Application of <scp><i>γ</i>‐cyclodextrin</scp>‐lysozyme as host materials for encapsulation of curcumin: characterization, stability, and controlled release properties
Bibliographic record
Abstract
BACKGROUND: In this study, a safe and relatively stable γ-cyclodextrin-lysozyme (γ-CD-Lys) was synthesized using epichlorohydrin as the cross-linking agent, and curcumin was successfully encapsulated in γ-CD-Lys. RESULTS: The successful Lys grafting onto γ-CD can be demonstrated by a high grafting ratio (79.02%) and was further confirmed by Fourier transform infrared (FTIR) band shifts and the new signal obtained at δ 2.75 in proton nuclear magnetic resonance. The encapsulation efficiency value of γ-CD-Lys was 76.74%, and the successful encapsulation of curcumin into γ-CD-Lys was confirmed by crystal structure change, increased melting point, and FTIR band shifts. The intermolecular bonds results suggested that associative forces between curcumin and γ-CD-Lys were electrostatic interaction, hydrogen bonds interaction, and hydrophobic interaction. The designed nanoparticles had excellent stability at low pH and low salt concentration. The release rate of these nanoparticles was inhibited in simulated gastric conditions, whereas it increased significantly in intestinal media. Simulated gastrointestinal digestion experiments further confirmed that nanoparticles showed higher bioaccessibility (86.05%) compared with curcumin (58.82%). CONCLUSION: Overall, our study showed that the nanoparticles were highly promising for delivering curcumin because of their enhanced functional attributes and stabilization in acid or low salt environments. Also, it was an excellent wall material for targeting hydrophobic bioactive compounds in the intestinal tract via oral administration. © 2022 Society of Chemical Industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".