Abstract 336: Reactive Ion Surface Modification of Vascular Graft Materials Enhances Endothelialization Without Promoting Thrombosis
Bibliographic record
Abstract
Previous work demonstrated that poly(vinyl alcohol) (PVA) holds great potential as a cardiovascular biomaterial. PVA prevents thrombosis at least as well as expanded polytetrafluoroethylene (ePTFE) clinical vascular grafts in whole blood studies. However, long term in vivo success of this material will likely depend on its ability to support an endothelial cell (EC) monolayer. To promote EC attachment and growth we are treating the PVA surface with high energy reactive ions. We hypothesize that increasing the concentration of reactive groups on the surface of the PVA will increase endothelial outgrowth cell (EOC, a type of endothelial progenitor cell isolated from whole blood) attachment without increasing thrombosis. To test this hypothesis we exposed PVA films to reactive ion modifications using O 2 , N 2 , and Ar gases at a variety of powers and durations. Treated samples were then characterized with X-ray photoelectron spectroscopy to quantify surface chemistries. Samples were seeded with EOCs to quantify attachment and proliferation using immunohistochemistry. Platelet and fibrin accumulation was measured dynamically in PVA tubes using a baboon arteriovenous shunt with radiolabeled platelets for 1hr. Flow rate was controlled and no anticoagulants were given. O 2 and N 2 treatments encouraged cell adhesion on the PVA films in an energy dependent manner, which correlated to an increase in surface nitrogen. Initial shunt data (n=3) indicate that treated samples did not have increased platelet attachment compared to untreated PVA or ePTFE. In conclusion, reactive ion modified-PVA demonstrates a promising biomaterial by supporting EC growth without increasing thrombosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".