Bioinspired multifunctional cellulose film: In situ bacterial capturing and killing for managing infected wounds
Bibliographic record
Abstract
Bacterial infection of cutaneous wounds can easily lead to occurrence of chronic wounds and even more serious diseases. Therefore, multifunctional, biodegradable, and reusable wound dressings that can quickly manage wound infection and promote wound healing are urgently desired. Herein, inspired by the “capturing and killing” action of Drosera peltata Thunb., a biomimetic cellulose film was constructed to capture the bacteria (via the rough structure of the film) and kill them (via the combination of photodynamic therapy and chemotherapy) to promote wound tissue remodeling. The film (termed OBC-PR) was simply prepared by chemically crosslinking the oxidized bacterial cellulose (OBC) with polyhexamethylene guanidine hydrochloride (PHGH) and rose bengal (RB). Notably, it could effectively capture Escherichia coli and Staphylococcus aureus bacterial cells with capture efficiencies of ∼99 % and ∼96 %, respectively, within 10 min. Furthermore, the in vivo experiments showed that OBC-PR could effectively promote the macrophage polarization toward the M2 phenotype and adequately induce the reconstruction of blood vessels and nerves, thus promoting wound healing. This study provides a potential direction for designing multifunctional wound dressings for managing infected skin wounds in the future.
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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".