Degradable Thermoresponsive Core Cross-Linked Micelles: Fabrication, Surface Functionalization, and Biorecognition
Bibliographic record
Abstract
We report on the fabrication of core cross-linked (CCL) micelles possessing thermoresponsive and degradable cores and biocompatible coronas cofunctionalized with carbohydrate and biotin moieties. Well-defined poly(2-aminoethylmethacrylamide) (PAEMA) homopolymer was first synthesized in a controlled fashion via the reversible addition-fragmentation chain transfer (RAFT) process. CCL micelles comprising of well-solvated PAEMA coronas and thermoresponsive cores were then obtained in a one-pot manner via RAFT copolymerization of N-isopropylacrylamide (NIPAM) and bis(2-methacryloyloxyethyl) disulfide (DSDMA) difunctional monomers by employing PAEMA as the macro-RAFT agent. In the presence of dithiothreitol (DTT), the obtained CCL micelles can be disintegrated into unimers due to the cleavage of disulfide cross-linkers, whereas deswelling of micellar cores can be achieved via heating above the phase transition temperature of PNIPAM. Thus, the release profiles of this type of nanocarriers are expected to be triggered by temperature and thiols or a combination of both. Furthermore, primary amine residues located within coronas of CCL micelles have been further exploited for surface functionalization with biotin and carbohydrate moieties, rendering them biocompatible and bioactive. The availability of biotin within the coronas of CCL micelles was confirmed by HABA/avidin binding assay and Diffractive Optics Technology (DOT) biosensing instrument. After the micelles were immobilized on the surface of avidin-sensor chip, specific biorecognition of the available biotins and carbohydrate moieties on the CCL micelles was further confirmed. We expect that this novel type of bioactive and potentially biocompatible CCL micelles can be employed as smart nanocarriers for targeted drug delivery and controlled release.
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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 | 0.001 | 0.001 |
| 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".