Fucoidan and topography modification improved in situ endothelialization on acellular synthetic vascular grafts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thrombogenesis remains the primary failure of synthetic vascular grafts. Endothelial coverage is crucial to provide an antithrombogenic surface. However, most synthetic materials do not support cell adhesion, and transanastomotic endothelial migration is limited. Here, a surface modification strategy using fucoidan and topography was developed to enable fast in situ endothelialization of polyvinyl alcohol, which is not endothelial cell-adhesive. Among three different immobilization approaches compared, conjugation of aminated-fucoidan promoted endothelial monolayer formation while minimizing thrombogenicity in both in vitro platelet rich plasma testing and ex vivo non-human primate shunt assay. Screening of six topographical patterns showed that 2 μm gratings increased endothelial cell migration without inducing inflammation responses of endothelial cells. Mechanistic studies demonstrated that fucoidan could attract fibronectin, enabling integrin binding and focal adhesion formation and activating focal adhesion kinase (FAK) signaling, and 2 μm gratings further enhanced FAK-mediated cell migration. In a clinically relevant rabbit carotid artery end-to-side anastomosis model, 60% in situ endothelialization was observed throughout the entire lumen of 1.7 mm inner diameter modified grafts, compared to 0% of unmodified graft, and the four-week graft patency also increased. This work presents a promising strategy to stimulate in situ endothelialization on synthetic materials for improving long-term performance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it