Acetaldehyde plasma polymer‐coated PET fibers for endothelial cell patterning: Chemical, topographical, and biological analysis
Bibliographic record
Abstract
The objective of this study was to produce fibrous biomaterials with cell adhesive and cell repulsive capabilities for biomedical applications. To this aim, the surface of 100-mum diameter polyethylene terephthalate fibers were functionalized with acetaldehyde plasma polymer deposition followed by carboxymethyl dextran grafting onto the aldehyde-coated surfaces via a polyethyleneimine interlayer. The performance of the surface modification steps were confirmed by surface chemical composition analysis using X-ray photoelectron spectroscopy, surface topography analysis by atomic force microscopy, and scanning electron microscopy. The acetaldehyde plasma polymer-coated and polyethyleneimine-grafted substrates promoted human umbilical vein endothelial cells attachment, spreading and actin filaments/focal adhesions formation. In contrast, carboxymethyl dextran-grafted substrates resisted cell adhesion. These observations demonstrate that the current surface-modified polymer fibers can be used in tissue engineering applications, such as cell patterning substrates or vascular prosthesis development.
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 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".