A Low Molecular Weight Hyaluronic Acid Derivative Accelerates Excisional Wound Healing by Modulating Pro-Inflammation, Promoting Epithelialization and Neovascularization, and Remodeling Collagen
Bibliographic record
Abstract
Recent knowledge of the cellular and molecular mechanisms underlying cutaneous wound healing has advanced the development of medical products. However, patients still suffer from the failure of current treatments, due to the complexity of healing process and thus novel therapeutic approaches are urgently needed. Previously, our laboratories produced a range of low molecular weight hyaluronic acid (LMW-HA) fragments, where a proportion of the glucosamine moieties were chemically N-acyl substituted. Specifically, N-butyrylation results in anti-inflammatory properties in a macrophage system, and we demonstrate the importance of N-acyl substituents in modulating the inflammatory response of LMW-HA. We have set up an inter-institutional collaborative program to examine the biomedical applications of the N-butyrylated LMW-HA (BHA). In this study, the potentials of BHA for dermal healing are assessed in vitro and in vivo. Consequently, BHA significantly promotes dermal healing relative to a commercial wound care product. By contrast, the “parent” partially de-acetylated LMW-HA (DHA) and the re-acetylated DHA (AHA) significantly delays wound closure, demonstrating the specificity of this N-acylation of LMW-HA in wound healing. Mechanistic studies reveal that the BHA-mediated therapeutic effect is achieved by targeting three phases of wound healing (i.e., inflammation, proliferation and maturation), demonstrating the significant potential of BHA for clinical translation in cutaneous wound healing.
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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".