Calcification of human valve interstitial cells is dependent on alkaline phosphatase activity.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: The calcification of heart valves is associated with valve degeneration and failure, but the mechanisms involved are poorly understood. The presence of lamellar bone has been demonstrated in calcified aortic valves. Since osseous calcification is closely associated with alkaline phosphatase (ALP) activity, it was hypothesized that ALP activity might be implicated in the calcification of isolated leaflet interstitial cells (ICs). METHODS: Human valve leaflet ICs were isolated from transplant-explanted hearts at the time of transplantation (n = 12). RESULTS: Isolated leaflet ICs expressed the fibroblast-specific antigen (100% of cells) and smooth muscle (SM) alpha-actin (70-80% of cells), but osteoblastic markers were not expressed. Cultured ICs did not calcify spontaneously, however when the growth medium was supplemented with beta-glycerophosphate (an organic phosphate) it induced the formation of calcified nodules that expressed osteonectin and ALP, but not SM alpha-actin. Beta-glycerophosphate-induced calcification of ICs showed a time-dependent effect on the calcium content of treated cells over a 14-day period. ALP activity was considerably increased in beta-glycerophosphate-treated ICs, and this correlated with the calcium content (r = 0.5: p = 0.01). Levamisol (an ALP inhibitor) inhibited the beta-glycerophosphate-induced calcification process, as well as the expression of osteoblastic differentiation markers. CONCLUSION: Isolated and cultured leaflet ICs did not calcify spontaneously, though organic phosphate induced the formation of calcified nodules that expressed osteoblastic markers. The calcification of isolated ICs was seen to be dependent on ALP activity.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".