Gelation of Native β-Lactoglobulin Induced by Electrostatic Attractive Interaction with Xanthan Gum
Bibliographic record
Abstract
The mechanism and kinetics of the electrostatic gelation of native beta-lactoglobulin-xanthan gum mixtures in aqueous solution is reported. The total biopolymer concentration at which gelation was obtained was extremely low (0.1 wt %) compared to the usually tested concentrations for protein-polysaccharide mixed gels (4-12 wt %). This is, to our knowledge, the first time that oppositely charged proteins and polysaccharides are reported to form a gel without applying any treatment to denature the protein (e.g. heating, enzymatic hydrolysis) and at such low concentrations. Static light-scattering and viscoelastic measurements allowed determination of the gelation kinetics. It was found that the gelation process initiated following a similar path as that of an associative phase separation process, i.e., with the formation of primary and interpolymeric electrostatic complexes. However, interpolymeric complexes were able to form clusters and junction zones that resulted in the freeze-in of the whole structure at the point of gelation. The formed gel is therefore a coupled-gel, that is, a gel that has junction zones involving two different molecules. The structuration of xanthan gum, even at these low concentrations, may have played a role in the structuration process. Due to the electrostatic nature of the gels, there was an optimum pH and macromolecular ratio at which the stability of the gels was maximal. This was related to the existence of a stoichiometric electrical charge equivalence pH, where molecules carry equal but opposite charges and protein-polysaccharide interactions are at their maximum.
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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".