On the potential for fibronectin/phosphorylcholine coatings on PTFE substrates to jointly modulate endothelial cell adhesion and hemocompatibility properties
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
The use of biomolecules as coatings on biomaterials is recognized to constitute a promising approach to modulate the biological response of the host. In this work, we propose a coating composed by 2 biomolecules susceptible to provide complementary properties for cardiovascular applications: fibronectin (FN) to enhance endothelialization, and phosphorylcholine (PRC) for its non thrombogenic properties. Polytetrafluoroethylene (PTFE) was selected as model substrate mainly because it is largely used in cardiovascular applications. Two approaches were investigated: 1) a sequential adsorption of the 2 biomolecules and 2) an adsorption of the protein followed by the grafting of phosphorylcholine via chemical activation. All coatings were characterized by immunofluorescence staining, X-Ray Photoelectron Spectroscopy and Scanning Electron Microscopy analyses. Assays with endothelial cells showed improvement on cell adhesion, spreading and metabolic activity on FN-PRC coatings compared with the uncoated PTFE. Platelets adhesion and activation were both reduced on the coated surfaces when compared with uncoated PTFE. Moreover, clotting time tests exhibited better hemocompatibility properties of the surfaces after a sequential adsorption of FN and PRC. In conclusion, FN-PRC coating improves cell adhesion and non-thrombogenic properties, thus revealing a certain potential for the development of this combined deposition strategy in cardiovascular applications.
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.
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