Supramolecular Nanostructures Based on Cyclodextrin and Poly(ethylene oxide): Syntheses, Structural Characterizations and Applications for Drug Delivery
Bibliographic record
Abstract
Cyclodextrins (CDs) have been extensively studied as drug delivery carriers through host⁻guest interactions. CD-based poly(pseudo)rotaxanes, which are composed of one or more CD rings threading on the polymer chain with or without bulky groups (or stoppers), have attracted great interest in the development of supramolecular biomaterials. Poly(ethylene oxide) (PEO) is a water-soluble, biocompatible polymer. Depending on the molecular weight, PEO can be used as a plasticizer or as a toughening agent. Moreover, the hydrogels of PEO are also extensively studied because of their outstanding characteristics in biological drug delivery systems. These biomaterials based on CD and PEO for controlled drug delivery have received increasing attention in recent years. In this review, we summarize the recent progress in supramolecular architectures, focusing on poly(pseudo)rotaxanes, vesicles and supramolecular hydrogels based on CDs and PEO for drug delivery. Particular focus will be devoted to the structures and properties of supramolecular copolymers based on these materials as well as their use for the design and synthesis of supramolecular hydrogels. Moreover, the various applications of drug delivery techniques such as drug absorption, controlled release and drug targeting based CD/PEO supramolecular complexes, are also discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".