Chitosan−Alginate Microcapsules for Oral Delivery of Egg Yolk Immunoglobulin (IgY)
Bibliographic record
Abstract
Chitosan-alginate microcapsules were evaluated as a method of oral delivery of IgY antibodies. Physical characteristics, encapsulation efficiency (EE%), the loading capacity for IgY (IgY loading percentage, %, w/w of microcapsules), gastro-resistance, and release characteristics of these microcapsules in vitro under varying pH were investigated. Optimum physical factors were established for preparation of homogeneous, spherical, and smooth microcapsules. IgY loading% was not significantly altered by pH of the encapsulation medium. Encapsulation efficiency was highest (73.93%) at a pH of 3.5, above which EE% decreased significantly (p < 0.05). IgY was released from microcapsules upon exposure to simulated intestinal fluid (SIF, pH 6.8), and decreasing pH increased significantly IgY release (p < 0.05). The stability of IgY in simulated gastric fluid (SGF, pH 1.2) was greatly improved by encapsulation in chitosan-alginate microcapsules, and the residual activity was not affected by pH of the encapsulation medium. Moreover, microencapsulated IgY was significantly resistant to pepsin hydrolysis. This approach may enable intact IgY to reach target microorganisms within the lower digestive tract.
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) | 0.001 | 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".