Lubricant‐Infused PET Grafts with Built‐In Biofunctional Nanoprobes Attenuate Thrombin Generation and Promote Targeted Binding of Cells
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
New surface coatings that enhance hemocompatibility and biofunctionality of synthetic vascular grafts such as expanded poly(tetrafluoroethylene) (ePTFE) and poly(ethylene terephthalate) (PET) are urgently needed. Lubricant-infused surfaces prevent nontargeted adhesion and enhance the biocompatibility of blood-contacting surfaces. However, limited success has been made in incorporating biofunctionality onto these surfaces and generating biofunctional lubricant-infused coatings that both prevent nonspecific adhesion and enhance targeted binding of biomolecules remains a challenge. Here, a new generation of fluorosilanized lubricant-infused PET surfaces with built-in biofunctional nanoprobes is reported. These surfaces are synthesized by starting with a self-assembled monolayer of fluorosilane that is partially etched using plasma modification technique, thereby creating a hydroxyl-terminated fluorosilanized PET surface. Simultaneously, silanized nanoprobes are produced by amino-silanizing anti-CD34 antibody in solution and directly coupling the anti-CD34-aminosilane nanoprobes onto the hydroxyl terminated, fluorosilanized PET surface. The PET surfaces are then lubricated, creating fluorosilanized biofunctional lubricant-infused PET substrates. Compared with unmodified PET surfaces, the designed biofunctional lubricant-infused PET surfaces significantly attenuate thrombin generation and blood clot formation and promote targeted binding of endothelial cells from human whole blood.
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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 | 0.000 | 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) | 0.000 | 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