Methoxy Poly(ethylene glycol)-<i>block</i>-Poly(δ-valerolactone) Copolymer Micelles for Formulation of Hydrophobic Drugs
Bibliographic record
Abstract
Six amphiphilic diblock copolymers based on methoxy poly(ethylene glycol) (MePEG) and poly(delta-valerolactone) (PVL) with varying hydrophilic and hydrophobic block lengths were synthesized via a metal-free cationic polymerization method. MePEG-b-PVL copolymers were synthesized using MePEG with Mn = 2000 or Mn = 5000 as the macroinitiator. 1H NMR and GPC analyses confirmed the synthesis of diblock copolymers with relatively narrow molecular weight distributions (Mn/Mw = 1.05-1.14). DSC analysis revealed that the melting temperatures (Tm) of the copolymers (47-58 degrees C) approach the Tm of MePEG as the PVL content is decreased. MePEG-b-PVL copolymer aggregates loaded with the hydrophobic anti-cancer drug paclitaxel were found to have effective mean diameters ranging from 31 to 970 nm depending on the composition of the copolymers. A MePEG-b-PVL copolymer of a specific composition was found to form drug-loaded micelles of 31 nm in diameter with a narrow size distribution and improve the apparent aqueous solubility of paclitaxel by more than 9000-fold. The biological activity of paclitaxel formulated in the MePEG-b-PVL micelles was confirmed in human MCF-7 breast and A2780 ovarian cancer cells. Furthermore, the biocompatibility of the copolymers was established in CHO-K1 fibroblast cells using a cell viability assay. The in vitro hydrolytic and enzymatic degradation of the micelles was also evaluated over a period of one month. The present study indicates that the MePEG-b-PVL copolymers are suitable biomaterials for hydrophobic drug formulation and delivery.
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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".