Synergistic Effect and Antibiofilm Activity of a Skin and Wound Cleanser.
Bibliographic record
Abstract
INTRODUCTION: Biofilm in chronic wounds impedes the wound healing process. Each biofilm has differing characteristics requiring a multifaceted approach for removal while maintaining a surrounding environment conducive to wound healing. OBJECTIVE: In this study, 3 of the components in a wound cleanser are tested to determine synergy in eradicating biofilms of methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa in vitro. MATERIALS AND METHODS: The 3 components assessed for synergy were ethylenediamine tetraacetic acid sodium salts (EDTA), vicinal diols (VD; ethylhexylglycerin and octane-1,2-diol), and polyhexamethylene biguanide (PHMB). Each component was assessed individually and in combination while dissolved in a base solution. The Calgary assay method was used for biofilm growth and treatment. Kull Equation analysis for synergy was conducted using viable count results. RESULTS: Synergy is defined as the interaction of components to produce a combined effect greater than the sum of their separate effects. The base solution containing all 3 components (EDTA, VD, and PHMB) reduced biofilm viability by more than 5 logs, demonstrating statistically significant synergy. The 3 components tested individually in the base solution resulted in the following: EDTA did not reduce bacteria viability; VD reduced viability by about 1 log; and PHMB reduced P aeruginosa viability by about 2.5 logs and MRSA viability by about 4 logs. Of importance, the MRSA biofilm failed to regrow in the recovery plates after combined treatment, indicating complete elimination of the biofilm bacteria. CONCLUSIONS: The experimental and calculated results indicate the 3 components (VD, EDTA, and PHMB) when used together act synergistically to eradicate MRSA and P aeruginosa biofilms in vitro.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".