Design and Evaluation of Multifunctional Nanocarriers for Selective Delivery of Coenzyme Q10 to Mitochondria
Bibliographic record
Abstract
Impairments of mitochondrial functions have been associated with failure of cellular functions in different tissues, leading to various pathologies. We report here a mitochondria-targeted nanodelivery system for coenzyme Q10 (CoQ10) that can reach mitochondria and deliver CoQ10 in adequate quantities. Multifunctional nanocarriers based on ABC miktoarm polymers (A = poly(ethylene glycol (PEG), B = polycaprolactone (PCL), and C = triphenylphosphonium bromide (TPPBr)) were synthesized using a combination of click chemistry with ring-opening polymerization, self-assembled into nanosized micelles, and were employed for CoQ10 loading. Drug loading capacity (60 wt %), micelle size (25-60 nm), and stability were determined using a variety of techniques. The micelles had a small critical association concentration and were colloidally stable in solution for more than 3 months. The extraordinarily high CoQ10 loading capacity in the micelles is attributed to good compatibility between CoQ10 and PCL, as indicated by the low Flory-Huggins interaction parameter. Confocal microscopy studies of the fluorescently labeled polymer analog together with the mitochondria-specific vital dye label indicated that the carrier did indeed reach mitochondria. The high CoQ10 loading efficiency allowed testing of micelles within a broad concentration range and provided evidence for CoQ10 effectiveness in two different experimental paradigms: oxidative stress and inflammation. Combined results from chemical, analytical, and biological experiments suggest that the new miktoarm-based carrier provides a suitable means of CoQ10 delivery to mitochondria without loss of drug effectiveness. The versatility of the click chemistry used to prepare this new mitochondria-targeting nanocarrier offers a widely applicable, simple, and easily reproducible procedure to deliver drugs to mitochondria or other intracellular organelles.
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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 | 0.001 | 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) | 0.000 | 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".