Block and Random Copolymers Bearing Cholic Acid and Oligo(ethylene glycol) Pendant Groups: Aggregation, Thermosensitivity, and Drug Loading
Bibliographic record
Abstract
A series of block and random copolymers consisting of oligo(ethylene glycol) and cholic acid pendant groups were synthesized via ring-opening metathesis polymerization of their norbornene derivatives. These block and random copolymers were designed to have similar molecular weights and comonomer ratios; both types of copolymers showed thermosensitivity in aqueous solutions with similar cloud points. The copolymers self-assembled into micelles in water as shown by dynamic light scattering and transmission electron microscopy. The hydrodynamic diameter of the micelles formed by the block copolymer is much larger and exhibited a broad and gradual shrinkage from 20 to 54 °C below its cloud point, while the micelles formed by the random copolymers are smaller in size but exhibited some swelling in the same temperature range. Based on in vitro drug release studies, 78% and 24% paclitaxel (PTX) were released in 24 h from micelles self-assembled by the block and random copolymers, respectively. PTX-loaded micelles formed by the block and random copolymers exhibited apparent antitumor efficacy toward the ovarian cancer cells with a particularly low half-maximal inhibitory concentration (IC50) of 27.4 and 40.2 ng/mL, respectively. Cholic acid-based micelles show promise as a versatile and potent platform for cancer chemotherapy.
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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".