Bactericidal efficacy of liposomal aminoglycosides against Burkholderia cenocepacia
Bibliographic record
Abstract
OBJECTIVES: Burkholderia cenocepacia (formally a genotype of Burkholderia cepacia complex called genomovar III) has emerged as a serious opportunistic pathogen in individuals with cystic fibrosis. We developed a liposomal antibiotic formulation composed of 1,2-distearoyl-sn-glycero-3-phosphocholine and cholesterol (molar ratio 2:1) to overcome B. cenocepacia's resistance to commonly used aminoglycosidic antibiotics. METHODS: The dehydration-rehydration vesicles technique was used to entrap antibiotics in liposomes. The size of liposome formulations was measured and encapsulation efficiencies were determined by microbiological assays. MICs of free and liposomal antibiotics against the clinical isolates of B. cenocepacia were determined by the standard broth dilution method and in vitro time--kill studies were performed using free and liposomal antibiotics at one, two or four times the MICs. We studied the mechanism of action of these formulations by using transmission electron microscopy (TEM), fluorescence-activated cell sorter (FACS) analysis, lipid-mixing assay and immunocytochemistry. RESULTS: The encapsulation efficiencies of amikacin, gentamicin and tobramycin into liposomes were 52.08 +/- 5.4%, 27.72 +/- 1.14% and 28.08 +/- 1.54%, respectively. The liposome formulations were more stable in PBS at 4 degrees C than in PBS, bronchoalveolar lavage fluid or plasma at 37 degrees C. The TEM studies along with lipid-mixing assays and FACS analysis indicated the lipid contact of the liposomal bilayers and bacterial cell membranes. Most importantly, our liposomal formulations reduced MICs for highly antibiotic-resistant strains and enhanced the antibiotics' penetration into the bacterial cells. For instance, bacterial eradication by liposomal tobramycin was 4-fold higher than free tobramycin. CONCLUSIONS: A liposomal drug delivery system might enhance the efficacy of commonly used aminoglycosides.
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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 | 0.001 | 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 | 0.000 | 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".