Natural Polymer-Based Antimicrobial Hydrogels without Synthetic Antibiotics as Wound Dressings
Bibliographic record
Abstract
Wound healing is usually accompanied by bacterial infection. The excessive use of synthetic antibiotics leads to drug resistance, posing a significant threat to human health. Hydrogel-based wound dressings aimed at mitigating bacterial infections have emerged as an effective wound treatment. The review presented herein particularly focuses on the hydrogels originating from natural polymers. To further enhance the performance of wound dressings, various strategies and approaches have been developed to endow the hydrogels with excellent broad-spectrum antibacterial activity. Those that are summarized in the current review are the hydrogels with intrinsic or stimuli-triggered bactericidal properties and others that serve as vehicles for loading antibacterial agents without synthetic antibiotics. Specific attention is paid to antimicrobial mechanisms and the antibacterial performance of hydrogels. Practical antibacterial applications to accelerate the wound healing employing these antibiotic-free hydrogels are also introduced along with the discussion on the current challenges and perspectives leading to new technologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".