The effects of phorbol ester activation and reactive oxygen species scavengers on the macrophage‐mediated foreign body reaction to polyurethanes
Bibliographic record
Abstract
Phorbol myristate acetate, a protein kinase C activator, inhibited monocyte-derived macrophage (MDM)-mediated degradation of aliphatic (HDI) polycarbonate-based polyurethanes but not degradation of the aromatic polycarbonate-based polyurethane (MDI). The objectives of this study were to determine if reactive oxygen species are involved in the phorbol myristate acetate effect on esterase activity and MDM-mediated polycarbonate-based polyurethane degradation and to find a good marker of material-initiated activation of MDM. The phorbol myristate acetate-dependent effects of the material chemistry on cell activation and degradation were evaluated by adding reactive oxygen species scavengers, catalase plus superoxide dismutase to MDM and assaying possible markers of MDM activation: esterase activity, acid phosphatase activity, and high molecular weight group box 1 protein (HMGB1). All treatments reduced the esterase activity in MDM on HDI but not in MDM on MDI. Acid phosphatase was inhibited in MDM to varying degrees on all surfaces by phorbol myristate acetate or catalase plus superoxide dismutase either alone or together. Secretion of HMGB1 from MDM on HDI431 was higher than MDI; however only secretion from MDM on HDI was inhibited by phorbol myristate acetate. In MDM on HDI, catalase plus superoxide dismutase reduced intracellular HMGB1 levels +/- phorbol myristate acetate; whereas, catalase, superoxide dismutase plus phorbol myristate acetate increased intracellular HMGB1 in MDM on MDI, suggesting that esterase and HMGB1 are more specific markers of activation than acid phosphatase. Manipulation of signaling pathways may provide insight surrounding the mechanism of activation for oxidative and/or hydrolytic degradative pathways in the MDM response to material surface chemistry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".