Cruciferin coating improves the stability of chitosan nanoparticles at low pH
Bibliographic record
Abstract
Encapsulation is an emerging technique to improve the solubility, permeability and bioavailability of bioactive compounds. Cruciferin, a major canola protein, has the potential to protect chitosan-based delivery systems under the gastric conditions due to its resistance to gastric digestion. Positively charged spherical nanoparticles with an average size of 165 nm were prepared. Two water-soluble and -insoluble model compounds (brilliant blue and β-carotene) were encapsulated. The characteristic studies of the particles showed that the chitosan-based core was coated by a cruciferin layer mainly through hydrogen bonding based on FTIR, DSC, surface hydrophobicity, dissociating and intrinsic fluorescence studies. The particles did not show toxicity to Caco-2 cells and their cellular uptake was observed using confocal microscopy. Release studies showed that the particles were resistant to simulated gastric and intestinal fluids and released less than 20% of the encapsulated compounds. Our results suggested that the particles are promising carriers for encapsulation of heat, pH and protease-degradable hydrophilic and hydrophobic bioactive compounds.
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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) | 0.001 | 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".