Wound Gel Formulations Containing Poloxamer 407 and Polyhexanide Have In Vitro Antimicrobial and Antibiofilm Activity Against Wound-Associated Microbial Pathogens
Bibliographic record
Abstract
Chronic wounds are often caused or exacerbated by microbial biofilms that are highly resistant to antimicrobial treatments and that prevent healing. This study compared the antimicrobial and antibiofilm activity of nine topical wound treatments, comprising gels with different concentrations of poloxamer 407 (20–26%) and different pH levels (4–6) and containing polyhexanide (PHMB) as an antimicrobial agent; the effects of pH on wound gels containing this agent have not been previously reported. The wound gel formulations were tested against six common wound-associated microbial pathogens: Staphylococcus aureus, S. epidermidis, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, and Candida albicans. Time-kill assays were used to assess antimicrobial activity against planktonic forms of each species, and a colony biofilm model was used to assess antibiofilm activity against existing biofilms as well as inhibition of new biofilm formation. Biofilm inhibition activity was also assessed in the presence of common wound dressing materials. Wound gels with higher pH levels exhibited stronger antimicrobial activity, while poloxamer 407 concentrations >20% negatively impacted antimicrobial activity. Wound gel formulations were identified that had antimicrobial, antibiofilm, and biofilm inhibition activity against all tested species in vitro. Biofilm inhibition activity was not affected by contact with common wound dressings. Further development of these wound gels may provide a valuable new option for the treatment and prevention of chronic 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) | 0.001 | 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".