Microencapsulation of Probiotic <i>Streptococcus salivarius</i> LAB813
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Probiotics are living microorganisms that confer a health benefit on the host when administered in adequate amounts. Streptococcus salivarius, a commensal bacterium found in the oral cavity, has been shown to secrete antimicrobial peptides and can be used as probiotics. This study aimed to develop a delivery system for the probiotic LAB813, a novel S. salivarius strain first identified in the laboratory. Probiotics can be delivered and protected through the encapsulation of biomaterials such as polysaccharides. Their biocompatibility, biodegradability, user-friendliness, and ease of access make polysaccharides useful for encapsulating probiotics. Alginate (Alg) and chitosan (Ch) are naturally obtained polysaccharides and, hence, tested for LAB813 encapsulation. An extrusion method of encapsulation was performed to form Alg microcapsules (Alg-LAB813), some of which were coated with Ch (Alg-LAB813-Ch) to provide dual-layered protection. Inhibitory assays of the Alg-LAB813 and Alg-LAB813-Ch microcapsules were assayed against an indicator strain. Alg-LAB813-Ch microcapsules showed superior antibacterial properties compared to Alg-LAB813 microcapsules over 24 h and when subject to temperatures ranging from 4 to 68 °C. In addition, Alg-LAB813-Ch microcapsules retained antibacterial activity for up to 28 days of storage at 4 °C. The strong and sustained inhibitory activities of Ch-coated Alg encapsulated LAB813 signify the potential for their use to improve oral health.
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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) | 0.001 | 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".