Quaternary Ammonium β-Cyclodextrin Nanoparticles for Enhancing Doxorubicin Permeability across the In Vitro Blood−Brain Barrier
Bibliographic record
Abstract
This study describes novel quaternary ammonium beta-cyclodextrin (QAbetaCD) nanoparticles as drug delivery carriers for doxorubicin (DOX), a hydrophobic anticancer drug, across the blood-brain barrier (BBB). QAbetaCD nanoparticles show 65-88 nm hydrodynamic radii with controllable cationic properties by adjusting the incorporated amount of quaternary ammonium group in their structure. ATR-FTIR studies confirm the complexation between the QAbetaCD nanoparticles and DOX. QAbetaCD nanoparticles are not toxic to bovine brain microvessel endothelial cells (BBMVECs) at concentrations up to 500 microg x mL(-1). They also do not change the integrity of BBMVEC monolayers, an in vitro BBB model, including transendothelial electrical resistance value, Lucifer yellow permeability, tight junction protein occludin and ZO-1 expression and morphology, cholesterol extraction, and P-glycoprotein (P-gp) expression and efflux activity, at a concentration of 100 microg x mL(-1). Some QAbetaCD nanoparticles not only are twice as permeable as dextran (M(w) = 4000 g x mol(-1)) control, but also enhance DOX permeability across BBMVEC monolayers by 2.2 times. Confocal microscopy and flow cytometry measurements imply that the permeability of QAbetaCD nanoparticles across the in vitro BBB is probably due to endocytosis. DOX/QAbetaCD complexes kill U87 cells as effectively as DOX alone. However, QAbetaCD nanoparticles completely protect BBMVECs from cytotoxicity of DOX at 5 and 10 microM after 4 h incubation. The developed QAbetaCD nanoparticles have great potential in safely and effectively delivering DOX and other therapeutic agents across the BBB.
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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".