Use of monocyte/endothelial cell co-cultures (in vitro) and a subcutaneous implant mouse model (in vivo) to evaluate a degradable polar hydrophobic ionic polyurethane
Bibliographic record
Abstract
Potential benefits of co-culturing monocytes (MC) with vascular smooth muscle cells have been reported on for tissue engineering applications with a degradable, polar, hydrophobic, and ionic polyurethane (D-PHI). Since the interaction of MC and endothelial cells (EC) within the blood vessel endothelium is also a process of wound repair it was of interest to investigate their function when cultured on the synthetic D-PHI materials, prior to considering the materials' use in vascular engineering. The co-culture (MC/EC) in vitro studies were carried out on films in 96 well plates and porous scaffold disks were prepared for implant studies in an in vivo subcutaneous mouse model. After 7 days in culture, the MC/EC condition was equal to EC growth but had lower esterase activity (a measure of degradative potential), no pro-inflammatory TNF-α and a relatively high anti-inflammatory IL-10 release while the ECs maintained their functional marker CD31. After explantation of the porous scaffolds, a live/dead stain showed that the cells infiltrating the scaffolds were viable and histological stains (May-Grunwald, Trichrome) demonstrated tissue in growth and extracellular matrix synthesis. Lysates from the implant scaffolds analyzed with a cytokine antibody array showed decreased pro-inflammatory cytokines (IL-6, TNF-α, GM-CSF), increased anti-inflammatory cytokines (IL-10, IL-13, TNF-RI), and increased chemotactic cytokines (MCP-1, MCP-5, RANTES). The low foreign body response elicited by D-PHI when implanted in vivo supported the in vitro studies (EC and MC co-culture), demonstrating that D-PHI promoted EC growth along with an anti-inflammatory MC, further demonstrating its potential as a tissue engineering scaffold for vascular applications.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".