Double-walled microspheres loaded with meglumine antimoniate: preparation, characterization and<i>in vitro</i>release study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to fabricate double-walled poly(lactide-co-glycolide) (PLGA) microspheres to increase encapsulation efficiency and avoid rapid release of hydrophilic drugs such as meglumine antimoniate. METHODS: In this study, double-walled and one-layered microspheres of PLGA were prepared using the emulsion solvent evaporation technique to better control the release of a hydrophilic drug, meglumine antimoniate (Glucantime®), which is the first choice treatment of cutaneous leishmaniasis. The effect of hydrophobic coating on microspheres' size, morphology, encapsulation efficiency and drug release characteristics was evaluated. Furthermore, the presence of antimony in meglumine antimoniate made it possible to observe the drug distribution within the microspheres' cross section by means of energy dispersive X-ray spectroscopy. RESULTS: Drug distribution images confirmed accumulation of the drug within the inner core of double-walled microspheres. In addition, these microspheres encapsulated the drug more efficiently up to 87% and demonstrated reduced initial burst and prolonged release compared to one-layered microspheres. These superiorities make double-walled microspheres an optimum candidate for sustained delivery of hydrophilic drugs. CONCLUSION: Double-walled microspheres provide some advantages over traditional microspheres overcoming most of their limitations. Double-walled microspheres were found to be more efficient than their corresponding one-layered microspheres in terms of encapsulation efficiencies and release characteristics.
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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".