In Vitro Assessment of the Synergy between Polymyxin B (PMB) and Polymyxin B Nonapeptide (PMBN) and Antibiotics on Biofilms from Diabetic Foot Infections
Bibliographic record
Abstract
Background: The increasing resistance of Gram-negative bacteria isolated from nosocomial infections and chronic wounds, such as diabetic foot ulcers has renewed research interests in the use of polymyxins in the treatment of multidrug resistant infections. The added resistance conferred by biofilm development in such infections and the absence of novel antibiotics presuppose that polymyxins are the likely drugs of choice in spite of their nephrotoxicity. The effects of PMB and PMBN have been previously assessed on planktonic bacteria isolated from various infections. Methods: This current study assessed the synergy between a PMB/PMBN and two antibiotics (ceftazidime and levofloxacin) in an attempt to develop a strategy for biofilm disruption using the Minimum Biofilm Eradication Concentration Physiology and Genetic assay (MBEC™ P & G, Innovotech Inc, Edmonton, Alberta, Canada) according to manufacturer’s instructions. Klebsiella pneumoniae (K. pneumoniae) and Proteus mirabilis (P. mirabilis) biofilms of initial broth suspensions of 108 colony forming units per mL, cultivated on the pegs of the MBEC device were challenged with 5120 µg/mL of both ceftazidime and levofloxacin in a ten-fold dilution assay and in the presence of 100 and 500 µg/mL PMB and PMBN. Results: From table of results (Table 1), it can be deduced that both ceftazidime and levofloxacin are very effective in inhibiting biofilm development (as shown by percentage inhibition (PI)) when augmented with PMB and PMBN. This is about 100-fold increase in efficacy when compared to the antibiotics used on their own. The percentage reduction (PR) in biofilm was also increased considerably when PMB and PMBN concentrations were increased to 500 µg/mL. PMB was more effective than its less antibacterial derivative PMBN. Levofloxacin was also found to be more effective than ceftazidime when combined with both PMB and PMBN due to its enhanced cell-membrane permeability and as an anti-DNA replication uncoupling agent. Conclusion: The above results indicate that the synergy between antibiotics and cell membrane permeabilising agents may provide alternate strategies towards biofilm eradication
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".