Encapsulation of Milk β-Lactoglobulin by Chitosan Nanoparticles
Bibliographic record
Abstract
Naturally occurring polymers, such as chitosan, have been extensively studied as carriers for therapeutic protein and gene delivery systems. β-Lactoglobulin (β-LG) is a member of the lipocalin superfamily of transporters for small hydrophobic molecules. We examine the binding of milk β-lactoglobulin with chitosan of different sizes such as chitosan 15, 100, and 200 KD in aqueous solution at pH 5-6, using FTIR, CD, and fluorescence spectroscopic methods. Structural analysis showed that chitosan binds β-LG via both hydrophilic and hydrophobic contacts with overall binding constants of K(β-LG-ch-15) = 4.1 (±0.4) × 10(2) M(-1), K(β-LG-ch-100) = 7.2 (±0.6) × 10(4) M(-1), and K(β-LG-ch-200) = 3.9 (±0.5) × 10(3) M(-1) with the number of bound protein per chitosan (n) 0.9 for ch-15, 0.6 for ch-100, and 1.6 for ch-200. Chitosan 100 KD forms stronger complexes with β-LG than chitosans 200 and 15 KD. Polymer binding did not alter protein conformation inducing structural stabilization. Chitosan 100 is a stronger protein transporter than chitosan 15 and 200 KD.
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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".