Topical application of a film‐forming emulgel dressing that controls the release of stratifin and acetylsalicylic acid and improves/prevents hypertrophic scarring
Bibliographic record
Abstract
Here, we evaluate the efficacy of an emulgel dressing to control the release of an antifibrogenic factor, stratifin (SFN), along with an anti-inflammatory drug, acetylsalicylic acid (ASA), to be used as a wound dressing with hypertrophic scar reducing features. Emulgel dressings were prepared by dispersing positively charged submicron vesicles in carboxymethyl cellulose gel. Release kinetics of SFN/ASA and toxicity for primary skin cells were assessed in vitro. Antifibrogenic efficacy of medicated emulgel dressings was tested on a rabbit ear fibrotic model. Following topical application on the wounds, emulgels formed an occlusive film and controlled the release of SFN and ASA for 7 and 24 hours, respectively. Wounds treated with SFN/ASA-containing emulgel dressings showed an 80% reduction in scar elevation compared with untreated controls. Topical formulations were nontoxic for cultured human keratinocytes and fibroblasts. Inflammation was significantly controlled in treated wounds, as shown by a reduced number of infiltrated CD3(+) T cells (p < 0.001) and macrophages. SFN/ASA-treated wounds showed a significantly higher (p < 0.001) expression of matrix metalloproteinase-1, resulting in reduced collagen deposition and less scarring. Film-forming emulgel dressings that control the release of antifibrogenic and anti-inflammatory factors provide an excellent treatment option for postburn hypertrophic scar management.
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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".