Development of a universal, oriented antibody immobilization method to functionalize vascular prostheses for enhanced endothelialization for potential clinical application
Bibliographic record
Abstract
BACKGROUND: Thrombosis is a common cause of vascular prosthesis failure. Antibody coating of prostheses to capture circulating endothelial progenitor cells to aid endothelialization on the device surface appears a promising solution to prevent thrombus formation. Compared with random antibody immobilization, oriented antibody coating (OAC) increases antibody-antigen binding capacity and reduces antibody immunogenicity in vivo. Currently, few OAC methods have been documented, with none possessing clinical application potential. RESULTS: Dopamine and the linker amino-PEG8-hydrazide-t-boc were successfully deposited on the surface of cobalt chromium (CC) discs, CC stents and expanded polytetrafluoroethylene (ePTFE) grafts under a slightly basic condition. CD34 antibodies were immobilized through the reaction between aldehydes in the Fc region created by oxidation and hydrazides in the linker after t-boc removal. CD34 antibody-coated surfaces were integral and smooth as shown by scanning electron microscopy (SEM), had significantly reduced or no substrate-specific signals as revealed by X-ray photoelectron spectroscopy, were hospitable for HUVEC growth as demonstrated by cell proliferation assay, and specifically bound CD34 + cells as shown by cell binding testing. CD34 antibody coating turned hydrophobic property of ePTFE grafts to hydrophilic. In a porcine carotid artery interposition model, a confluent monolayer of cobblestone-shaped CD31 + endothelial cells on the luminal surface of the CD34 antibody coated ePTFE graft were observed. In contrast, thrombi and fibrin fibers on the bare graft, and sporadic cells on the graft coated by chemicals without antibodies were seen. CONCLUSION: A universal, OAC method was developed. Our in vitro and in vivo data suggest that the method can be potentially translated into clinical application, e.g., modifying ePTFE grafts to mitigate their thrombotic propensity and possibly provide for improved long-term patency for small-diameter grafts.
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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".