Bismuth-ethanedithiol incorporated in a liposome-loaded tobramycin formulation modulates the alginate levels in mucoid <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
OBJECTIVES: This study examined the antibacterial activity, alginate modulation, and deposition of a tobramycin bismuth-ethanedithiol (Tob-Bi) conventional (free) or vesicle-entrapped (lipo) formulation against two mucoid Pseudomonas aeruginosa clinical isolates. METHODS: The inhibitory, bactericidal and biofilm eradication concentrations (in presence or absence of alginate lyase) were determined. The modulation of alginate was assessed by the carbazole assay and fluorescent-labelling of live alginate-producing biofilms by confocal microscopy. The deposition of the formulations was assessed using the immunogold-labelling technique, transmission electron microscopy, and energy dispersive X-ray spectroscopy (EDS). KEY FINDINGS: The inhibitory and bactericidal concentrations for lipo Tob-Bi compared with free Tob-Bi were reduced in all strains by 2- to 8-fold, and 2- to 32-fold, respectively. The biofilm eradication concentrations for lipo Tob-Bi compared with free Tob-Bi were reduced by 4- to 32-fold in the mucoid strains. The addition of alginate lyase transiently enhanced eradication for one mucoid strain only. The alginate levels were attenuated by more than half, and free Tob-Bi fared better than lipo Tob-Bi determined by the carbazole assay. Under confocal microscopy, alginate lyase reduced alginate levels and detached mucoid biofilms. Free and lipo Tob-Bi did not detach the bacteria from the surface, but attenuated alginate levels. Tobramycin was detected by immunogold-labelling inside the bacterium, but EDS did not detect bismuth deposits. CONCLUSIONS: These findings substantiate a role in which tobramycin, bismuth, and alginate lyase play in eradicating mucoid P. aeruginosa growth and modulate alginate levels.
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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) | 0.000 | 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 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".