Preclinical evaluation of degradation kinetics and elemental mapping of first- and second-generation bioresorbable magnesium scaffolds
Bibliographic record
Abstract
AIMS: Because vascular restoration therapy using bioresorbable vascular scaffolds (BRS) remains an appealing concept to restore vasoreactivity, an understanding of biodegradation remains paramount during preclinical testing. We therefore aimed to investigate the qualitative and temporal course of degradation of magnesium alloy-based bioresorbable vascular scaffolds in juvenile swine. METHODS AND RESULTS: Qualitative characterisation of biodegradation was performed in 41 DREAMS 1G up to three years, while degradation kinetics were acquired in 54 DREAMS 2G implanted into porcine coronary arteries for 28, 90 and 180 days, one and two years. Assessment of end product composition was achieved in DREAMS 2G at 180 days. Myocardium was examined, while an OCT attenuation score was derived at strut level from 180 days to two years in DREAMS 2G. Degradation of DREAMS entails two corrosive phases. At one year, 94.8% of the magnesium was bioabsorbed in DREAMS 2G and, at two years, magnesium was completely replaced by amorphous calcium phosphate. Von Kossa staining revealed variable peri-strut mineralisation at all time points and only small focal myocardial emboli observed in one animal in the 180 days cohort. Strut discontinuity density was low at 28 days (0.5±0.57 per mm) and increased to a density above 7.5 per mm up to one year. OCT attenuation score correlated well with strut-based degradation analysis up to two years. CONCLUSIONS: While the current set of data supports vascular safety, clinical trials are warranted to prove the concept of vascular restoration following DREAMS implantation.
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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".