Investigation of Genipin Cross-Linked Microcapsule for Oral Delivery of Live Bacterial Cells and Other Biotherapeutics: Preparation and In Vitro Analysis in Simulated Human Gastrointestinal Model
Bibliographic record
Abstract
Oral therapy utilizing engineered microorganisms has shown promise in the treatment of many diseases. By microencapsulation, viable cells can overcome the harsh gastrointestinal (GI) environment and secrete needed therapeutics into the gut. These engineered cells should be encased without escaping into the GI tract for safety concerns, thus robust microcapsule membrane is requisite. This paper examined the GI performance of a novel microcapsule membrane using a dynamic simulated human GI model. Results showed that the genipin cross-linked alginate-chitosan (GCAC) microcapsules possessed strong resistance to structural disintegration in the simulated GI environment. Leakage of encapsulated high molecular weight dextran, a model material to be protected during the simulated GI transit, was negligible over 72 h of exposure, in contrast to considerable leakage of dextran from the non-cross-linked counterparts. These microcapsules did not alter the microflora and enzymatic activities in the simulated human colonic media. This study suggested the potential of the GCAC microcapsules for oral delivery of live microorganisms and other biotherapeutics.
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".