Development of Nanostructured Lipid Carriers for the Delivery of Idebenone in Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay
Bibliographic record
Abstract
Abstract Oxidative stress occurs when physiological antioxidant systems do not manage to counteract the excessive intracellular production of reactive oxygen species (ROS), which accumulate leading to irreversible oxidation of DNA and other biomacromolecules, and thus to the onset of pathological conditions. Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a neurodegenerative disease characterized by autosomal recessive mutations in the sacsin gene (SACS). It has been demonstrated that cells of ARSACS patients show bioenergetic and mitochondrial impairment, denoted by reduced respiratory chain activities and ATP synthesis. In order to design a suitable therapy for ARSACS, it is essential to consider that treatments need to cross the blood–brain barrier (BBB), a specialized structure that separates the subtle environment of the brain from blood circulation. Nanostructured lipid carriers (NLCs), constituted by a solid lipid shell and a liquid lipid phase in the core, have been fabricated for loading hydrophobic molecules, improving their bioavailability. Idebenone (IDE), a synthetic analogue of coenzyme Q10, is able to inhibit lipid peroxidation and detoxify several free radicals. However, because of its poor solubility, it requires ad hoc drug-delivery systems for enhancing its pharmacokinetic properties, preventing undesired cytotoxicity. In this work, NLCs loaded with idebenone (IDE-NLCs) have been prepared. The nanovectors have been physicochemically characterized, and their biological activity has been evaluated on different central nervous system cell lines. IDE-NLCs demonstrated to be stable in water and in cell culture media, and showed a sustained drug release profile. Interestingly, preliminary data demonstrated their ability to permeate an in vitro BBB model. Their protective antioxidant activity in human healthy primary skin fibroblasts and their therapeutic efficacy in ARSACS-derived primary skin fibroblasts have been also investigated, showing their potential for future development as therapeutic agents.
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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".