Stable, Bioresponsive, and Macrophage-Evading Polyurethane Micelles Containing an Anionic Tripeptide Chain Extender
Bibliographic record
Abstract
Polymeric nanocarriers have been extensively used in medicinal applications for drug delivery. However, intravenous nanocarriers circulating in the blood will be rapidly cleared from the mononuclear macrophage system. The surface physicochemical characterizations of nanocarriers are the primary factors to determine their fate in vivo, such as evading the reticuloendothelial system, exhibiting long blood circulation times, and accumulating in the targeted site. In this work, we develop a series of polyurethane micelles containing segments of an anionic tripeptide, hydrophilic mPEG, and disulfide bonds. It is found that the long hydrophilic mPEG can shield the micellar surface and have a synergistic effect with the negatively charged tripeptide to minimize macrophage phagocytosis. Meanwhile, the disulfide bond can rapidly respond to the intracellular reduction environment, leading to the acceleration of drug release and improvement of the therapeutic effect. Our results verify that these anionic polyurethane micelles hold great potential in the development of the stealth immune system and controllable intracellular drug transporters.
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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".