Probiotic Ferulic Acid Esterase Active Lactobacillus fermentum NCIMB 5221 APA Microcapsules for Oral Delivery: Preparation and in Vitro Characterization
Bibliographic record
Abstract
Probiotics possess potential therapeutic and preventative effects for various diseases and metabolic disorders. One important limitation for the oral delivery of probiotics is the harsh conditions of the upper gastrointestinal tract (GIT) which challenge bacterial viability and activity. One proposed method to surpass this obstacle is the use of microencapsulation to improve the delivery of bacterial cells to the lower GIT. The aim of this study is to use alginate-poly-L-lysine-alginate (APA) microcapsules to encapsulate Lactobacillus fermentum NCIMB 5221 and characterize its enzymatic activity and viability through a simulated GIT. This specific strain, in previous research, was characterized for its inherent ferulic acid esterase (FAE) activity which could prove beneficial in the development of a therapeutic for the treatment and prevention of cancers and metabolic disorders. Our findings demonstrate that the APA microcapsule does not slow the mass transfer of substrate into and that of the FA product out of the microcapsule, while also not impairing bacterial cell viability. The use of simulated gastrointestinal conditions led to a significant 2.5 log difference in viability between the free (1.10 × 104 ± 1.00 × 103 cfu/mL) and the microencapsulated (5.50 × 106 ± 1.00 × 105 cfu/mL) L. fermentum NCIMB 5221 following exposure. The work presented here suggests that APA microencapsulation can be used as an effective oral delivery method for L. fermentum NCIMB 5221, a FAE-active probiotic strain.
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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".