Biofilm reduction by a new burn gel that targets nociception
Bibliographic record
Abstract
AIMS: To compare the ability of an amorphous first aid topical gel containing vinegar, citric acid and EDTA (RescuDerm(TM); RESC) and various derivative formulations to eradicate Pseudomonas aeruginosa (PSEUD) and Staphylococcus epidermidis (STAPH) biofilms. METHODS AND RESULTS: 24-h biofilms prepared using the Minimum Biofilm Elimination Concentration (MBEC) Assay System were exposed for 4 or 24 h to the different gel formulations. Citric acid-free, acetic acid-free or acetic acid-free/sodium acetate-supplemented RESC gels reduced PSEUD and STAPH biofilm formation as effectively as RESC. Substituting the weak organic acids with equivalent concentrations of glacial acetic acid reduced the effectiveness of gel against PSEUD and STAPH biofilms by half, but viable bacterial counts still remained below 4 log(10) CFU/peg. Removal of gelling agent and/or EDTA enhanced efficacy against PSEUD but not STAPH biofilms. An acidified placebo gel formulation generated an only marginal bactericidal effect compared to that of RESC. CONCLUSIONS: RESC is a promising new antimicrobial agent. Its weak organic acid content, rather than merely acidic pH, mediates its considerable in vitro bactericidal efficacy against bacterial biofilms. SIGNIFICANCE AND IMPACT OF THE STUDY: These data, taken together with the observation that RescuDerm possesses broad in vitro bactericidal activity against other pathogen species, suggest the potential usefulness of this product for controlling biofilm formation on a variety of cutaneous traumatic and surgical wounds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".