Near-infrared light sensitive polypeptide block copolymer micelles for drug delivery
Bibliographic record
Abstract
A new biocompatible block copolymer (BCP) composed of poly(ethylene oxide) (PEO) and poly(L-glutamic acid) bearing a number of 6-bromo-7-hydroxycoumarin-4-ylmethyl groups, PEO114-b-P(LGA0.62-co-COU0.38)34, was prepared for near-infrared (NIR) light-induced drug delivery. We demonstrate that micelles of PEO114-b-P(LGA0.62-co-COU0.38)34 could be disrupted by 794 nm NIR light excitation via two-photon absorption. This was linked to the high two-photon absorption cross-section of the coumarin moiety. Disruption followed from the NIR light-induced removal of coumarin groups from the polypeptide block that shifted the hydrophilic–hydrophobic balance toward the destabilization of the micelles in aqueous solution. Using NIR light-triggered disruption of BCP micelles, we investigated the release of an antibacterial drug (Rifampicin) and an anticancer drug (Paclitaxel) loaded into the photosensitive BCP micelles. We found that the two drugs could be released effectively upon NIR light exposure of the micellar solution. To our knowledge, this is the first study of NIR light-triggered disruption of biocompatible polypeptide BCP micelles and its use for drug release. This is a step forward towards light-controllable drug 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) | 0.000 | 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 | 0.001 |
| 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".