Fabrication of Cellulosic Nonwoven-Based Wound Dressings Coated with CTAB-Loaded Double Network PAMPS/PNaA Hydrogels
Bibliographic record
Abstract
Novel approaches have been implemented to fabricate wound dressings including electrospinning of hydrogels, and coating-based nonwoven hydrogels. In this study, only the coating technique was studied in order to fabricate wound dressing. For this purpose, nonwoven cotton fabrics were coated with layer-by-layer PNaA (poly sodium acrylate) and poly 2-Acrylamido-2-methylpropane sulfonic acid (PAMPS). Microwave techniques were then implemented to create an antibacterial activity using cetyltrimethylammonium bromide (CTAB). For the characterization, the physical, mechanical and antibacterial properties of the different samples and to determine potential wound dressing candidates, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), swelling, and water vapor permeability (WVP) tests as well as contact angle measurements with water were performed. The application of microwave techniques using CTAB on the fabricated nonwoven-based wound dressings showed potential results of creating an efficient antibacterial activity with high fibroblast cell viability. The in vitro aspirin release experiment confirmed that the release amount depended on the number of hydrogel layers. The results of physical and mechanical tests showed that coated nonwoven with layers of hydrogels had the desired strength along breathability, flexibility, and wettability. These cumulative results indicate that the fabricated structures in this work are good potential candidates for wound dressing 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".