Temperature‐Sensitive Microcapsules Containing Lactoferrin and Their Action Against <i>Carnobacterium viridans</i> on Bologna
Bibliographic record
Abstract
ABSTRACT: Lactoferrin (LF) was encapsulated in 2 types of emulsion to protect it from contact with agents like divalent cations, which interfere with its antimicrobial activity. First, paste‐like microcapsules were prepared as water‐in‐oil (W 1 /O) emulsions from mixtures of 20% w/v LF in distilled water, 20% w/v LF in 3% w/v sodium lactate or in 20 mM sodium bicarbonate, which were emulsified with an oil mixture of 22% butter fat plus 78% corn oil and 0.1% polyglycerol polyricinoleate. Second, freeze‐dried double emulsion (W 1 /O/W 2 ), powdered microcapsules were produced following emulsification of paste‐like microcapsules in an external aqueous phase (W 2 ) consisting of a denatured whey protein isolate (WPI) solution. The release of LF from the W 1 /O microcapsules was dependent on temperature and NaCl concentration. LF was not released from the W 1 /O emulsion at <5.5 °C. Its release was greater from W 1 /O microcapsules when suspended in 5% aqueous NaCl than in water at ≥10 °C, whereas LF release from freeze‐dried microcapsules was not controlled by temperature change. Paste‐like microcapsules were incorporated in edible WPI packaging film to test the antimicrobial activity of LF against a meat spoilage organism Carnobacterium viridans . The film was applied to the surface of bologna after its inoculation with the organism and stored under vacuum at 4 or 10 °C for 28 d. The growth of C. viridans was delayed at both temperatures and microencapsulated LF had greater antimicrobial activity than when unencapsulated. The temperature‐sensitive property of the W 1 /O microcapsules was reduced when they were incorporated into a WPI film.
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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".