Acellular porcine and kangaroo aortic valve scaffolds show more intense immune-mediated calcification than cross-linked Toronto SPV(R) valves in the sheep model
Bibliographic record
Abstract
AIM OF THE STUDY: A major limitation of currently available bioprosthetic valves is their propensity to calcify. At present, one approach in tissue-engineering, uses decellularized, xenogenic scaffolds that are implanted, with the expectation of complete matrix repopulation in vivo. Whether or not such a decellularized matrix will be sufficiently endowed to prevent calcification is unknown. MATERIALS AND METHODS: This study examines the calcification potential of xenogenic biological scaffolds from two species, namely pigs (n=3) and kangaroos (n=3) in the sheep model and compared them to a commercially available glutaraldehyde treated porcine bioprosthetic valve (Toronto SPV) (n=3). RESULTS: Valves and matrices were explanted after 120 days. Histologically (H&E and Von Kossa stain) more calcium was found in the acellular matrices. The mean calcium content (mg/g-dw) of the Toronto SPV valve leaflets was 2.63 mg/g-dw compared to 43.81 mg/g-dw (P=0.12) in kangaroo and 105.08 mg/g-dw (P=0.004) in porcine matrices. On electron microscopy calcific deposits were located between as well as in close association with the collagen fibers in all tissue. In contrast to the cross-linked gluteraldehyde fixed bioprostheses both matrices showed strong immune IgG reaction. CONCLUSION: Toronto SPV valves calcified significantly less than the tested biological matrices irrespective of species of origin. Surprisingly, xenogenic decelullarized scaffolds are inherently prone to calcification due to a strong immunogenicity.
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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".