The combined use of paclitaxel-loaded nanoparticles with a low-molecular-weight copolymer inhibitor of P-glycoprotein to overcome drug resistance
Bibliographic record
Abstract
Two types of nanoparticles were prepared using the diblock copolymer methoxy poly(ethylene glycol)-block-poly(caprolactone) (MePEG-b-PCL), with either a short PCL block length, which forms micelles, or with a longer PCL block length, which forms kinetically "frozen core" structures termed nanospheres. Paclitaxel (PTX)-loaded micelles and nanospheres were evaluated for their cytotoxicity, cellular polymer uptake, and drug accumulation in drug-sensitive (Madin-Darby Canine Kidney [MDCK]II) and multidrug-resistant (MDR) P-glycoprotein (P-gp)-overexpressing (MDCKII-MDR1) cell lines. Both types of PTX-loaded nanoparticles were equally effective at inhibiting proliferation of MDCKII cells, but PTX-loaded micelles were more cytotoxic than nanospheres in MDCKII-MDR1 cells. The intracellular accumulation of both PTX and the diblock copolymers were similar for both nanoparticles, suggesting that the difference in cytotoxicity might be due to the different drug-release profiles. Furthermore, the cytotoxicity of these PTX-loaded nanoparticles was enhanced when these systems were subsequently or concurrently combined with a low-molecular-weight MePEG-b-PCL diblock copolymer, which we have previously demonstrated to be an effective P-gp inhibitor. These results suggest that the dual functionality of MePEG-b-PCL might be useful in delivering drug intracellularly and in modulating P-gp in order to optimize the cytotoxicity of PTX in multidrug-resistant cells.
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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".