Preimplant ultrastructure and calcification tendency of various biological aortic valves.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: In recent years a number of fixation and anti-calcification methods have been developed, but little is yet known about the calcification process of biological valves. The aims of this study were to: (i) perform a systematic ultrastructural investigation on various biological valves; and (ii) determine the extent of calcification of these valves in a subcutaneous rat model. METHODS: The following porcine aortic prostheses were investigated: Toronto-SPV, Intact, Freestyle, Mosaic and Hancock-II. Samples taken from the valve leaflets, and in the case of the Freestyle and Toronto-SPV valves also from the aortic wall, were examined ultrastructurally using scanning and transmission electron microscopy. Other samples were implanted subcutaneously in Wistar rats for 12 weeks. The calcium content of the samples was measured using atomic absorption spectrophotometry. RESULTS: All valves examined showed a considerable loss of the endothelial cover. Significant changes in valve ultrastructure were also detected. With regard to calcium content, two valve groups could be distinguished (p <0.05): (i) those with high calcium content, e.g. Toronto-SPV and Intact (>40 mg/g dry tissue); and (ii) those with low calcium content, e.g. Mosaic, Freestyle and Hancock-II (<5 mg/g). CONCLUSION: Fixation methods have pronounced effects on the ultrastructural integrity of bioprostheses. The degenerative calcification of bioprostheses can be effectively inhibited by glutaraldehyde-free fixation and anti-calcification treatments.
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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".