VIC activation. Supported by a grant from the Heart and Stroke Foundation of Ontario (grant NA6204).
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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) | 0.002 | 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".