Characterization of a degradable polar hydrophobic ionic polyurethane with circulating angiogenic cells<i>in vitro</i>
Bibliographic record
Abstract
This study investigated the interaction of human circulating angiogenic cells (CACs) with a degradable polar hydrophobic ionic polyurethane (D-PHI) which has been previously shown to exhibit anti-inflammatory character and favorable interactions with human endothelial cells (ECs). Given the implication of the CACs in microvessel development it was of intrinsic interest to expand our knowledge of D-PHI biocompatibility with this relevant primary cell involved in angiogenesis. The findings will be compared to a well-established benchmark substrate for CACs, fibronectin-coated tissue culture polystyrene (TCPS). Immunoblotting analysis showed that CACs were a heterogeneous population of cells composed mostly of monocytic cells expressing the CD14 marker. Assessment of the cytokine release profile, using ELISA, showed that D-PHI supported a higher concentration of interleukin-10 (IL-10) when compared to the concentration of tumor necrosis factor alpha, which is indicative of an anti-inflammatory phenotype, and was different from the response with TCPS. It was found that the CACs were attached to D-PHI and remained viable and functional (nitric oxide production) during the seven days of culture. However, there did not appear to be any significant proliferation on D-PHI, contrary to the CAC growth on fibronectin-coated TCPS. It was concluded that D-PHI displayed some of the qualities suitable to enable the retention of CACs onto this substrate, as well as maintaining an anti-inflammatory phenotype, characteristics which have been reported to be important for angiogenesis in vivo.
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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".