Bile Acid-Based Drug Delivery Systems for Enhanced Doxorubicin Encapsulation: Comparing Hydrophobic and Ionic Interactions in Drug Loading and Release
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Doxorubicin (Dox) is a drug of choice in the design of drug delivery systems directed toward breast cancers, but is often limited by loading and control over its release from polymer micelles. Bile acid-based block copolymers present certain advantages over traditional polymer-based systems for drug delivery purposes, since they can enable a higher drug loading via the formation of a reservoir through their aggregation process. In this study, hydrophobic and electrostatic interactions are compared for their influence on Dox loading inside cholic acid based block copolymers. Poly(allyl glycidyl ether) (PAGE) and poly(ethylene glycol) (PEG) were grafted from the cholic acid (CA) core yielding a star-shaped block copolymer with 4 arms (CA-(PAGE-b-PEG)4) and then loaded with Dox via a nanoprecipitation technique. A high Dox loading of 14 wt % was achieved via electrostatic as opposed to hydrophobic interactions with or without oleic acid as a cosurfactant. The electrostatic interactions confer a pH responsiveness to the system. 50% of the loaded Dox was released at pH 5 in comparison to 12% at pH 7.4. The nanoparticles with Dox loaded via hydrophobic interactions did not show such a pH responsiveness. The systems with Dox loaded via electrostatic interactions showed the lowest IC50 and highest cellular internalization, indicating the pre-eminence of this interaction in Dox loading. The blank formulations are biocompatible and did not show cytotoxicity up to 0.17 mg/mL. The new functionalized star block copolymers based on cholic acid show great potential as drug delivery carriers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 it