Dual Cross-Linked Chitosan-Based Films with pH-Sensitive Coloration and Drug Release Kinetics for Smart Wound Dressings
Bibliographic record
Abstract
In this study, we developed dual-cross-linked hydrogel films based on carboxyethyl chitosan (CECS) and sodium alginate (SA), utilizing dialdehyde β-cyclodextrin (DA-βCD) and gluconic acid δ-lactone (GDL) as cross-linkers. Designed as smart wound dressings, the films exhibit pH sensitivity due to the incorporation of carboxyethylated phenol red-grafted chitosan (CS-PR-AA), which allows them to change color from orange to purple in response to pH variations. FT-IR and TGA analyses confirmed the formation of imine bonds and polyelectrolyte complexes, indicating successful cross-linking. The films demonstrated high cell viability, confirming their biocompatibility and nontoxicity. The swelling behavior varied with pH, underscoring their adaptability to different wound environments. Additionally, drug release kinetics were studied for films incorporating diclofenac sodium (DCF) at various pH levels, revealing that the release rate was influenced by cross-linking density and environmental pH. These findings suggest that the dual-cross-linked hydrogel films have significant potential as smart wound dressings, offering controlled drug release and pH-responsive behavior suitable for wound care applications.
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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) | 0.000 | 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 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".