Antibacterial Efficacy of Gentamicin Encapsulated in pH-Sensitive Liposomes against an In Vivo <i>Salmonella enterica</i> Serovar Typhimurium Intracellular Infection Model
Bibliographic record
Abstract
Encapsulation of gentamicin in liposomes can be used to achieve intracellular delivery and broaden the clinical utility of this drug. We have previously described a novel, rationally designed, pH-sensitive liposomal carrier for gentamicin that has superior in vitro efficacy against intracellular infections compared to the efficacies of both free gentamicin and non-pH-sensitive liposomal controls. This liposomal carrier demonstrated pH-sensitive fusion that was dependent on the presence of unsaturated phosphatidylethanolamine (PE) and the pH-sensitive lipid N-succinyldioleoyl-PE. The pharmacokinetics and biodistribution of the free and liposomal gentamicin were examined in mice bearing a systemic Salmonella enterica serovar Typhimurium infection. Encapsulation of gentamicin in pH-sensitive liposomes significantly increased the concentrations of the drug in plasma compared to those of free gentamicin. Furthermore, the levels of accumulation of drug in the infected liver and spleen were increased by 153- and 437-fold, respectively, as a result of liposomal encapsulation. The increased accumulation of gentamicin in the liver and spleen effected by liposomal delivery was associated with 10(4)-fold greater antibacterial activity than that associated with free gentamicin in a murine salmonellosis model. These pH-sensitive liposomal antibiotic carriers with enhanced in vitro activity could be used to improve both in vivo intracellular drug delivery and biological activity.
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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".