Biodegradation of polycarbonate‐based polyurethanes by the human monocyte‐derived macrophage and U937 cell systems
Bibliographic record
Abstract
The prominent cell type found on implanted medical devices during the chronic inflammatory response is the monocyte-derived macrophage (MDM). Using an activated in vitro cell system, it was possible to show that MDMs possess esterolytic activities that may contribute to the degradation of polyurethanes. In the present study, the U937 cell line was paralleled to the MDM cell system in order to validate the use of a cell line that could expedite studies on biomaterial biocompatibility and biostability. Using 12-o-tetradecanoylphorbol 13-acetate (PMA), the optimum differentiation time for the U937 cells was 72 h based on biodegradation, degradative potential, and (35)S-methionine uptake. After activation of the cells by resuspending from tissue culture polystyrene plates and reseeding onto a (14)C-labeled polycarbonate-based polyurethane(PCNU), both U937 cells and the MDMs elicited comparable radiolabel release (measure of polymer breakdown) and esterase activity (measure of degradative potential) at 48 h. There was no difference in the effect on radiolabel release and esterase activity elicited by both cell types with inhibitors of protein synthesis, esterase activity, and phospholipase A(2). This established that both cell types likely used similar hydrolytic activities and signaling pathways to cause degradation of the PCNU. Immunoblotting demonstrated that both cell systems secreted monocyte-specific esterase and cholesterol esterase enzymes previously shown to degrade PCNUs. The U937 cell system is more convenient and reproducible than MDMs for pursuing possible biological pathways elucidating the mechanism of polyurethane biodegradation. Once established with U937s, the pathways can then be validated with the more physiologically relevant human MDM cell system.
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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 | 0.001 | 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) | 0.001 | 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".