Application of Chitosan‐Based Biomaterials for Blood Vessel Regeneration
Bibliographic record
Abstract
Abstract Summary:Vascular diseases are the leading cause of morbidity and mortality in the western world. Autologous vessels remain the standard for coronary grafting and peripheral bypass surgery; however, their availability in patients can be limited. Therapeutic angiogenesis using growth factors, genes, or progenitor cells has been given considerable scientific attention over the last decade, but has not yet provided a definitive clinical benefit. Biomaterials could be developed to protect protein, DNA and cells against hostile conditions. Chitosan, a natural polymer of glucosamine and N‐acetyl glucosamine, has been widely studied in tissue engineering due to its biocompatibility, biodegradability, and muco‐adhesive and antimicrobial properties. Notably, the application of chitosan has been gaining attention in the vascular field due to its structural similarity to glycosaminoglycans, which are components of a tissue's extracellular matrix. In this review, chitosan‐based materials, and their use in tissue engineered blood vessels, and as protein, gene and cell vectors for angiogenic therapy are discussed.
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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".