Bromelain Loading and Release from a Hydrogel Formulated Using Alginate and Arabic Gum
Bibliographic record
Abstract
An ideal wound dressing ensures a moist environment around the wound area and absorbs exudates from the wound surface. Topical application of bromelain to incised wounds has been shown to reprogram the wound microenvironment to promote effective tissue repair. Combining the characteristics of hydrogels and bromelain is therefore of great interest. Herein, we describe the development of a hydrogel, formulated using alginate and Arabic gum, for bromelain loading and release. The hydrogel formulation was evaluated using response surface methodology, considering the pH value and the concentration of alginate and Arabic gum. Bromelain loading and release were evaluated based on passive diffusion. Differential scanning calorimetry and Fourier transform infrared spectroscopy were performed to confirm bromelain immobilization in the hydrogel. The final hydrogel formulation had a swelling ratio of 227 % and incorporated 19 % of bromelain from a bromelain solution. Bromelain immobilization in the hydrogel was the result of hydrogen bond formation and was optimal at 4 °C after 4 h of contact. This evidence suggests that bromelain entrapment into a hydrogel is a promising strategy for the development of wound dressings that support the debridement of burns and wounds.
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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".