Cell Interactions with Vascular Regenerative MAA‐Based Materials in the Context of Wound Healing
Bibliographic record
Abstract
In diabetic patients the development of chronic non-healing wounds is a common complication. A methacrylic acid-based biomaterial is a vascular regenerative material that enhances diabetic healing without the use of cells or growth factors. The bioactive nature of this material is thought to be associated with its anionic charge or surface chemistry. Contact between the methacrylic acid-based biomaterial and tissue begins with protein (including complement) adsorption and is followed by interaction of the biomaterial with resident and infiltrating cells in the wound bed (e.g., macrophages and endothelial cells). This results in changes to their surface receptors to activate phosphorylation cascades that lead to differential activation of signalling pathways such as those involving osteopontin and sonic hedgehog. These changes modulate the phenotype of the cells in the wound bed, eventually improving vessel formation and wound healing. Understanding the molecular and cellular mechanisms will have broad implications for biomaterials, not just the methacrylic acid-based material, and will facilitate the advancement of regenerative biomaterials for diverse applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".