Targeted Delivery of Amantadine-loaded Methacrylate Nanosphere-ligands for the Potential Treatment of Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
PURPOSE: This study aimed to develop and analyse poly(DL-lactic acid)-methacrylic acid nanospheres bound to the chelating ligand diethylenetriaminepentaacetic acid (DTPA) for the targeted delivery of amantadine in Amyotrophic Lateral Sclerosis (ALS). METHODS: The nanospheres were prepared by a double emulsion solvent evaporation technique statistically optimized employing a 3-Factor Box-Behnken experimental design. Analysis of the particle size, zeta potential, polydispersity (Pdl), morphology, drug entrapment and drug release kinetics were carried out. RESULTS: The prepared nanospheres were determined to have particle sizes ranging from 68.31 to 113.6 nm (Pdl ≤ 0.5). An initial burst release (50% of amantadine released in 24 hr) was also obtained, followed by a prolonged release phase of amantadine over 72 hr. Successful conjugation of the chelating ligand onto the surface of the optimised nanospheres was thereafter achieved and confirmed by TEM. The synthesized modified nanospheres were spherical in shape, 105.6 nm in size, with a PdI of 0.24 and zeta potential of -28.0 mV. Conjugation efficiency was determined to be 74%. In vitro and ex vivo cell study results confirmed the intracellular uptake of the modified nanospheres by the NSC-34 cell line and the non-cytotoxicity of the synthesized nanospheres. CONCLUSIONS: Biocompatible amantadine-loaded nanospheres were successfully designed, characterized and optimized employing the randomized Box-Behnken statistical design. Delivery of amantadine over 72 hrs was achieved, with the nanospheres being of a size capable of internalization by the NSC- 34 cells. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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) | 0.001 | 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".