Application of Pickering emulsions in probiotic encapsulation- A review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Probiotics are live microorganisms that confer health benefits to host organisms when consumed in adequate amounts and are often incorporated into foods for human consumption. However, this has negative implications on their viability as large numbers of these beneficial bacteria are deactivated when subjected to harsh conditions during processing, storage, and passage through the gastrointestinal tract. To address these issues, numerous studies on encapsulation techniques to protect probiotics have been conducted. This review focuses on emulsion technology for probiotic encapsulation, with a special focus on Pickering emulsions. Pickering emulsions are stabilized by solid particles, which adsorb strongly onto the liquid-liquid interfaces to prevent aggregation. Pickering emulsions have demonstrated enhanced stability, high encapsulation efficiency, and cost-effectiveness compared to other encapsulation techniques. Additionally, Pickering emulsions are regarded as safe and biocompatible and utilize natural materials, such as cellulose and chitosan derived from plants, shellfish, and fungi, which may also be viewed as more acceptable in food systems than common synthetic and natural molecular surfactants. This article reviews the current status of Pickering emulsion use for probiotic delivery and explores the potential of this technique for application in other fields, such as livestock farming, pet food, and aquaculture.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it