Diabetic wound regeneration using peptide-modified hydrogels to target re-epithelialization
Bibliographic record
Abstract
The QHREDGS peptide, both as a soluble supplement and when immobilized in a substrate, protected keratinocytes against hydrogen peroxide stress in a dose-dependent manner. Collective migration of both normal and diabetic human keratinocytes was promoted on chitosan-collagen films with the immobilized QHREDGS peptide. The clinical relevance was demonstrated further by assessing the chitosan-collagen hydrogel with immobilized QHREDGS in full-thickness excisional wounds in a db/db diabetic mouse model; QHREDGS showed significantly accelerated and enhanced wound closure compared with a clinically approved collagen wound dressing, peptide-free hydrogel, or blank wound controls. The accelerated wound closure resulted primarily from faster re-epithelialization and increased formation of granulation tissue. There were no observable differences in blood vessel density or size within the wound; however, the total number of blood vessels was greater in the peptide-hydrogel-treated wounds. Together, these findings indicate that QHREDGS is a promising candidate for wound-healing interventions that enhance re-epithelialization and the formation of granulation tissue.
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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".