Novel adjuvant strategy to potentiate bacitracin against MDR MRSA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Bacitracin is an antimicrobial peptide that is frequently used as an active ingredient in antimicrobial ointments. However, bacitracin resistance is highly prevalent in community-associated MRSA (CA-MRSA) strains and significantly compromises the effectiveness of existing antimicrobial ointments. In this study, we aimed to develop novel adjuvants to enhance the antimicrobial activity of bacitracin by using alkyl gallates. METHODS: The growth of MRSA USA300, the predominant CA-MRSA strain in the USA, was determined in the presence of bacitracin and alkyl gallates at various concentrations. The viability of USA300 and MDR clinical isolates of MRSA was measured after exposure to various combinations of bacitracin and alkyl gallates. RESULTS: Whereas 100 U/mL bacitracin did not inhibit USA300, 1 U/mL bacitracin in combination with as low as 2 mg/L octyl gallate (OG) and 8 mg/L dodecyl gallate (DG), respectively, completely inhibited the growth of USA300. Among the tested alkyl gallates, OG most significantly enhanced the bactericidal activity of bacitracin. For example, 10(-3) U/mL bacitracin with 5 mg/L OG effectively killed USA300, which is an ∼200 000-fold decrease in the MBC of bacitracin for USA300. Furthermore, bacitracin/OG combinations demonstrated similar levels of antimicrobial activity against human clinical isolates of MRSA resistant to multiple antibiotics of clinical importance. CONCLUSIONS: Some alkyl gallates, particularly OG, significantly increased the antimicrobial activity of bacitracin against MDR MRSA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it