Polyethylene terephthalate textile heart valve: How poly(ethylene glycol) grafting limits fibrosis
Bibliographic record
Abstract
Abstract Transcatheter aortic valve replacement (TAVR) is an alternative technique to surgical valve replacement for over 300,000 patients worldwide. The valve material used in the TAVR is made of biological tissues, whose durability remains unknown. The success of the TAVR favors the research toward synthetic valve leaflet materials as an alternative to biological tissues. In particular, polyethylene terephthalate (PET) textile valves have recently proven durability over a 6‐month period in animal sheep models. Excessive fibrotic tissue formation remains, however, a critical issue to be addressed. The aim of this work was therefore to investigate the potential of PET textiles covalently conjugated with polyethylene glycol (PEG), known for its antifouling properties, to modulate the fibrosis formation both in vitro and in vivo. For this purpose, the surfaces of heart valves made of PET textiles were functionalized with an atmospheric pressure plasma, leading to the formation of carboxylic acid (COOH) groups, further used for PEG‐NH2 conjugation. Surface modification efficiency was assessed by X‐ray photoelectron spectroscopy and water contact angle measurements. The biological behavior of the as‐modified surfaces was evaluated by in vitro assays, using rat cardiac fibroblast cells. The results show that PEG treated substrates restrained the fibroblasts adhesion and proliferation. The PEG treated valve, implanted in a juvenile sheep model, showed a significant fibrosis reduction. The explant also revealed calcification issues that need to be addressed.
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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".