Swollen Micelles for the Preparation of Gated, Squeezable, pH-Responsive Drug Carriers
Bibliographic record
Abstract
Natural variations in pH levels of tissues in the body make it an attractive stimuli to trigger drug release from a delivery vehicle. A number of such carriers have been developed but achieving high drug loading combined with low leakage at physiological pH and tunable controlled release at the site of action is an ongoing challenge. Here we report a novel strategy for the synthesis of entirely hydrophilic stimuli-responsive nanocarriers with high passive loading efficiency of doxorubicin (DOX), which show good stability at pH 7 and rapid tunable drug release at intracellular pH. The particles ( D h = 120–150 nm), are prepared by cross-linking the core of swollen micelles of the triblock copolymer poly[poly(ethylene glycol) methyl ether methacrylate- b - N, N ′-di(methylamino)ethyl methacrylate- b - tert -butyl methacrylate] (poly(PEGMEM A) - b - PDMAEMA- b -P t BMA)). After subsequent deprotection of the tert -butyl groups a hydrophilic poly(methacrylic acid) (PMAA) core is revealed. Due to the negative charge in the acidic core the particles absorb 100% of the DOX from solution at pH 7 at up to 50 wt % DOX/polymer, making them extremely simple to load. Unlike other systems, the DMAEMA “gating” shell ensures low drug leakage at pH 7, whereas physical shrinkage of the MAA core allows rapid release below pH 6. The particles deliver DOX with high efficiency to human pancreatic cancer AsPC-1 cell lines, even lowering the IC50 of DOX. As the particles are stable as a dry powder and can be loaded with any mixture of positively charged drugs without complex synthetic or purification steps, we propose they will find use in a range of delivery applications.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".