Preparation and <i>in vitro</i> analysis of microencapsulated live <i>Lactobacillus fermentum</i> 11976 for augmentation of feruloyl esterase in the gastrointestinal tract
Bibliographic record
Abstract
FA (ferulic acid) is a well-known phenolic phytochemical present in plant cell walls. Various studies have indicated that FA has many physiological functions in the prevention of chronic disease. It has been shown to play an important chemoprotective role in degenerative diseases. FA also shows strong antioxidant and nitrite-scavenging potential and anticarcinogenic and antiinflammatory properties. The in vivo physiological importance of FA depends on its availability for absorption. Dietary fibre-bound FA is partially released by gut micro-organisms; however, the concentration of the released FA is too low to act as a chemopreventive agent. Therefore it is important to augment the bioavailability of FA to appreciate more fully its real physiological effect. This paper evaluates the suitability of the alginate-poly(L-lysine)-alginate microcapsules for oral delivery of live feruloyl esterase-producing Lactobacillus fermentum 11976 cells, in vitro, by using a dynamic simulated human GI (gastrointestinal) model. The present study shows that microencapsulated L. fermentum 11976 cells can efficiently break down a FA-containing substrate, and establishes the biotechnological basis for their use in supplementing the bioavailability of dietary FA in the intestine.
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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) | 0.001 | 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".