Exploring cell compatibility of a fibronectin‐functionalized physically crosslinked poly(vinyl alcohol) hydrogel
Bibliographic record
Abstract
Physically crosslinked poly(vinyl alcohol) (PVA) hydrogels prepared using a low-temperature thermally cycled process have tunable mechanical properties that fall within the range of soft tissues, including cardiovascular tissue. An approach to render it hemocompatible is by endothelization, but its hydrophilic nature is not conducive to cell adhesion and spreading. We investigated the functionalization reaction of this class of PVA hydrogel with fibronectin (FN) for adhesion and spreading of primary porcine radial artery cells and vascular endothelial cells. These are cells relevant to small-diameter vascular graft development. FN functionalization was achieved using a multistep reaction, but the activation step involving carbonyl diimidazole normally required for chemically crosslinked PVA was found to be unnecessary. The reaction resulted in an increase in the elastic modulus of the PVA hydrogel but is still well within the range of cardiovascular tissue. Confocal microscopy confirmed the adhesion and spreading of both cell types on the PVA-FN surfaces, whereas cells failed to adhere to the PVA control. This is a first step toward an alternative for the realization of a synthetic replacement small-diameter vascular graft.
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".