Role of protein kinase C in the monocyte‐derived macrophage‐mediated biodegradation of polycarbonate‐based polyurethanes
Bibliographic record
Abstract
Polycarbonate-polyurethanes (PCNUs) elicit a foreign body reaction during the initial tissue contact, partly mediated by the respiratory burst in monocytes, during which protein kinase C (PKC) activates NADPH (nicotinamide adenine dinucleotide phosphate) oxidase. Using an in vitro cell system, monocytes were differentiated into monocyte-derived macrophages (MDMs) and then reseeded onto three PCNUs (HDI431, HDI321, or MDI321): hexane (HDI) or 4,4-methylene bis-phenyl (MDI) diisocyanates synthesized with poly(1,6-hexyl 1,2-ethyl carbonate) diol (PCN) and 14C-labeled butanediol (BD) in the ratios 4:3:1 or 3:2:1 (diisocyanate/PCN/BD). MDM-mediated degradation was assessed by radiolabel release in the presence of a PKC activator (phorbol myristate acetate), inhibitor (H7), and a catalase/peroxidase inhibitor (NaN3). Activating PKC decreased biodegradation and esterase activity in MDMs on HDI431 and HDI321 but not MDI321, whereas H7 and NaN3 inhibited the MDM degradation of MDI321 only. Pretreatment of the PCNUs with H2O2 inhibited esterase-mediated radiolabel release from HDI431 and HDI321 but stimulated radiolabel release from MDI321. The difference in the effect of H2O2 on the HDI versus MDI PCNUs contributes to explaining the effect of PKC activation on material degradation. Understanding the mechanism by which this pathway is linked to PCNU chemistry may assist in designing materials with tailored biodegradation rates.
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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) | 0.001 | 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".