Probing Prolamin-Anthocyanin Interactions for the Rational Design of Plant-Based Encapsulation Systems
Bibliographic record
Abstract
Plant proteins are increasingly focused upon as alternatives to animal-derived macromolecules for the encapsulation of bioactives. The rational design of encapsulation carriers should be based on a solid understanding of the interactions between the proteins and bioactives. Encapsulation technology for food applications has focused predominantly on the protection and controlled release of hydrophobic bioactives. For hydrophilic molecules, although not less important from a nutritional and health perspective, significantly fewer encapsulation systems have been explored, designed and described. As hydrophilic molecules tend to partition into the aqueous food matrix, it is even more crucial to understand and to be able to modulate the interactions between the hydrophilic bioactive and the encapsulating matrix material in food relevant conditions. Therefore, examining the nature of the interactions between anthocyanins (ACNs), a hydrophilic bioactive, and prolamin plant proteins (gliadin, hordein, secalin, and avenin) is timely. These interactions were examined using steady-state and time-resolved luminescence spectroscopy techniques. The ACN-induced quenching of the prolamins intrinsic fluorescence emission did not follow a linear Stern-Volmer relationship, but rather displayed an upward curvature for all the prolamins tested. Hence, both static and dynamic quenching likely occurred in the prolamin-ACN systems. The quenching mechanism was further explored based on the changes in fluorescence lifetime as ACN concentration increased. As the independent lifetimes of the prolamin-ACN combinations did not decrease discernibly as a function of ACN concentration, static quenching is presumably the predominant quenching mechanism. The thermodynamic parameters revealed that the interactions between secalin- and avenin-ACN are mainly driven by the hydrophobic effect, while those between gliadin- and hordein-ACN are dominated by ionic interactions. Zeta-potential measurements support the dominant ionic interactions found for gliadin and hordein. The insights gained in this research will serve as a sound basis for further studies focusing on matrix selection with regard to creating performant encapsulation systems for ACNs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".