Preparation and In Vitro Drug Release Behavior of 1,10-Phenanthroline/β-cyclodextrin–poly (Glycidyl Methacrylate) Drug-Loaded Microspheres
Bibliographic record
Abstract
In this study, novel star-shaped polymers of β-cyclodextrin (β-CD)–poly (glycidyl methacrylate) (PGMA) were prepared by atom transfer radical polymerization (ATRP), formed from GMA and β-CD. In addition, the structure, properties and hydrophilicity of the β-CD-PGMA polymers thus prepared were systematically analyzed. 1,10-phenanthroline monohydrate (Phen)/β-CD-PGMA drug-loaded microspheres were prepared by emulsion solvent evaporation. The optimum preparation conditions were determined by orthogonal tests. Analysis results indicated that the performance of star-shaped polymers of β-CD-PGMA clearly changes, resulting in the increase of the contact angle from 17° to 72.5°, and their thermal degradation temperature was enhanced from 260 °C to 401 °C. Moreover, β-CD-PGMA drug-loaded microspheres with a smooth, spherical surface were successfully prepared, and the drug-loading capacity and average particle size of drug-loaded microspheres were 26.67 % and 10 μm, respectively. Drug release tests indicated that the release behavior of β-CD-PGMA drug-loaded microspheres conformed to Higuchi release kinetics, which exhibited a significant drug delivery capability. The release rate and utilization of β-CD-PGMA were greater than that of β-CD, demonstrating that β-CD-PGMA was more suitable as a drug delivery material.
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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".