AB082. Gold nanoparticles as a new drug vector for glaucoma therapy
Bibliographic record
Abstract
Background: Glaucoma is an optical neuropathy affecting over 67 million people in the world. Efficiency of current active molecules, as travoprost (hydrophobic) is limited when administered by ophthalmic drops. Indeed, more than 99.9% is discarded due to multiple factors including lacrimal drainage. Low retention time of drugs at the cornea leads to their poor penetration. The aim of the project is to develop a drug delivery system allowing the drug penetration through biological barriers. Our hypothesis is that a drug delivery system based on gold nanoparticles should enhance the efficiency of the drugs. The main objective is to study the encapsulation ability of gold nanoparticles towards travoprost. The specific objectives are (I) the synthesis and characterizations of gold nanoparticles; (II) the establishment of the encapsulation protocol; (III) the method development of the separation of free and encapsulated drugs and; (IV) the quantification of the encapsulated drugs. Methods: Gold nanoparticles were synthesized by a new method developed in our laboratory. An encapsulation protocol was settled using aqueous conditions at 37 °C. The separation of free and encapsulated drugs was performed with magnetic beads. The quantification of the encapsulated drugs was then performed by high performance liquid chromatography and confirmed by UV-visible spectroscopy. Results: Gold nanoparticles of 28±1 nm were synthesized and purified according to our new experimental conditions. The encapsulation protocol lasts 5 days in the optimised conditions. The separation method involving magnetic beads was optimized to get rid of non-specific interactions. The travoprost was incubated with the nanoparticles until the reach of equilibrium in solution. Conclusions: We showed that active molecules used for glaucoma therapy, as travoprost, can be encapsulated in gold nanoparticles. Further analysis will allow identifying the encapsulation properties of various gold nanoparticles, differing by their size, shape and chemical surface. These data suggest the possible improvements.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".