Characterization of a Degradable Polar Hydrophobic Ionic Polyurethane Using a Monocyte/Endothelial Cell Co-culture (in vitro) and a Subcutaneous Implant Mouse Model (in vivo)
Bibliographic record
Abstract
A degradable/polar/hydrophobic/ionic (D-PHI) polyurethane with properties intended to promote tissue regeneration in a small diameter peripheral artery vascular graft was evaluated for cell biocompatibility and growth. Films were cast in polypropylene 96 well plates for monocyte/endothelial cell (EC) co-culture in vitro studies and porous scaffold discs were implanted in an in vivo subcutaneous mouse model. After 7 days in culture the co-culture demonstrated cell adhesion and growth, low esterase activity (a measure of degradative potential and cell activation), no detectable release of pro-inflammatory cytokine (tumour necrosis factor -α) but measurable anti-inflammatory interleukin (IL)-10. The EC and the co-culture expressed the EC biomarker CD31, whereas the monocyte monoculture did not. Cytokine array analysis of the in vivo characterization of D-PH supported an anti-inflammatory phenotype of cells at the site of the implant. Levels of IL-6 significantly decreased over time while IL-10 was significantly higher at 6 weeks post implant. TNF-α levels did not change significantly from 24 hours onwards, however the trend was towards lesser amounts following the initial time point. Histological analysis of the explanted scaffolds showed excellent tissue ingrowth and vascularization. A live/dead stain showed that the cells infiltrating the scaffolds were viable. Both the in vitro and in vivo results of this thesis indicate that D-PHI is a good candidate material for tissue engineering a peripheral artery vascular graft.
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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".