Alterations in collagen fiber crimp morphology with accelerated cyclic loading and transvalvular pressure fixation in porcine aortic valves
Bibliographic record
Abstract
It is known that changes in the collagen fiber orientation of porcine bioprosthetic heart valves (PBHV) occur with (i) cyclic loading and (ii) fixation pressure. These changes correlate to alterations in biaxial extensibility, as reported by Wells et al. (2002). It is hypothesized that the increased collagen fiber alignment detected by small angle light scattering in (i) and (ii) is either due to the gross fiber splay, or a decrease in the colllagen fiber crimp (i.e. increase in crimp period). To address this hypothesis, we examined the changes in collagen fiber crimp morphology of PBHVs fixed at 0, 1, 2, and 4 mmHg transvalvular pressure, as well as 0 and 4 mmHg fixed PBHV following 0, 1/spl times/10/sup 6/, 50/spl times/10/sup 6/, 200/spl times/10/sup 6/, and 500/spl times/10/sup 6/ in vitro accelerated test cycles. Fast Fourier transform analysis of polarized light micrographs was used to calculate the collagen fiber crimp period. As PBHVs were fixed at increasing pressures, it was found that the crimp period increases from 15.2 /spl mu/m at 0 mmHg to 21.4 /spl mu/m at 4 mmHg. Additionally, a 65% increase in crimp period was observed between 0-50/spl times/10/sup 6/ cycles in the 0 mmHg fixed valves, while only an 18% increase in the 4 mmHg fixed valves over the same cycle duration. We conclude that decreasing collagen crimp is a primary mechanism contributing to PBHV cyclic fatigue damage.
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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".