A laminin mimetic peptide SIKVAV-conjugated chitosan hydrogel promoting wound healing by enhancing angiogenesis, re-epithelialization and collagen deposition
Bibliographic record
Abstract
Angiogenesis and re-epithelialization are critical factors in skin wound healing. Growth factors and stem cells have demonstrated their active roles in promoting these two processes. Peptides show similar effects with growth factors with lower cost and controllable properties. Here we report a biomimetic fragment of the laminin -Ser-Ile-Lys-Val-Ala-Val (SIKVAV)-conjugated chitosan hydrogel that can promote skin regeneration. In vitro we found that this peptide-conjugated hydrogel significantly promoted BMSC adhesion and proliferation. In vivo, this hydrogel accelerated wound contraction. The subcutaneous implantation test and H&E staining results revealed that the peptide-modified chitosan hydrogel dramatically led to the formation of new blood vessels. Moreover, Masson staining showed that many newborn collagen fibers appeared in the peptide hydrogel group, while only a few newborn collagen fibers were found in control and chitosan hydrogel groups. The peptide chitosan hydrogel also re-epithelialized quickly, while the control and chitosan hydrogel took more time to complete. These results suggest that the SIKVAV peptide is an effective motif to significantly improve the function of chitosan in angiogenesis and re-epithelialization of skin.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".