Polymer assisted entrapment of netilmicin in PLGA nanoparticles for sustained antibacterial activity
Bibliographic record
Abstract
This study was aimed to develop poly(dl-lactide-co-glycolide) (PLGA) nanoparticle of highly water soluble antibiotic drug, netilmicin sulfate (NS) with improved entrapment efficiency (EE) and antibacterial activity. Dextran sulfate was introduced as helper polymer to form electrostatic complex with NS. Nanoparticles were prepared by double emulsification method and optimized using 2(5-1) fractional factorial design. EE was mainly influenced by dextran sulfate: NS charge ratio and PLGA concentration, whereas particle size (PS) was affected by all factors examined. The optimized NS-loaded-NPs had EE and PS of 93.23 ± 2.7% and 140.83 ± 2.4 nm respectively. NS-loaded-NPs effectively inhibited bacterial growth compared to free NS. Sustained release protected its inactivation and reduced the decline in its killing activity over time even in presence of bronchial cells. A MIC value of 18 μg/mL was observed for NPs on P. aeruginosa. Therefore, NPs with sustained bactericidal efficiency against P. aeruginosa may provide therapeutic benefit in chronic pulmonary infection, like cystic fibrosis.
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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".